data analysis in legal research

Trending News

Related Practices & Jurisdictions

• Law Office Management
• Litigation / Trial Practice
• Communications, Media & Internet
• All Federal

Legal data analytics opens a new world of possibilities for law firms to achieve operational efficiency and improve outcomes for clients – all with existing data sources.

It’s likely that you already use legal analytics without realizing it but devising a strategy can help maximize your firm’s success. Here’s everything you need to know about legal data analytics.

What Are Legal Data Analytics?

Legal analytics is the process of including  data-driven insights  into the decision-making process for law firms, such as legal strategy, resource management, and matter forecasting. This offers a competitive advantage by providing full visibility and transparency into law firm operations.

Types of Legal Data Analytics

There are two types of legal data analytics: business and practice. The former focuses on data that are relevant to all businesses, while the latter is specific to legal practices. Each is broken down into specific topics.

Business Data Analysis

Financial Analysis:  At the end of the day, a law firm is still a business. Financial analysis is important to identify cost-saving opportunities, optimize billing processes, and assess profitability. This includes important financial statements like the income statement, balance sheet, and cash flow statement. Client Relationship Management (CRM):  CRM improves the client experience by enhancing client interactions, identifying cross-selling opportunities, and improving client retention rates. The CRM holds all your relevant client data, including case history, communication history, and demographics, segments the client base according to industry, revenue, or location, and provides granular details to personalize interactions. Marketing and Business Development:  Marketing analytics can help you understand your ideal client, where your practice stands compared to competitors, and how your marketing initiatives are performing. You can also learn where your prospective clients are coming from to determine the best marketing channels for your budget.

Practice Data Analytics

Case Outcome Prediction:  Predictive legal analytics provides forecasting for case timelines to the most probable outcome to build a case, devise litigation and negotiation strategies, and evaluate options. Legal Research and Document Analysis:  Legal research can be a time-consuming process, but it’s key in identifying the important precedents or statutes that provide a competitive edge. Legal research analytics helps you identify the relevant cases in your practice area more efficiently to spend more time developing your case strategy. Workflow Optimization : Lawyers often struggle with time management, but you can improve your firm’s workflows by analyzing data on workloads, case duration, and resource allocation. You’ll save time with streamlined processes and enhance your firm’s productivity and ensure that you’re allocating resources and delegating tasks effectively.

Why Should My Law Firm Track Legal Data

Legal data is important for all firms, big and small. Here’s why:

Strategic Decision-Making

With legal data, you can make informed decisions that are backed by evidence and trends instead of assumptions and biases. Whether you’re planning to branch into a new practice area or looking to expand your law firm into new markets or locations, you can rely on data insights for more favorable outcomes.

Client Service Improvement

The client experience is one of the most important aspects of staying competitive in the modern legal market. By tracking legal data, law firms can better understand client needs, preferences, and patterns to improve client satisfaction and loyalty.

Competitive Advantage

With increased competition and savvier clients, law firms often struggle to stay ahead and acquire new clients. Legal data gives you a competitive edge by identifying emerging trends, market opportunities, and potential risks, so you can stand out in a crowded market.

Performance Evaluation

Tracking legal data gives you insights to continuously improve your firm’s performance and identify areas for improvement. Data trends reveal strengths, weaknesses, and blind spots for an objective view of your performance and success.

How to Track Legal Data Analytics

Ready to include legal data analytics in your firm’s processes? Here’s how:

Define Key Metrics

It’s important to have a goal in mind and metrics to define success with legal analytics. Your metrics will vary depending on the type of analytics. For example, client acquisition, the cost to acquire a new client, and the average value of a client or case aid your  marketing  strategy, while realization rate, utilization rate, and billable hours inform your productivity. Clearly define these metrics to zero in on the relevant data.

Data Collection and Storage

You likely already have data for your firm in the form of financial records, client information, and marketing metrics, but you should have systems in place to collect and store it all. Implement processes to gather and organize it effectively, then store it in a secure and reliable data storage system.

Data Analysis Tools

Data analysis tools are key to successful legal analytics. You can rely on external tools like Excel or Power BI, but a comprehensive  law practice management  solution with reporting helps you home in on targeted, relevant data for your goals. With Bill4Time, you can get a robust view of your data from time tracking and billable hours to clients and matters. 

Team Collaboration and Training

Legal data analytics is a firmwide initiative that involves lawyers and support staff. All team members should be trained in the importance of legal data analytics and how to use your data  analysis  tools for insights. 

Cloud-based law practice management software offers a secure, centralized source for all your firm data that staff can access at any time, from anywhere. If you want some users to have limited access, you can customize permissions and track activity for full control and visibility.

Continuous Improvement

Legal analytics is an ongoing process. You should conduct regular sessions with staff and stay updated on the latest trends and developments in legal data analytics to enhance your processes and continue to derive meaningful insights.

Final Thoughts

Legal data analytics changes the way law firms and legal professionals use their time, strategize cases, enhance the client experience, and make informed business decisions. As the legal market becomes more competitive, legal data is the key to attracting clients, staying profitable, and encouraging future growth.

Current Legal Analysis

More from bill4time, upcoming legal education events.

Sign Up for e-NewsBulletins

• Platform Overview All-in-one legal research and workflow software
• Legal Research Unmetered access to primary and secondary sources
• Workflow Tools AI-powered tools for smarter workflows
• News & Analysis Paywall-free premium Bloomberg news and coverage
• Practical Guidance Ready-to-use guidance for any legal task
• Contract Solutions New: Streamlined contract workflow platform
• Introducing Contract Solutions Experience contract simplicity
• Watch product demo
• Law Firms Find everything you need to serve your clients
• In-House Counsel Expand expertise, reduce cost, and save time
• Government Get unlimited access to state and federal coverage
• Law Schools Succeed in school and prepare for practice
• Customer Cost Savings and Benefits See why GCs and CLOs choose Bloomberg Law
• Getting Started Experience one platform, one price, and continuous innovation
• Our Initiatives Empower the next generation of lawyers
• Careers Explore alternative law careers and join our team
• Press Releases See our latest news and product updates
• DEI Framework Raising the bar for law firms
• Request Pricing
• Legal Solutions

How to Conduct Legal Research

September 21, 2021

Conducting legal research can challenge even the most skilled law practitioners.

As laws evolve across jurisdictions, it can be a difficult to keep pace with every legal development. Equally daunting is the ability to track and glean insights into stakeholder strategies and legal responses. Without quick and easy access to the right tools, the legal research upon which case strategy hinges may face cost, personnel, and litigation outcome challenges.

Bloomberg Law’s artificial intelligence-driven tools drastically reduce the time to perform legal research. Whether you seek quick answers to legal research definitions, or general guidance on the legal research process, Bloomberg Law’s Core Litigation Skills Toolkit has you covered.

What is legal research?

Legal research is the process of uncovering and understanding all of the legal precedents, laws, regulations, and other legal authorities that apply in a case and inform an attorney’s course of action.

Legal research often involves case law research, which is the practice of identifying and interpreting the most relevant cases concerning the topic at issue. Legal research can also involve a deep dive into a judge’s past rulings or opposing counsel’s record of success.

Research is not a process that has a finite start and end, but remains ongoing throughout every phase of a legal matter. It is a cornerstone of a litigator’s skills.

[Learn how our integrated, time-saving litigation research tools allow litigators to streamline their work and get answers quickly.]

Where do I begin my legal research?

Beginning your legal research will look different for each assignment. At the outset, ensure that you understand your goal by asking questions and taking careful notes. Ask about background case information, logistical issues such as filing deadlines, the client/matter number, and billing instructions.

It’s also important to consider how your legal research will be used. Is the research to be used for a pending motion? If you are helping with a motion for summary judgment, for example, your goal is to find cases that are in the same procedural posture as yours and come out favorably for your side (i.e., if your client is the one filing the motion, try to find cases where a motion for summary judgment was granted, not denied). Keep in mind the burden of proof for different kinds of motions.

Finally, but no less important, assess the key facts of the case. Who are the relevant parties? Where is the jurisdiction? Who is the judge? Note all case details that come to mind.

What if I’m new to the practice area or specific legal issue?

While conducting legal research, it is easy to go down rabbit holes. Resist the urge to start by reviewing individual cases, which may prove irrelevant. Start instead with secondary sources, which often provide a prevailing statement of the law for a specific topic. These sources will save time and orient you to the area of the law and key issues.

Litigation Practical Guidance provides the essentials including step-by-step guidance, expert legal analysis, and a preview of next steps. Source citations are included in all Practical Guidance, and you can filter Points of Law, Smart Code®, and court opinions searches to get the jurisdiction-specific cases or statutes you need.

Searching across Points of Law will help to get your bearings on an issue before diving into reading the cases in full. Points of Law uses machine learning to identify key legal principles expressed in court opinions, which are easily searchable by keyword and jurisdiction. This tool helps you quickly find other cases that have expressed the same Point of Law, and directs you to related Points of Law that might be relevant to your research. It is automatically updated with the most recent opinions, saving you time and helping you quickly drill down to the relevant cases.

How do I respond to the opposing side’s brief?

Whether a brief is yours or that of the opposing party, Bloomberg Law’s Brief Analyzer is an essential component in the legal research process. It reduces the time spent analyzing a brief, identifying relevant authorities, and preparing a solid response.

To start, navigate to Brief Analyzer available from the Bloomberg Law homepage, within the Litigation Intelligence Center , or from Docket Key search results for briefs.

Simply upload the opposing side’s brief into the tool, and Brief Analyzer will generate a report of the cited authorities and arguments contained in the brief.

You can easily view a comparison with the brief and analysis side by side. It will also point you directly to relevant cases, Points of Law, and Practical Guidance to jump start your research.

[ How to Write a Legal Brief – Learn how to shorten the legal research cycle and give your legal brief a competitive advantage.]

How to optimize your search.

Crafting searches is a critical skill when it comes to legal research. Although many legal research platforms, including Bloomberg Law, offer natural language searching, terms and connectors (also called Boolean) searching is still a vital legal research skill and should be used when searching across court opinions, dockets, Points of Law, and other primary and secondary sources.

When you conduct a natural language search, the search engine applies algorithms to rank your results. Why a certain case is ranked as it is may not be obvious. This makes it harder to interpret whether the search is giving you everything you need. It is also harder to efficiently and effectively manipulate your search terms to zero in on the results you want. Using Boolean searching gives you better control over your search and greater confidence in your results.

The good news? Bloomberg Law does not charge by the search for court opinion searches. If your initial search was much too broad or much too narrow, you do not have to worry about immediately running a new and improved search.

Follow these tips when beginning a search to ensure that you do not miss relevant materials:

• Make sure you do not have typos in your search string.
• Search the appropriate source or section of the research platform. It is possible to search only within a practice area, jurisdiction, secondary resource, or other grouping of materials.
• Make sure you know which terms and connectors are utilized by the platform you are working on and what they mean – there is no uniform standard set of terms of connectors utilized by all platforms.
• Include in your search all possible terms the court might use, or alternate ways the court may address an issue. It is best to group the alternatives together within a parenthetical, connected by OR between each term.
• Consider including single and multiple character wildcards when relevant. Using a single character wildcard (an asterisk) and/or a multiple character wildcard (an exclamation point) helps you capture all word variations – even those you might not have envisioned.
• Try using a tool that helps you find additional relevant case law. When you find relevant authority, use BCITE on Bloomberg Law to find all other cases and/or sources that cite back to that case. When in BCITE, click on the Citing Documents tab, and search by keyword to narrow the results. Alternatively, you can use the court’s language or ruling to search Points of Law and find other cases that addressed the same issue or reached the same ruling.

[Bloomberg Law subscribers can access a complete checklist of search term best practices . Not a subscriber? Request a Demo .]

How can legal research help with drafting or strategy?

Before drafting a motion or brief, search for examples of what firm lawyers filed with the court in similar cases. You can likely find recent examples in your firm’s internal document system or search Bloomberg Law’s dockets. If possible, look for things filed before the same judge so you can get a quick check on rules/procedures to be followed (and by the same partner when possible so you can get an idea of their style preferences).

Careful docket search provides a wealth of information about relevant cases, jurisdictions, judges, and opposing counsel. On Bloomberg Law, type “Dockets Search” in the Go bar or find the dockets search box in the Litigation Intelligence Center .

If you do not know the specific docket number and/or court, use the docket search functionality Docket Key . Select from any of 20 categories, including motions, briefs, and orders, across all 94 federal district courts, to pinpoint the exact filing of choice.

Dockets can also help you access lots of information to guide your case strategy. For example, if you are considering filing a particular type of motion, such as a sanctions motion, you can use dockets to help determine how frequently your judge grants sanctions motions. You can also use dockets to see how similar cases before your judge proceeded through discovery.

If you are researching expert witnesses, you can use dockets to help determine if the expert has been recently excluded from a case, or whether their opinion has been limited. If so, this will help you determine whether the expert is a good fit for your case.

Dockets are a powerful research tool that allow you to search across filings to support your argument. Stay apprised of docket updates with the “Create Alert” option on Bloomberg Law.

Dive deeper into competitive research.

For even more competitive research insights, dive into Bloomberg Law’s Litigation Analytics – this is available in the Litigation tab on the homepage. Data here helps attorneys develop litigation strategy, predict possible outcomes, and better advise clients.

To start, under Litigation Analytics , leverage the Attorney tab to view case history and preview legal strategies the opposition may practice against you. Also, within Litigation Analytics, use the Court tab to get aggregate motion and appeal outcome rates across all federal courts, with the option to run comparisons across jurisdictions, and filter by company, law firm, and attorney.

Use the Judge tab to glean insights from cited opinions, and past and current decisions by motion and appeal outcomes. Also view litigation analytics in the right rail of court opinions.

Docket search can also offer intel on your opponent. Has your opponent filed similar lawsuits or made similar arguments before? How did those cases pan out? You can learn a lot about an opponent from past appearances in court.

How do I validate case law citations?

Checking the status of case law is essential in legal research. Rely on Bloomberg Law’s proprietary citator, BCITE. This time-saving tool lets you know if a case is still good law.

Under each court opinion, simply look to the right rail. There, you will see a thumbnail icon for “BCITE Analysis.” Click on the icon, and you will be provided quick links to direct history (opinions that affect or are affected by the outcome of the case at issue); case analysis (citing cases, with filter and search options), table of authorities, and citing documents.

How should I use technology to improve my legal research?

A significant benefit of digital research platforms and analytics is increased efficiency. Modern legal research technology helps attorneys sift through thousands of cases quickly and comprehensively. These products can also help aggregate or summarize data in a way that is more useful and make associations instantaneously.

For example, before litigation analytics were common, a partner may have asked a junior associate to find all summary judgment motions ruled on by a specific judge to determine how often that judge grants or denies them. The attorney could have done so by manually searching over PACER and/or by searching through court opinions, but that would take a long time. Now, Litigation Analytics can aggregate that data and provide an answer in seconds. Understanding that such products exist can be a game changer. Automating parts of the research process frees up time and effort for other activities that benefit the client and makes legal research and writing more efficient.

[Read our article: Six ways legal technology aids your litigation workflow .]

Tools like  Points of Law ,  dockets  and  Brief Analyzer  can also increase efficiency, especially when narrowing your research to confirm that you found everything on point. In the past, attorneys had to spend many hours (and lots of money) running multiple court opinion searches to ensure they did not miss a case on point. Now, there are tools that can dramatically speed up that process. For example, running a search over Points of Law can immediately direct you to other cases that discuss that same legal principle.

However, it’s important to remember that digital research and analytical tools should be seen as enhancing the legal research experience, not displacing the review, analysis, and judgment of an attorney. An attorney uses his or her knowledge of their client, the facts, the precedent, expert opinions, and his or her own experiences to predict the likely result in a given matter. Digital research products enhance this process by providing more data on a wider array of variables so that an attorney can take even more information into consideration.

[Get all your questions answered, request a Bloomberg Law demo , and more.]

Recommended for you

See bloomberg law in action.

From live events to in-depth reports, discover singular thought leadership from Bloomberg Law. Our network of expert analysts is always on the case – so you can make yours. Request a demo to see it for yourself.

Data in the Court

Judicial decision making.

In recent years, legal technology has swept the industry—in contracts, in due diligence, in patents, in legal research, and perhaps most successfully, in e-discovery. Given the proliferation of such tools across the legal profession, it should come as no surprise that they—and the technology underpinning them—are also entering courtrooms. For instance, many have written about the use of technology to aid in setting bail or recommending sentencing for convicted parties. Most recently, a whole cottage industry has formed around judge/judicial analytics. If “ Judges in the Lab ” attempted to get into the heads of judges by tracking document view patterns and other indicators as they decided a fictional case, judicial analytics attempts to use data culled from publicly available dockets to provide insight to clients on judges and court behavior to help determine litigation strategy. In the past decade, some large players, including Thomson Reuters and LexisNexis, as well as smaller legal tech startups like Gavelytics and Trellis, have stepped in to provide insights into judges, giving more robust and empirical sourcing into what was once mere anecdote. As these analytics increasingly become an industry standard, more law firms are finding it necessary to have judicial data on hand to inform strategy, while in-house teams are subscribing to them to inform how they select outside counsel for litigation. While there are important technical debates to be had around the technology underpinning these tools, this story focuses on how the tools that do exist are used in the marketplace.

In this article, we speak to Robert (Bob) Ambrogi, legal tech journalist and media lawyer, about why judicial analytics is a valuable tool for lawyers looking to compete in today’s profession. Then, we speak with two legal tech users—Wendy Butler Curtis, chief innovation officer at Orrick, and Kate Orr, senior innovation counsel at Orrick—about what role analytics play in the law firm space.

Judges as data points

In 2015, Bob Ambrogi wrote a column for his blog, LawSites , titled “ In Litigation and Legal Research, Judicial Analytics Is the New Black ,” predicting that judicial analytics would be the next big thing for the profession. Ambrogi, who has covered legal technology for decades, reported from the American Association of Law Libraries annual meeting, where three different organizations were showcasing their judicial analytics platforms: Lex Machina, Ravel Law, and ALM. In the years since, many more companies have launched to provide such services. Companies like Gavelytics and Trellis, which began with a focus on judges, have rapidly expanded their scope seeking to provide both more state judicial data as well as complementary data around the courtroom, such as expert witness analysis, opposing counsel research, and more. Established legal research players like LexisNexis, which acquired both Lex Machina and Ravel in the past few years, and Thomson Reuters’s Westlaw Edge have also launched tools focused on judges within their legal analytics suite (Context and Precedent Analytics, respectively). And many of the products have moved from simply including docket data—bare bones recorded court data such as the length of a trial, the counsel on record, the subject of the suit, and so forth—to more sophisticated content analysis. Thus, tools like Precedent and Context look at the language in court decisions, taking into account judicial citation patterns in an attempt to predict (or at least provide insight into) how a judge makes decisions. (For more on all the companies mentioned above, see Ambrogi’s podcast, LawNext , which includes interviews with the founders of Gavelytics, Trellis, and more.)

[Legal analytics are] expanding our understanding of what it means to conduct legal research. Bob Ambrogi

From that context, in talking to The Practice, Ambrogi says judicial analytics, broadly construed, has largely lived up to its early promise. Rather than dive into PACER or search through public state or county records—much of which may not be digitized or standard—the new tools save lawyers time and energy by providing a user-friendly interface that filters and visualizes information. By using these judicial analytics tools, Ambrogi says, lawyers can ask questions like: “Is a judge more or less likely to grant the motion for summary judgment?” and “How long does this judge usually take to decide a certain kind of a case?” And even, “What influences does that judge tend to rely on?” It’s up to the lawyer to interpret the data as they see fit—Ambrogi notes that judicial analytics cannot predict what the judge will do in any specific instance. But it may give you a suite of data points to help you try to make that judgment call. Given this, Ambrogi suggests, the profession has moved from questioning whether or not practitioners need such tools to asking, Is it malpractice not to use them if they’re available?

For Ambrogi, these platforms are game-changing because they’re “expanding our understanding of what it means to conduct legal research—that legal research is not just about cases and statutes; it’s about gaining insights into the judges and lawyers and parties involved in a matter and how we adapt those cases and statutes and our own strategies based on those insights that we’ve gained,” he says. In particular, he is fascinated by advances in content analytics—though notes there is work to do. Ambrogi says:

If you know that this judge, based on analysis of their past decisions, finds cases out of the Second Circuit to be really persuasive in deciding IP matters, then you know you’re going to focus your brief on cases decided by the Second Circuit. And if you have been able to see that this judge often tends to cite certain cases as the controlling precedent in a particular matter, then you’d be a fool not to make sure you cite those cases as the controlling precedent in your brief. If you do nothing but speak to the judge’s particular profile and propensities, these analytics can give you an edge, and in litigation, that’s significant.

What’s coming down the pipeline? Ambrogi would love to see more marriages between legal technology, citing what might happen if you were able to layer on a product like Casetext’s Compose, which creates a first draft of a brief, with litigation analytics so that your first draft  already caters to the court in which you’re arguing. But before we see any technological synergies, the data in each service probably has to improve. Studies done in 2019 and 2020 by law firm librarians compared federal litigation products , revealing stark differences between products due to the quality and quantity of their data. For instance, when asking a question like, “In how many [patent] cases has Irell & Manella appeared in front of Judge Richard Andrews in the District of Delaware [since January 1, 2007],” studies found that “no two vendors had the same answer.”

The tools might be a game-changer, but they also have much further to go to truly change the game.

According to the ABA Journal , the reason for such wild conclusions has to do with the underlying inconsistency of the data in each product. For instance, the platforms in question all drew from federal litigation data from PACER, which itself costs money—causing platforms to pick and choose what they buy within a budget—and the data within PACER itself is frequently flawed. Typos or erroneous nature of suit (NOS) codes abound, and omissions, like if counsel changed halfway through a case, may occur. As Ambrogi notes, platforms like Trellis and Gavelytics that are trying to account for even less systemized state data have even more work ahead of them.

What this means is that the tools might be a game-changer, but they also have much further to go to truly change the game. Normalizing and systemizing the data will take time and money. “They’re using AI to some extent to try to do that, help with that cleanup, but there still have to be humans involved, and where you need intensive work by humans, it’s a very expensive process,” says Ambrogi.

The user’s experience

As senior innovation counsel at Orrick, Kate Orr thinks carefully about how technology can complement and bolster the firm’s lawyers and the work that they do. About four years ago, Orrick integrated judicial analytics into CaseStream, their homegrown case management system. Every litigation matter flows through CaseStream, run by a case manager professional (typically not a lawyer) whose job is to connect the team with records, resources, and tools—including a suite of litigation and judicial analytics. “We feed the analytics to our lawyers and teams at the start of a case, or even before if they’re trying to decide which jurisdiction to file in, so they don’t have to remember to go find them,” Orr says. She continues:

When we serve up that platter of analytics, we say, ‘OK, you have a case in this court with this judge against this opposing counsel. Here are the analytics that are available to you from the resources that we have here at Orrick, and here’s a link where you can manipulate the analytics yourself.’ Because that’s an important part of using them. You can have the report, but there is often a lot more you can visualize with the analytics through filtering and sorting. That work requires someone familiar with the facts and law at issue in the case.

Wendy Butler Curtis, Orrick’s chief innovation officer, adds that it was critical to serve the data in an easy-to-use manner. She notes, “We’ve got tech fatigue, we’ve got platform fatigue, we’ve got login fatigue, so Kate’s model helps meet people where they are, emphasizing that the people and processes are as important as the data analytics that these tools are providing.”

While both Butler Curtis and Orr stress the importance of the data in helping to inform decision making, both also note that the analytics, as they exist, are imperfect. “It’s just one thing that we think about, but it is very rarely the determining factor,” says Butler Curtis. As case in point, she notes that if a lawyer knows that 70 percent of the time a single judge denied motions to dismiss—a data point that current tools can largely determine—that percentage does not capture the complexity or difficulty of the case or argument. The analytics succeed when providing informative or illustrative data, says Orr, such as “a snapshot of the judge and her history, the breakdown of the kinds of cases she works on, her propensity to dismiss cases, the time it takes to resolve cases, and typical outcomes.” But “they aren’t as strong on strategy.” There is some information one can glean, such as the cases that judge might typically rely on that may factor into the legal strategy, but it doesn’t tell the whole story. This gap in analysis reminds Orr of how a streaming service might not perfectly understand your choices. She says:

I turn on Netflix and I watch some terrible old movie for the sake of nostalgia because I watched it when I was 10 years old. I wasn’t watching the movie because I like that genre, and yet, the next time I turn on Netflix, it’s recommending other terrible old movies to me. There’s a layer of personalization missing there that reminds me of analytics and where they fall short. There’s some data there, but we’re still working on how we can actually use it and what value it brings.

Both attorneys also note that while some tools purport to be able to predict behavior using sophisticated content analysis of judicial decisions and opinions, there is room to improve when it comes to prediction. Nevertheless, Butler Curtis and Orr still view the tools as valuable—particularly for an unforeseen benefit: the analytics have become a tool in the firm’s commitment to well-being. When CaseStream delivers “analytics on a platter,” lawyers get data points of, for instance, court and even judge timings (for example, the data shows that this court/judge typically takes X days to rule on this type of matter). How does that impact issues of well-being? Lawyers gain a measure of predictability in an otherwise unpredictable practice area. Having this information allows the firm to both staff cases in sensible ways, including ensuring work is distributed equitably and efficiently, and give individual lawyers more control over how they allocate their time—including with respect to work/life integration. This may be particularly important given that litigation has traditionally been male-dominated .

Wendy Butler Curtis and Kate Orr of Orrick stress that having those data points allows the firm and its people to plan and adapt for the known chaos.

Butler Curtis recalls an instance where such legal analytics would have proved fruitful. A junior appellate lawyer joined the trial team just as they were starting trial. She relates:

I’ll never forget, he called me in a panic asking: ‘How are you going into the pretrial conference? We don’t have an answer on the jury charge.’ ‘How are you doing opening arguments? We don’t have a ruling on the motion on limine.’ Each step was a stressor for him. Imagine if he had access to analytics showing that in this court it was not uncommon for the judge to begin trial with pretrial motions still pending.

Again, Butler Curtis and Orr acknowledge that such analytics are imperfect. However, they stress that having those data points, particularly during stressful and often unpredictable litigation, allows the firm and its people to plan and adapt for the known chaos. As Orr says, they can help cut down on “exercises in futility,” helping lawyers ask more informed questions, such as, “Why are we filing this motion in limine if we know this court never rules on them?”

Both Butler Curtis and Orr admit that the idea that such analytics could help mitigate burnout is something they’re figuring out as they go. And, when Orrick first heard the sales pitch from their legal technology vendors, it was an advantage that wasn’t even on the horizon. Right now, judicial analytics adds the biggest value in providing that perspective on timing.

Choose your arbitrator

Like judicial analytics platforms, similar organizations are trying to categorize and make sense of international arbitration. Unlike with judges, companies who engage in arbitration often have the benefit of choosing their arbitrator. ArbiLex, a company started by Isabel Yang in the Harvard Innovation Lab while she was a Harvard Law School SJD student, uses artificial intelligence and predictive analytics to drive data-driven decision making in the legal profession. ArbiLex not only helps legal buyers choose their arbitrator on the basis of factors like standard time to resolution but quantifies risk factors for legal financers. As noted in a Forbes article about the founder , “The main benefit of ArbiLex’s product is mapping out risk factors associated with an arbitration case. The startup’s algorithms can help benchmark and quantify probabilities, which allows users to think more probabilistically when assessing settlement outcomes as opposed to maintaining a binary mindset.”

Catherine Rogers, who is both professor of law at Penn State Law and professor of ethics, regulation and the rule of law at Queen Mary University of London, provides a different view of arbitrators within the same horizon. Her nonprofit, Arbitrator Intelligence , “is an information aggregator that collects and analyzes information about arbitrators’ track records, which parties and counsel can use to better inform their arbitrator selection,” according to their website. Rather than use machine learning to rank and categorize arbitrators, Rogers asks users of arbitration to provide qualitative feedback about their experiences, while arbitrators can record video interviews to sell their services. To date, the organization has information about over 800 arbitrators from over 125 countries in its system.

Debating the issues

Usefulness aside, judicial analysis does not come without controversy. In 2019 France banned its use , citing privacy concerns and the possibility that such scrutiny could lead to undue pressure on decision making. Yet, judges, Ambrogi believes, should not fear analytics, which can help lawyers better tailor their briefs and strategically honor a judge’s knowledge and experience. “If I’m a judge who has a lot of experience in trademark law, I don’t want some lawyer trying to write a long thesis on trademark law, trying to educate me about something that I probably know better than that lawyer,” he says.

There are larger debates at play. As Butler Curtis notes, there is a “a fundamental ground-swelling resistance to the amount of data that’s out there about each of us and how it is used,” she says. Particular to this is the idea that “people are making decisions based on this increased data when it doesn’t necessarily tell the fair and full picture,” she indicates. (For more, see “ The Cost of Judgment .”)

These tools are expensive right now—because of what is needed to create them, they’ll continue to be expensive for a while. Bob Ambrogi

Butler Curtis also worries about the data in legal analytics, but not simply because of privacy or the quality or inconsistency. What’s accounted for does not paint the whole picture and could lead to an unfair distribution of credit: “While the tools are working to improve this, the primary source of data is who signed the pleading, not who wrote the motion or did the argument.”

For Ambrogi’s part, he notes that “these tools are expensive right now—because of what is needed to create them, they’ll continue to be expensive for a while.” He goes on, “And that does potentially create an uneven playing field, both for smaller-firm lawyers, who don’t have the budgets to be using these tools in the same way as their big-firm counterparts, and even more so for pro se litigants, putting them at an even greater disadvantage.”

At the same time, in their paper, “ Judging by Numbers: How Will Judicial Analytics Impact the Justice System and Its Stakeholders? ” University of Ottawa law professors Jena McGill and Amy Salyzyn predict that judicial analytics could become cheaper and more widely available over time. Such a possibility opens judges up to scrutiny in ways that might prove fruitful for weeding out bias or discrimination. McGill and Salyzyn see a future in which judicial analytics is open to not just law firms willing to pay for it but also public citizens hoping to analyze, understand, and hold accountable public servants. This, they write, would be in line with many countries, like Canada, where governments have pledged further transparency.

What is the problem that we can solve with this data? Wendy Butler Curtis

Other questions abound: Are legal analytics—and this type of curated assessment of judges—a natural evolution? What does it say about our judicial system? How should we think about decision making in the courtroom in general? For now, Ambrogi says, “in terms of practical impact on lawyers’ practices today, judicial analytics and broader litigation analytics are incredibly potent.”

Butler Curtis approaches it by asking: What is the problem that we can solve with this data? “Just when we think of all the ways that you would use it, you think of three more,” she says.

Related Content

The implications of chatgpt for legal services and society.

Law Firms in the ESG Game

Ethical Prompts

Knowledge Search

Search all of our knowledge, from The Practice to Insights to Academic Publications and Reports in one place.

Exploring Legal Data Analytics: Your Ultimate Guide (with use cases)

The new world of legal analytics now offers compelling and exciting ways to assist law firms achieve huge operational efficiency and improved outcomes for their clients, often just by making use of existing data sources.

According to research by Gartner in 2018, 70% of law firms state they intend to invest in legal data analytics, but in practice, only 20% are using it to drive efficiency and enable data-driven decisions.

At Bigle Legal, we are passionate about the exciting opportunities this technology can bring to legal teams of all types.

In this article, we will provide a compelling case for how your law firm can be transformed by leveraging legal analytics... in particular :

• What is meant by legal data analytics
• How legal analytics is already being used
• How your firm can quickly start to leverage its potential
• Its future in law, and;
• Why lawyers should invest time to become confident and acquainted with this new way of working

Ready to dive deeper?

Panning for gold: what is data analytics?

Before we look into the legal applications for data analytics, we need to understand what it is.

Firstly, it is important to understand that data analytics is not a specific technology or set of tools ; it is the process of turning raw data into useful insights. There are many ways to achieve this aim, with a wide array of technological solutions and methodologies. As such, data analytics is a science.

Data analysts or scientists work through a model of collecting data , processing and cleaning the data , performing exploratory analysis , applying models and algorithms , and then providing information on which decisions can be made (this is referred to as the intelligence cycle).

In doing so, the vast data put into the system is narrowed down at each stage until only the most important elements remain. Therefore, you can think of data analytics rather like panning for gold. The more you can put in, the more you glean as a result – but to do so requires careful planning, expertise, and vast computing power.

How is data analytics being used in legal practice?

Before we discuss the reasons why many firms are yet to make the leap, we will establish the potential use-cases.

Predictive analysis

Having the ability to predict the probability of winning a case , which judge will provide the most favourable decision, and drawing conclusions about opposing counsel and litigation parties offers a significant competitive advantage to law firms.

This is because rather than investing valuable time and people resources into cases which ultimately prove to be costly or unsuccessful, lawyers can decide whether to take a case on , and if they do, determine a strategy which has the chance of the most favourable outcome.

Where traditionally legal researchers may be tasked with making such assessments, this can be done rapidly and with little lawyer or paralegal overhead. Legal predictive analysis can also help provide accurate cost estimates for cases (based on all historical cases with similar aspects) and then enable law firms to offer fixed priced fees.

It is worth noting, however, that France has recently legislated to ban the use of data analytics to uncover the pattern of judge behaviour in relation to Court decisions. On the one hand, this may limit the potential use of this technology in some countries, but this also serves to illustrate how powerful such analytic methods can be.

Marketing analysis

Savvy legal marketing departments are now using data-driven marketing analytics to provide new insights into their client-base , r efine pricing models , and respond to requests for proposals (RFPs) .

For many law firms, the overhead of creating pitches and responding to proposal requests can be incredibly onerous. Indeed, capturing the data and information necessary to service such requests is considered to be one of the largest constraints placed on business development teams.

Data analytics can play a key role in automating much of the information gathering process, freeing staff up to complete their roles.

When it comes to targeting potential clients, by analysing data from customer social media behaviour, previous sales information, customer relationship management systems (CRM), web analytics, and email campaigns, law firms are starting to get a highly granular view of who their clients are, allowing them to refine and personalise their marketing approach .

By taking a more scientific approach, marketing teams can compare the results of different campaigns by undertaking A/B testing . This allows them to ask questions such as – which style of blog content do prospective clients prefer, which aspects of our most successful ads and landing pages cause clients to click for more information, and what is it about our emails that makes people engage our services.

This optimisation process can have a dramatic effect on the overall number of successful client engagements.

eDiscovery / legal document analysis

One of the most powerful uses for data analytics for law firms is the ability to make sense of vast amounts of documents to aid legal cases .

Electronic discovery (known as eDiscovery) is the process of identifying electronically stored information (ESI) which is pertinent to a legal case, then systematically preserving, collecting, processing, reviewing, and analysing, that information for production and presentation (this is referred to as the EDRM process ).

Traditionally, the discovery (or disclosure) process has been extremely costly and onerous , and this has become increasingly so as the number of emails, documents, videos, audio files, spreadsheets and other types of ESI balloon. This can even prevent law firms from taking on more complex legal cases.

eDiscovery solutions work by applying data analytics principles to automatically find patterns and themes. Then with the aid of predictive coding (or technology-assisted review), which allows lawyers to help train the software using a small subset of the documents, the system makes better decisions, further saving time and money.

Data analytics in the form of eDiscovery offers a perfect opportunity for law firms to drive massive efficiencies in their document review costs , freeing up staff for a higher value and more profitable work.

Options for implementing data analytics within a law firm

Many law firms will understandably be concerned that the cost and ramp-up time to implement legal analytics within their business may be prohibitive.

One way to greatly reduce the implementation time for such systems and processes is to outsource to specialist legal analytics solution providers , such as:

• Wavelength Law

Many solution providers can manage all aspects of your data analytics needs, including consulting expertise, IT design and implementation, project management, process analysts, training, and even undertaking data analysis on your behalf.

Law firms can also consider data analytics solutions with little or no in-house IT requirement. One such provider is Legalytics , which provides a legal analytics cloud-based solution which can be accessed regardless of location.

Such solutions allow law firms to gain from the latest data analytic technology, including :

• Microsoft Business Intelligence , Power BI , SQL Server , Dynamics , Azure , and HDInsight
• Amazon Web Services

Why lawyers should invest time in learning legal data analytics?

The benefits of legal data analytics are not solely for the law firm ; it is important to understand that by embracing and becoming highly competent in this emerging area, lawyers can :

• Free up vast amounts of time
• Concentrate on higher value tasks which provide greater work satisfaction
• Increase their chances of achieving a successful outcome for their clients, and;
• Make themselves more attractive to law firms by having a wider set of skills.

Lawyers of the future will not only be expected to study how technology applies to their profession, but employers will naturally expect a robust understanding.

The future of data analytics in law

We already see compelling signs of change within the legal industry in relation to technology .

For example, new roles are already emerging , such as:

• Legal data analysts
• Legal programmers (Harvard Law School even have a course entitled ‘Programming for Lawyers’)
• Legal project managers

So influential will data be in the practice of law, the term ‘data-driven lawyer’ is now widely used to refer to those whose practice is underpinned by data insights at all stages of the legal process.

In the coming few years, artificial intelligence, and in particular, machine learning, will add to the effectiveness of legal data analytics.

As global law firm, Linklaters , state, “AI-based tools enable more sophisticated data analytics that have the potential to complement and inform the advice that we provide to clients”.

What's next?

In 2019, we are only at the start of the evolution of legal data analytics; much more is to come. Not only will legal analytics enable law firms to compete and drive efficiencies, but it can also be used to improve the client experience by ensuring decisions are made which lead to the best possible outcome, reducing time to completion of a matter, and eliminating wasted steps in the legal process.

And if you are still to be convinced that your law firm, or you as an individual lawyer should invest in legal data analytics, consider that this will become the new normal in the next five years.

And when the ability to process vast amounts of data of all kinds in order to make decisions, gain insights, find patterns, and automate processes becomes both essential and normal, firms and individuals who have taken the opportunity to embrace legal technology will find they will remain competitive and thrive in the data-driven world.

Related posts

Best Books for Lawyers to read in 2023: Career & Personal Growth

Alternative Legal Service Provider on the rise: threat or opportunity?

Knowledge Management for lawyers: how to Maintain Continuous Learning

Data Analysis for Legal Scholarship

What is data analysis for legal scholarship / empirical legal scholarship, publications on empirical legal scholarship, organizations focused on empirical legal scholarship.

• Data Analysis Tools
• Where to Find Data and Statistics
• Where to Learn More

Reference Librarian

Contact a Biddle Librarian

Need some more personalized research assistance? Reach out to a Biddle Law Librarian! At this link to Biddle's Ask a Librarian Service , you can:

• Chat with a librarian (during regular business hours),
• Email a librarian (your question will be answered by a member of the reference staff), or
• Request an appointment for an individual research consultation with a librarian.

Key to Icons Used on This Page

Data analysis in legal scholarship is part of a broader trend in legal scholarship toward more empirical legal research. Empirical research is research based on facts, observation, or experiments (rather than on theories or opinions). Empirical legal research involves using methods and approaches to research questions from other disciplines - largely social science disciplines like political science, economics, sociology, psychology, etc - to answer questions related to the law. Many of these methods involve finding or generating data and then using a tool or set of tools to analyze and visualize that data in order to support an argument or claim.

This guide will give a brief introduction to some Data Analysis Tools , Where to Find Data and Statistics that could be utilized to answer questions related to the law, and Where to Learn More about these tools and methods.

Additionally, on this Home page you will find links to some publications focused on empirical legal scholarship, as well as some organizations and professional associations that focus on empirical legal research and supporting the scholars who do that work.

• Next: Data Analysis Tools >>
• Last Updated: Dec 8, 2023 10:28 AM
• URL: https://law.upenn.libguides.com/data

Library electronic resources outage May 29th and 30th

Between 9:00 PM EST on Saturday, May 29th and 9:00 PM EST on Sunday, May 30th users will not be able to access resources through the Law Library’s Catalog, the Law Library’s Database List, the Law Library’s Frequently Used Databases List, or the Law Library’s Research Guides. Users can still access databases that require an individual user account (ex. Westlaw, LexisNexis, and Bloomberg Law), or databases listed on the Main Library’s A-Z Database List.

• Georgetown Law Library
• Research Process

Statistics and Empirical Legal Studies Research Guide

• Data Analysis Tools
• Getting Started
• Research Design
• Data Collection
• Articles on Empirical Methodology in Law
• Selected Books on Empirical Legal Research Methodology
• Selected Books on Empirical Methodology in Other Disciplines
• Searching for Empirical Studies on a Particular Topic
• Research Data Archives and Specialized Search Engines
• Courts and the Judiciary
• Crime and Criminal Justice
• Demographics
• Economics, Finance and Trade
• Elections and Public Opinion
• Foreign and International Data
• Government Enforcement, Regulation, and Spending
• Health and Well-being

Commercial Data Analysis Packages

Free and open source statistical analysis tools, choosing between statistical tests, software guides, key to icons.

• Georgetown only
• On Bloomberg
• More Info (hover)
• Preeminent Treatise

• << Previous: Health and Well-being
• © Georgetown University Law Library. These guides may be used for educational purposes, as long as proper credit is given. These guides may not be sold. Any comments, suggestions, or requests to republish or adapt a guide should be submitted using the Research Guides Comments form . Proper credit includes the statement: Written by, or adapted from, Georgetown Law Library (current as of .....).
• Last Updated: Mar 22, 2024 12:04 PM
• URL: https://guides.ll.georgetown.edu/EmpiricalLegalStudies

How Data Science Could Reshape What We Know About the Law

Karolina Naranjo-Velasco's journey to the law and data science began with understanding war and how it deepens inequalities. 

Growing up in Santander, Colombia, she witnessed the social and economic effects of armed conflict on families, including her own, and saw how war impacted the most disadvantaged in her country.

During vacations at her family’s cattle ranch, she noticed that the rural population had endured multiple forms of violence and experienced social and economic exclusion. This exclusion, in turn, produced several waves of victimization, such as forced displacement and a lack of access to economic opportunities.

She wanted to help find solutions to these seemingly intractable problems, a passion that led her to pursue social justice as a personal and professional vocation. 

“That’s why I studied law — to defend people and make a difference,” she said. 

After years as an attorney, she realized interpreting data can affect people’s lives in tangible ways. Serving as a victim reparation and assistance director in her region, she was inspired to pursue an education in computational methods to explore how the legal community could benefit from the more effective use of automated systems, particularly in decision-making. 

This belief in data science as a pivotal tool in the legal field led her to the University of Virginia where she’s pursuing a doctoral degree in data science after earning a master’s degree in the field. 

Naranjo-Velasco’s life and mission are powerful illustrations of how data science and the law can intersect, leading to important insights about issues that have a profound impact on society, both inside and outside courtrooms. It’s work that’s being done not only by Naranjo-Velasco at the School of Data Science but across Grounds at the University’s Law School. 

Promoting justice through data science

From her days as a practicing attorney to her shift to data science, Naranjo-Velasco has seen how consequential, yet sometimes inscrutable, legal data can be.

The data contained in legal documents, such as court opinions, can have far-reaching impacts and can even trigger sweeping changes, she said. These documents are often hard for the public to understand because they use complex language. 

Despite their complexity, Naranjo-Velasco concluded that data science tools can facilitate their comprehension and make them more accessible. 

A concept known as “law-as-data” has served as the basis for statistical and computational approaches to handle the unique characteristics of legal documents, she said. In addition, the boom of large language models, or LLMs, can help fill this gap. 

“We can train those models, for example, for summarization of legal documents to enhance legal analysis,” said Naranjo-Velasco.

Naranjo-Velasco is continuing to build a new skill set while at UVA, from how to optimize the training method for artificial intelligence systems to better understanding how to use and evaluate algorithms. 

Looking ahead, she’s excited about the possibilities of using natural language processing, especially LLMs, to analyze legal decisions. She’s also encouraged by the possibilities offered by the rapidly evolving world of legal tech and computational legal studies, where new tools, such as chatbots, are being created to help ensure more people can receive answers on legal matters. 

There are many ways to be innovative in these areas, she said.

She is hopeful that artificial intelligence tools can make complex legal concepts more accessible. 

“An AI system that simplifies technical language and documents into easily readable and understandable legal text helps a lot. Knowing our rights can help us feel protected by the law,” she said. 

Quantifying judges

Like Naranjo-Velasco, researchers at UVA’s Law School are also embracing the use of data to better understand the law and judiciary.  

Li Zhang leads the Legal Data Lab at UVA’s Law School. Founded in 2016, it was one of the first data labs of its kind at a U.S. law school. 

Before pursuing his Ph.D. as a computational social scientist specializing in the intersection of human-computer interaction and political communication, Zhang had had a long academic interest in the history of science and technology.

Unlike some previous major scientific developments, with data science, Zhang said, “this time you can be in the thick of it and study the impact it is going to unleash on human society.”

He soon became passionate about applying his skills to teach, promote, and support data-driven scholarship — not only in classrooms but also at a university library. He was working as a social sciences and data librarian at Skidmore Collage when he saw an opening at UVA’s Legal Data Lab.

Even though he didn’t have a background in legal research, in 2023 he jumped at the chance to support the work of the faculty and students at one of the top law schools in the country. 

There is a “growing interest among students for empirical studies,” Zhang said. “And that often involves big data, harvesting, cleaning, and processing data in creative ways.”

Zhang has been involved with projects relating to judicial behavior, including an ongoing collaboration with the school’s Supreme Court Litigation Clinic, which wants to build a model that can predict the success of petitions for certiorari, the term used when the court agrees to hear a case.  

“It’s pretty challenging from the data gathering to the modeling,” Zhang said, explaining that because the court grants so few cert petitions relative to how many litigants seek review, the issue of class imbalance arises.

“I’m still experimenting with different techniques to augment the dataset,” he said.

Zhang also recently partnered with a law professor who, using data science methods, developed an innovative new way to measure the ideology of federal court judges . 

Kevin Cope , an associate professor of law at UVA, is both a practitioner and teacher of legal empirical analysis.  

Working with Zhang, he computed what he called Jurist-Derived Judicial Ideology Scores , which place nearly every Article III federal judge since 1990 on an ideological scale. The ratings are based on hundreds of thousands of pages of comments from experts such as lawyers or former law clerks describing the ideological bent of over 2,000 judges. 

“The idea is we can use the wisdom of experts to measure judges across courts, and even over time — that’s something that’s proved elusive thus far,” Cope said. 

That’s because judges across the country preside over such a wide variety of matters. “It’s a very difficult measurement problem to compare them with each other because we don’t have a frame of reference. They’re hearing completely different cases,” he said. 

Ultimately, the dataset Cope worked with consisted of 100 large books of hardcopy records, many of which had various notes that were difficult to interpret or missing pages.

“Trying to automate the system for quantifying this information proved extremely difficult,” he said. 

Zhang, though, was able to design a method for recovering and quantifying all of the problematic or missing pages. 

“Every project has really unique challenges, but I think this project truly was unique,” Cope said. 

Thus far, Cope has published his ideological scores for federal circuit judges. Soon, he’ll share his ideology scores on U.S. district court judges, as well as findings on other traits, including temperament and judging style — data that could offer untold new insights about the men and women who make decisions that have the potential to reshape American society.  

The future of data science and the law

So, where do data science and the study of law go from here? On Grounds, the future certainly appears promising. 

“UVA has a great tradition of quantitative analysis, of empirical legal studies on our faculty,” said Cope. 

“Increasingly, we have students who are interested in empirical work as well,” he added.

Cope is also hopeful that data analysis will continue to be emphasized by legal educators and in the profession. 

“As with many other professions, much of what lawyers do will be supplemented or supplanted by artificial intelligence in the coming years," he said. "To stay relevant, lawyers would be well-advised to become conversational in the languages of data analysis and machine learning, in order to either apply these technologies themselves or collaborate with legal data scientists. And to prepare modern lawyers, law schools will need to make those skills a bigger part of the curriculum.” 

Zhang also believes lawyers will rely more on data science.

“It’s just a matter of time before it becomes an integral part of their practices,” he said. 

As for Naranjo-Velasco, she plans to continue focusing on the intersection of the law and data science throughout her doctoral work at UVA and beyond, finding ways where her unique background can help her promote a more just society by enhancing AI tools for legal analysis. 

It’s a passion that is fueled by her past in Colombia and her discovery of the potential of data science to make a positive impact on society.

“Data science has the power to bring objectivity to law,” she said. “It also allows us to take many sources of information and put them together to understand the facts. That's why it's a valuable tool for both lawyers and data scientists". 

A Day to Inspire: Key Takeaways from WiDS 2024

Alum Uses Data Science to Make an Impact on City Government

Student Spotlight: Karolina Naranjo-Velasco Combines Data Science, Law, and Social Justice

Ph.D. Student Profile: Karolina Naranjo-Velasco

Get the latest news.

Subscribe to receive updates from the School of Data Science.

• Prospective Student
• School of Data Science Alumnus
• UVA Affiliate
• Industry Member

Legal Practice

Benefits of using data analysis for legal research

In today’s time, it’s not just about the practice of the law, it’s about striving as a business, whether you’re in a corporate sector or a law firm. To win cases, maintain your firm’s budget, and attract more cases, a lawyer must possess both legal understanding and business sense. If you only think about the law, then it’s high time you start thinking about the business also. 

Data analysis helps not only in commercial sectors but also in the legal sector. If you run a law firm, then you definitely need data analysis as you would not want to come out as a fool in front of your clients. Through data analysis, you can predict a certain case’s verdict, maintain your firm’s budget, tell how much time a particular case would take, and many other important things.

Hence, without wasting any more time, let’s take a look at what legal analysis is and how it is helpful for lawyers.

Read Also – Here is the Importance of Legal Research in Legal Practice

What is legal analysis? 

• Using factual work data to make decisions about respective cases or legal affairs—are one of the most rapid ways to construct a business case for a legal practice. They give a way to lawyers in any situation to earn a competitive benefit, both legally and in terms of business development.
• Legal analysis is the application of law to evidence.  There is a particular pattern to legal analysis.  This pattern is usually referred to as the IRAC method .

The key advantages of data analysis for legal research:

• The opportunities of winning a case could be greater as by analyzing the data of previous trials, valuable acumen could be derived regarding the crucial issues like time, judge’s decision and also specific things that might help the firm cultivate a smarter strategy to win a specific case.
• Cases frequently continue for a long duration before emerging as a loss. To save money and time wasted on a specific case, the legal analysis could assist lawyers to conclude whether to go on or to negotiate.
• Frequently, law firms need to employ external expertise to assist with their case, the decision being expensive must be supported by factual data. With legal analysis, it would be simpler to go through data considering a specific client and his conduct in synonymous cases in the past.
• There could be a crucial development in the field of operational capability. In the maximum situations, lawyers invest a huge amount of time in categorizing case papers and other data. This way they are wasting their time in finding previous information when they could be paying attention in offering consultation to a possible client and attaining another case thereby adding financial advantage to the firm. The task of data analysis should always be dealt with by the legal analytics system.
• At the end of the day a law firm is just a business, so, to guarantee that the business undertakings of the firm are being managed with effectiveness, a legal analysis system could be useful. Whether it’s cost management or hiring or maintaining old staff, important information could be gained, which could be directed to get in more profit.
• By picking data from your case management system, you can get an immediate “at a glance” judgment of your development on operations, business improvement, and particular matters. These illustrated dashboards and charts allow people to see how they are operating against timelines and funds so they can immediately know whether they’re on path or stumbling behind with project fulfillment, and billing. Where do you have blockages, and what help do you need to get rid of them?

Is your law firm taking full benefit of its data through analytics tools? If not, this is the time to commence. Your preliminary effort doesn’t have to be complex or costly; in fact, it’s reasonable to start little, gain some success, and grow into more complicated experiments over time. Look at the data you’re already compiling via your e-invoicing and case management systems and start inquiring about the issues. Use that data to produce a few thorough reports and adjust your work execution. As you analyze the results, formulate new questions, and discover the new data to answer those questions, your analytical strategy will be off and running.

Which software to choose for legal analysis?

You must be anxious to know the answer to this question, it’s Legodesk. It is the best upcoming legal management system with various features for lawyers and law firms. With Legodesk’s integrated platform , you can track down cases and case time with ease, track down information with a simple search option, connect safely with your team and clients, etc. Other than the legal analysis features, you also get features like e-billing, sending automatic email notifications, form template creation, and so much more. The best part is you get a 14-day free trial and you can cancel anytime you want. Now you won’t have to worry about any case or about the functionality of your firm as Legodesk is here to help you.

Try our Debt Resolution solutions today       Request a Demo

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Data Analysis in Research: Types & Methods

Content Index

Why analyze data in research?

Types of data in research, finding patterns in the qualitative data, methods used for data analysis in qualitative research, preparing data for analysis, methods used for data analysis in quantitative research, considerations in research data analysis, what is data analysis in research.

Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. 

Three essential things occur during the data analysis process — the first is data organization . Summarization and categorization together contribute to becoming the second known method used for data reduction. It helps find patterns and themes in the data for easy identification and linking. The third and last way is data analysis – researchers do it in both top-down and bottom-up fashion.

LEARN ABOUT: Research Process Steps

On the other hand, Marshall and Rossman describe data analysis as a messy, ambiguous, and time-consuming but creative and fascinating process through which a mass of collected data is brought to order, structure and meaning.

We can say that “the data analysis and data interpretation is a process representing the application of deductive and inductive logic to the research and data analysis.”

Researchers rely heavily on data as they have a story to tell or research problems to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data Mining’, which often reveals some interesting patterns within the data that are worth exploring.

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased toward unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research. 

Create a Free Account

Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.

• Qualitative data: When the data presented has words and descriptions, then we call it qualitative data . Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal qualitative interviews , qualitative observation or using open-ended questions in surveys.
• Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data . This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data.
• Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.

Learn More : Examples of Qualitative Data in Education

Data analysis in qualitative research

Data analysis and qualitative data research work a little differently from the numerical data as the quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting insight from such complicated information is a complicated process. Hence it is typically used for exploratory research and data analysis .

Although there are several ways to find patterns in the textual information, a word-based method is the most relied and widely used global technique for research and data analysis. Notably, the data analysis process in qualitative research is manual. Here the researchers usually read the available data and find repetitive or commonly used words. 

For example, while studying data collected from African countries to understand the most pressing issues people face, researchers might find  “food”  and  “hunger” are the most commonly used words and will highlight them for further analysis.

LEARN ABOUT: Level of Analysis

The keyword context is another widely used word-based technique. In this method, the researcher tries to understand the concept by analyzing the context in which the participants use a particular keyword.  

For example , researchers conducting research and data analysis for studying the concept of ‘diabetes’ amongst respondents might analyze the context of when and how the respondent has used or referred to the word ‘diabetes.’

The scrutiny-based technique is also one of the highly recommended  text analysis  methods used to identify a quality data pattern. Compare and contrast is the widely used method under this technique to differentiate how a specific text is similar or different from each other. 

For example: To find out the “importance of resident doctor in a company,” the collected data is divided into people who think it is necessary to hire a resident doctor and those who think it is unnecessary. Compare and contrast is the best method that can be used to analyze the polls having single-answer questions types .

Metaphors can be used to reduce the data pile and find patterns in it so that it becomes easier to connect data with theory.

Variable Partitioning is another technique used to split variables so that researchers can find more coherent descriptions and explanations from the enormous data.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

There are several techniques to analyze the data in qualitative research, but here are some commonly used methods,

• Content Analysis:  It is widely accepted and the most frequently employed technique for data analysis in research methodology. It can be used to analyze the documented information from text, images, and sometimes from the physical items. It depends on the research questions to predict when and where to use this method.
• Narrative Analysis: This method is used to analyze content gathered from various sources such as personal interviews, field observation, and  surveys . The majority of times, stories, or opinions shared by people are focused on finding answers to the research questions.
• Discourse Analysis:  Similar to narrative analysis, discourse analysis is used to analyze the interactions with people. Nevertheless, this particular method considers the social context under which or within which the communication between the researcher and respondent takes place. In addition to that, discourse analysis also focuses on the lifestyle and day-to-day environment while deriving any conclusion.
• Grounded Theory:  When you want to explain why a particular phenomenon happened, then using grounded theory for analyzing quality data is the best resort. Grounded theory is applied to study data about the host of similar cases occurring in different settings. When researchers are using this method, they might alter explanations or produce new ones until they arrive at some conclusion.

LEARN ABOUT: 12 Best Tools for Researchers

Data analysis in quantitative research

The first stage in research and data analysis is to make it for the analysis so that the nominal data can be converted into something meaningful. Data preparation consists of the below phases.

Phase I: Data Validation

Data validation is done to understand if the collected data sample is per the pre-set standards, or it is a biased data sample again divided into four different stages

• Fraud: To ensure an actual human being records each response to the survey or the questionnaire
• Screening: To make sure each participant or respondent is selected or chosen in compliance with the research criteria
• Procedure: To ensure ethical standards were maintained while collecting the data sample
• Completeness: To ensure that the respondent has answered all the questions in an online survey. Else, the interviewer had asked all the questions devised in the questionnaire.

Phase II: Data Editing

More often, an extensive research data sample comes loaded with errors. Respondents sometimes fill in some fields incorrectly or sometimes skip them accidentally. Data editing is a process wherein the researchers have to confirm that the provided data is free of such errors. They need to conduct necessary checks and outlier checks to edit the raw edit and make it ready for analysis.

Phase III: Data Coding

Out of all three, this is the most critical phase of data preparation associated with grouping and assigning values to the survey responses . If a survey is completed with a 1000 sample size, the researcher will create an age bracket to distinguish the respondents based on their age. Thus, it becomes easier to analyze small data buckets rather than deal with the massive data pile.

LEARN ABOUT: Steps in Qualitative Research

After the data is prepared for analysis, researchers are open to using different research and data analysis methods to derive meaningful insights. For sure, statistical analysis plans are the most favored to analyze numerical data. In statistical analysis, distinguishing between categorical data and numerical data is essential, as categorical data involves distinct categories or labels, while numerical data consists of measurable quantities. The method is again classified into two groups. First, ‘Descriptive Statistics’ used to describe data. Second, ‘Inferential statistics’ that helps in comparing the data .

Descriptive statistics

This method is used to describe the basic features of versatile types of data in research. It presents the data in such a meaningful way that pattern in the data starts making sense. Nevertheless, the descriptive analysis does not go beyond making conclusions. The conclusions are again based on the hypothesis researchers have formulated so far. Here are a few major types of descriptive analysis methods.

Measures of Frequency

• Count, Percent, Frequency
• It is used to denote home often a particular event occurs.
• Researchers use it when they want to showcase how often a response is given.

Measures of Central Tendency

• Mean, Median, Mode
• The method is widely used to demonstrate distribution by various points.
• Researchers use this method when they want to showcase the most commonly or averagely indicated response.

Measures of Dispersion or Variation

• Range, Variance, Standard deviation
• Here the field equals high/low points.
• Variance standard deviation = difference between the observed score and mean
• It is used to identify the spread of scores by stating intervals.
• Researchers use this method to showcase data spread out. It helps them identify the depth until which the data is spread out that it directly affects the mean.

Measures of Position

• Percentile ranks, Quartile ranks
• It relies on standardized scores helping researchers to identify the relationship between different scores.
• It is often used when researchers want to compare scores with the average count.

For quantitative research use of descriptive analysis often give absolute numbers, but the in-depth analysis is never sufficient to demonstrate the rationale behind those numbers. Nevertheless, it is necessary to think of the best method for research and data analysis suiting your survey questionnaire and what story researchers want to tell. For example, the mean is the best way to demonstrate the students’ average scores in schools. It is better to rely on the descriptive statistics when the researchers intend to keep the research or outcome limited to the provided  sample  without generalizing it. For example, when you want to compare average voting done in two different cities, differential statistics are enough.

Descriptive analysis is also called a ‘univariate analysis’ since it is commonly used to analyze a single variable.

Inferential statistics

Inferential statistics are used to make predictions about a larger population after research and data analysis of the representing population’s collected sample. For example, you can ask some odd 100 audiences at a movie theater if they like the movie they are watching. Researchers then use inferential statistics on the collected  sample  to reason that about 80-90% of people like the movie. 

Here are two significant areas of inferential statistics.

• Estimating parameters: It takes statistics from the sample research data and demonstrates something about the population parameter.
• Hypothesis test: I t’s about sampling research data to answer the survey research questions. For example, researchers might be interested to understand if the new shade of lipstick recently launched is good or not, or if the multivitamin capsules help children to perform better at games.

These are sophisticated analysis methods used to showcase the relationship between different variables instead of describing a single variable. It is often used when researchers want something beyond absolute numbers to understand the relationship between variables.

Here are some of the commonly used methods for data analysis in research.

• Correlation: When researchers are not conducting experimental research or quasi-experimental research wherein the researchers are interested to understand the relationship between two or more variables, they opt for correlational research methods.
• Cross-tabulation: Also called contingency tables,  cross-tabulation  is used to analyze the relationship between multiple variables.  Suppose provided data has age and gender categories presented in rows and columns. A two-dimensional cross-tabulation helps for seamless data analysis and research by showing the number of males and females in each age category.
• Regression analysis: For understanding the strong relationship between two variables, researchers do not look beyond the primary and commonly used regression analysis method, which is also a type of predictive analysis used. In this method, you have an essential factor called the dependent variable. You also have multiple independent variables in regression analysis. You undertake efforts to find out the impact of independent variables on the dependent variable. The values of both independent and dependent variables are assumed as being ascertained in an error-free random manner.
• Frequency tables: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
• Analysis of variance: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
• Researchers must have the necessary research skills to analyze and manipulation the data , Getting trained to demonstrate a high standard of research practice. Ideally, researchers must possess more than a basic understanding of the rationale of selecting one statistical method over the other to obtain better data insights.
• Usually, research and data analytics projects differ by scientific discipline; therefore, getting statistical advice at the beginning of analysis helps design a survey questionnaire, select data collection  methods, and choose samples.

LEARN ABOUT: Best Data Collection Tools

• The primary aim of data research and analysis is to derive ultimate insights that are unbiased. Any mistake in or keeping a biased mind to collect data, selecting an analysis method, or choosing  audience  sample il to draw a biased inference.
• Irrelevant to the sophistication used in research data and analysis is enough to rectify the poorly defined objective outcome measurements. It does not matter if the design is at fault or intentions are not clear, but lack of clarity might mislead readers, so avoid the practice.
• The motive behind data analysis in research is to present accurate and reliable data. As far as possible, avoid statistical errors, and find a way to deal with everyday challenges like outliers, missing data, data altering, data mining , or developing graphical representation.

LEARN MORE: Descriptive Research vs Correlational Research The sheer amount of data generated daily is frightening. Especially when data analysis has taken center stage. in 2018. In last year, the total data supply amounted to 2.8 trillion gigabytes. Hence, it is clear that the enterprises willing to survive in the hypercompetitive world must possess an excellent capability to analyze complex research data, derive actionable insights, and adapt to the new market needs.

LEARN ABOUT: Average Order Value

QuestionPro is an online survey platform that empowers organizations in data analysis and research and provides them a medium to collect data by creating appealing surveys.

MORE LIKE THIS

20 Best Website Optimization Tools to Improve Your Website

Mar 22, 2024

15 Best Digital Customer Experience Software of 2024

15 Best Product Experience Software of 2024

15 Best Customer Analytics Software of 2024 | QuestionPro

Mar 21, 2024

Other categories

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

• Search Menu
• Browse content in Arts and Humanities
• Browse content in Archaeology
• Anglo-Saxon and Medieval Archaeology
• Archaeological Methodology and Techniques
• Archaeology by Region
• Archaeology of Religion
• Archaeology of Trade and Exchange
• Biblical Archaeology
• Contemporary and Public Archaeology
• Environmental Archaeology
• Historical Archaeology
• History and Theory of Archaeology
• Industrial Archaeology
• Landscape Archaeology
• Mortuary Archaeology
• Prehistoric Archaeology
• Underwater Archaeology
• Urban Archaeology
• Zooarchaeology
• Browse content in Architecture
• Architectural Structure and Design
• History of Architecture
• Residential and Domestic Buildings
• Theory of Architecture
• Browse content in Art
• Art Subjects and Themes
• History of Art
• Industrial and Commercial Art
• Theory of Art
• Biographical Studies
• Byzantine Studies
• Browse content in Classical Studies
• Classical History
• Classical Philosophy
• Classical Mythology
• Classical Literature
• Classical Reception
• Classical Art and Architecture
• Classical Oratory and Rhetoric
• Greek and Roman Papyrology
• Greek and Roman Epigraphy
• Greek and Roman Law
• Greek and Roman Archaeology
• Late Antiquity
• Religion in the Ancient World
• Digital Humanities
• Browse content in History
• Colonialism and Imperialism
• Diplomatic History
• Environmental History
• Genealogy, Heraldry, Names, and Honours
• Genocide and Ethnic Cleansing
• Historical Geography
• History by Period
• History of Emotions
• History of Agriculture
• History of Education
• History of Gender and Sexuality
• Industrial History
• Intellectual History
• International History
• Labour History
• Legal and Constitutional History
• Local and Family History
• Maritime History
• Military History
• National Liberation and Post-Colonialism
• Oral History
• Political History
• Public History
• Regional and National History
• Revolutions and Rebellions
• Slavery and Abolition of Slavery
• Social and Cultural History
• Theory, Methods, and Historiography
• Urban History
• World History
• Browse content in Language Teaching and Learning
• Language Learning (Specific Skills)
• Language Teaching Theory and Methods
• Browse content in Linguistics
• Applied Linguistics
• Cognitive Linguistics
• Computational Linguistics
• Forensic Linguistics
• Grammar, Syntax and Morphology
• Historical and Diachronic Linguistics
• History of English
• Language Evolution
• Language Reference
• Language Acquisition
• Language Variation
• Language Families
• Lexicography
• Linguistic Anthropology
• Linguistic Theories
• Linguistic Typology
• Phonetics and Phonology
• Psycholinguistics
• Sociolinguistics
• Translation and Interpretation
• Writing Systems
• Browse content in Literature
• Bibliography
• Children's Literature Studies
• Literary Studies (Romanticism)
• Literary Studies (American)
• Literary Studies (Asian)
• Literary Studies (European)
• Literary Studies (Eco-criticism)
• Literary Studies (Modernism)
• Literary Studies - World
• Literary Studies (1500 to 1800)
• Literary Studies (19th Century)
• Literary Studies (20th Century onwards)
• Literary Studies (African American Literature)
• Literary Studies (British and Irish)
• Literary Studies (Early and Medieval)
• Literary Studies (Fiction, Novelists, and Prose Writers)
• Literary Studies (Gender Studies)
• Literary Studies (Graphic Novels)
• Literary Studies (History of the Book)
• Literary Studies (Plays and Playwrights)
• Literary Studies (Poetry and Poets)
• Literary Studies (Postcolonial Literature)
• Literary Studies (Queer Studies)
• Literary Studies (Science Fiction)
• Literary Studies (Travel Literature)
• Literary Studies (War Literature)
• Literary Studies (Women's Writing)
• Literary Theory and Cultural Studies
• Mythology and Folklore
• Shakespeare Studies and Criticism
• Browse content in Media Studies
• Browse content in Music
• Applied Music
• Dance and Music
• Ethics in Music
• Ethnomusicology
• Gender and Sexuality in Music
• Medicine and Music
• Music Cultures
• Music and Media
• Music and Religion
• Music and Culture
• Music Education and Pedagogy
• Music Theory and Analysis
• Musical Scores, Lyrics, and Libretti
• Musical Structures, Styles, and Techniques
• Musicology and Music History
• Performance Practice and Studies
• Race and Ethnicity in Music
• Sound Studies
• Browse content in Performing Arts
• Browse content in Philosophy
• Aesthetics and Philosophy of Art
• Epistemology
• Feminist Philosophy
• History of Western Philosophy
• Metaphysics
• Moral Philosophy
• Non-Western Philosophy
• Philosophy of Language
• Philosophy of Mind
• Philosophy of Perception
• Philosophy of Science
• Philosophy of Action
• Philosophy of Law
• Philosophy of Religion
• Philosophy of Mathematics and Logic
• Practical Ethics
• Social and Political Philosophy
• Browse content in Religion
• Biblical Studies
• Christianity
• East Asian Religions
• History of Religion
• Judaism and Jewish Studies
• Qumran Studies
• Religion and Education
• Religion and Health
• Religion and Politics
• Religion and Science
• Religion and Law
• Religion and Art, Literature, and Music
• Religious Studies
• Browse content in Society and Culture
• Cookery, Food, and Drink
• Cultural Studies
• Customs and Traditions
• Ethical Issues and Debates
• Hobbies, Games, Arts and Crafts
• Lifestyle, Home, and Garden
• Natural world, Country Life, and Pets
• Popular Beliefs and Controversial Knowledge
• Sports and Outdoor Recreation
• Technology and Society
• Travel and Holiday
• Visual Culture
• Browse content in Law
• Arbitration
• Browse content in Company and Commercial Law
• Commercial Law
• Company Law
• Browse content in Comparative Law
• Systems of Law
• Competition Law
• Browse content in Constitutional and Administrative Law
• Government Powers
• Judicial Review
• Local Government Law
• Military and Defence Law
• Parliamentary and Legislative Practice
• Construction Law
• Contract Law
• Browse content in Criminal Law
• Criminal Procedure
• Criminal Evidence Law
• Sentencing and Punishment
• Employment and Labour Law
• Environment and Energy Law
• Browse content in Financial Law
• Banking Law
• Insolvency Law
• History of Law
• Human Rights and Immigration
• Intellectual Property Law
• Browse content in International Law
• Private International Law and Conflict of Laws
• Public International Law
• IT and Communications Law
• Jurisprudence and Philosophy of Law
• Law and Politics
• Law and Society
• Browse content in Legal System and Practice
• Courts and Procedure
• Legal Skills and Practice
• Primary Sources of Law
• Regulation of Legal Profession
• Medical and Healthcare Law
• Browse content in Policing
• Criminal Investigation and Detection
• Police and Security Services
• Police Procedure and Law
• Police Regional Planning
• Browse content in Property Law
• Personal Property Law
• Study and Revision
• Terrorism and National Security Law
• Browse content in Trusts Law
• Wills and Probate or Succession
• Browse content in Medicine and Health
• Browse content in Allied Health Professions
• Arts Therapies
• Clinical Science
• Dietetics and Nutrition
• Occupational Therapy
• Operating Department Practice
• Physiotherapy
• Radiography
• Speech and Language Therapy
• Browse content in Anaesthetics
• General Anaesthesia
• Neuroanaesthesia
• Clinical Neuroscience
• Browse content in Clinical Medicine
• Acute Medicine
• Cardiovascular Medicine
• Clinical Genetics
• Clinical Pharmacology and Therapeutics
• Dermatology
• Endocrinology and Diabetes
• Gastroenterology
• Genito-urinary Medicine
• Geriatric Medicine
• Infectious Diseases
• Medical Toxicology
• Medical Oncology
• Pain Medicine
• Palliative Medicine
• Rehabilitation Medicine
• Respiratory Medicine and Pulmonology
• Rheumatology
• Sleep Medicine
• Sports and Exercise Medicine
• Community Medical Services
• Critical Care
• Emergency Medicine
• Forensic Medicine
• Haematology
• History of Medicine
• Browse content in Medical Skills
• Clinical Skills
• Communication Skills
• Nursing Skills
• Surgical Skills
• Browse content in Medical Dentistry
• Oral and Maxillofacial Surgery
• Paediatric Dentistry
• Restorative Dentistry and Orthodontics
• Surgical Dentistry
• Medical Ethics
• Medical Statistics and Methodology
• Browse content in Neurology
• Clinical Neurophysiology
• Neuropathology
• Nursing Studies
• Browse content in Obstetrics and Gynaecology
• Gynaecology
• Occupational Medicine
• Ophthalmology
• Otolaryngology (ENT)
• Browse content in Paediatrics
• Neonatology
• Browse content in Pathology
• Chemical Pathology
• Clinical Cytogenetics and Molecular Genetics
• Histopathology
• Medical Microbiology and Virology
• Patient Education and Information
• Browse content in Pharmacology
• Psychopharmacology
• Browse content in Popular Health
• Caring for Others
• Complementary and Alternative Medicine
• Self-help and Personal Development
• Browse content in Preclinical Medicine
• Cell Biology
• Molecular Biology and Genetics
• Reproduction, Growth and Development
• Primary Care
• Professional Development in Medicine
• Browse content in Psychiatry
• Addiction Medicine
• Child and Adolescent Psychiatry
• Forensic Psychiatry
• Learning Disabilities
• Old Age Psychiatry
• Psychotherapy
• Browse content in Public Health and Epidemiology
• Epidemiology
• Public Health
• Browse content in Radiology
• Clinical Radiology
• Interventional Radiology
• Nuclear Medicine
• Radiation Oncology
• Reproductive Medicine
• Browse content in Surgery
• Cardiothoracic Surgery
• Gastro-intestinal and Colorectal Surgery
• General Surgery
• Neurosurgery
• Paediatric Surgery
• Peri-operative Care
• Plastic and Reconstructive Surgery
• Surgical Oncology
• Transplant Surgery
• Trauma and Orthopaedic Surgery
• Vascular Surgery
• Browse content in Science and Mathematics
• Browse content in Biological Sciences
• Aquatic Biology
• Biochemistry
• Bioinformatics and Computational Biology
• Developmental Biology
• Ecology and Conservation
• Evolutionary Biology
• Genetics and Genomics
• Microbiology
• Molecular and Cell Biology
• Natural History
• Plant Sciences and Forestry
• Research Methods in Life Sciences
• Structural Biology
• Systems Biology
• Zoology and Animal Sciences
• Browse content in Chemistry
• Analytical Chemistry
• Computational Chemistry
• Crystallography
• Environmental Chemistry
• Industrial Chemistry
• Inorganic Chemistry
• Materials Chemistry
• Medicinal Chemistry
• Mineralogy and Gems
• Organic Chemistry
• Physical Chemistry
• Polymer Chemistry
• Study and Communication Skills in Chemistry
• Theoretical Chemistry
• Browse content in Computer Science
• Artificial Intelligence
• Computer Architecture and Logic Design
• Game Studies
• Human-Computer Interaction
• Mathematical Theory of Computation
• Programming Languages
• Software Engineering
• Systems Analysis and Design
• Virtual Reality
• Browse content in Computing
• Business Applications
• Computer Security
• Computer Games
• Computer Networking and Communications
• Digital Lifestyle
• Graphical and Digital Media Applications
• Operating Systems
• Browse content in Earth Sciences and Geography
• Atmospheric Sciences
• Environmental Geography
• Geology and the Lithosphere
• Maps and Map-making
• Meteorology and Climatology
• Oceanography and Hydrology
• Palaeontology
• Physical Geography and Topography
• Regional Geography
• Soil Science
• Urban Geography
• Browse content in Engineering and Technology
• Agriculture and Farming
• Biological Engineering
• Civil Engineering, Surveying, and Building
• Electronics and Communications Engineering
• Energy Technology
• Engineering (General)
• Environmental Science, Engineering, and Technology
• History of Engineering and Technology
• Mechanical Engineering and Materials
• Technology of Industrial Chemistry
• Transport Technology and Trades
• Browse content in Environmental Science
• Applied Ecology (Environmental Science)
• Conservation of the Environment (Environmental Science)
• Environmental Sustainability
• Environmentalist Thought and Ideology (Environmental Science)
• Management of Land and Natural Resources (Environmental Science)
• Natural Disasters (Environmental Science)
• Nuclear Issues (Environmental Science)
• Pollution and Threats to the Environment (Environmental Science)
• Social Impact of Environmental Issues (Environmental Science)
• History of Science and Technology
• Browse content in Materials Science
• Ceramics and Glasses
• Composite Materials
• Metals, Alloying, and Corrosion
• Nanotechnology
• Browse content in Mathematics
• Applied Mathematics
• Biomathematics and Statistics
• History of Mathematics
• Mathematical Education
• Mathematical Finance
• Mathematical Analysis
• Numerical and Computational Mathematics
• Probability and Statistics
• Pure Mathematics
• Browse content in Neuroscience
• Cognition and Behavioural Neuroscience
• Development of the Nervous System
• Disorders of the Nervous System
• History of Neuroscience
• Invertebrate Neurobiology
• Molecular and Cellular Systems
• Neuroendocrinology and Autonomic Nervous System
• Neuroscientific Techniques
• Sensory and Motor Systems
• Browse content in Physics
• Astronomy and Astrophysics
• Atomic, Molecular, and Optical Physics
• Biological and Medical Physics
• Classical Mechanics
• Computational Physics
• Condensed Matter Physics
• Electromagnetism, Optics, and Acoustics
• History of Physics
• Mathematical and Statistical Physics
• Measurement Science
• Nuclear Physics
• Particles and Fields
• Plasma Physics
• Quantum Physics
• Relativity and Gravitation
• Semiconductor and Mesoscopic Physics
• Browse content in Psychology
• Affective Sciences
• Clinical Psychology
• Cognitive Psychology
• Cognitive Neuroscience
• Criminal and Forensic Psychology
• Developmental Psychology
• Educational Psychology
• Evolutionary Psychology
• Health Psychology
• History and Systems in Psychology
• Music Psychology
• Neuropsychology
• Organizational Psychology
• Psychological Assessment and Testing
• Psychology of Human-Technology Interaction
• Psychology Professional Development and Training
• Research Methods in Psychology
• Social Psychology
• Browse content in Social Sciences
• Browse content in Anthropology
• Anthropology of Religion
• Human Evolution
• Medical Anthropology
• Physical Anthropology
• Regional Anthropology
• Social and Cultural Anthropology
• Theory and Practice of Anthropology
• Browse content in Business and Management
• Business Ethics
• Business Strategy
• Business History
• Business and Technology
• Business and Government
• Business and the Environment
• Comparative Management
• Corporate Governance
• Corporate Social Responsibility
• Entrepreneurship
• Health Management
• Human Resource Management
• Industrial and Employment Relations
• Industry Studies
• Information and Communication Technologies
• International Business
• Knowledge Management
• Management and Management Techniques
• Operations Management
• Organizational Theory and Behaviour
• Pensions and Pension Management
• Public and Nonprofit Management
• Strategic Management
• Supply Chain Management
• Browse content in Criminology and Criminal Justice
• Criminal Justice
• Criminology
• Forms of Crime
• International and Comparative Criminology
• Youth Violence and Juvenile Justice
• Development Studies
• Browse content in Economics
• Agricultural, Environmental, and Natural Resource Economics
• Asian Economics
• Behavioural Finance
• Behavioural Economics and Neuroeconomics
• Econometrics and Mathematical Economics
• Economic History
• Economic Systems
• Economic Methodology
• Economic Development and Growth
• Financial Markets
• Financial Institutions and Services
• General Economics and Teaching
• Health, Education, and Welfare
• History of Economic Thought
• International Economics
• Labour and Demographic Economics
• Law and Economics
• Macroeconomics and Monetary Economics
• Microeconomics
• Public Economics
• Urban, Rural, and Regional Economics
• Welfare Economics
• Browse content in Education
• Adult Education and Continuous Learning
• Care and Counselling of Students
• Early Childhood and Elementary Education
• Educational Equipment and Technology
• Educational Strategies and Policy
• Higher and Further Education
• Organization and Management of Education
• Philosophy and Theory of Education
• Schools Studies
• Secondary Education
• Teaching of a Specific Subject
• Teaching of Specific Groups and Special Educational Needs
• Teaching Skills and Techniques
• Browse content in Environment
• Applied Ecology (Social Science)
• Climate Change
• Conservation of the Environment (Social Science)
• Environmentalist Thought and Ideology (Social Science)
• Natural Disasters (Environment)
• Social Impact of Environmental Issues (Social Science)
• Browse content in Human Geography
• Cultural Geography
• Economic Geography
• Political Geography
• Browse content in Interdisciplinary Studies
• Communication Studies
• Museums, Libraries, and Information Sciences
• Browse content in Politics
• African Politics
• Asian Politics
• Chinese Politics
• Comparative Politics
• Conflict Politics
• Elections and Electoral Studies
• Environmental Politics
• European Union
• Foreign Policy
• Gender and Politics
• Human Rights and Politics
• Indian Politics
• International Relations
• International Organization (Politics)
• International Political Economy
• Irish Politics
• Latin American Politics
• Middle Eastern Politics
• Political Behaviour
• Political Economy
• Political Institutions
• Political Methodology
• Political Communication
• Political Philosophy
• Political Sociology
• Political Theory
• Politics and Law
• Public Policy
• Public Administration
• Quantitative Political Methodology
• Regional Political Studies
• Russian Politics
• Security Studies
• State and Local Government
• UK Politics
• US Politics
• Browse content in Regional and Area Studies
• African Studies
• Asian Studies
• East Asian Studies
• Japanese Studies
• Latin American Studies
• Middle Eastern Studies
• Native American Studies
• Scottish Studies
• Browse content in Research and Information
• Research Methods
• Browse content in Social Work
• Addictions and Substance Misuse
• Adoption and Fostering
• Care of the Elderly
• Child and Adolescent Social Work
• Couple and Family Social Work
• Developmental and Physical Disabilities Social Work
• Direct Practice and Clinical Social Work
• Emergency Services
• Human Behaviour and the Social Environment
• International and Global Issues in Social Work
• Mental and Behavioural Health
• Social Justice and Human Rights
• Social Policy and Advocacy
• Social Work and Crime and Justice
• Social Work Macro Practice
• Social Work Practice Settings
• Social Work Research and Evidence-based Practice
• Welfare and Benefit Systems
• Browse content in Sociology
• Childhood Studies
• Community Development
• Comparative and Historical Sociology
• Economic Sociology
• Gender and Sexuality
• Gerontology and Ageing
• Health, Illness, and Medicine
• Marriage and the Family
• Migration Studies
• Occupations, Professions, and Work
• Organizations
• Population and Demography
• Race and Ethnicity
• Social Theory
• Social Movements and Social Change
• Social Research and Statistics
• Social Stratification, Inequality, and Mobility
• Sociology of Religion
• Sociology of Education
• Sport and Leisure
• Urban and Rural Studies
• Browse content in Warfare and Defence
• Defence Strategy, Planning, and Research
• Land Forces and Warfare
• Military Administration
• Military Life and Institutions
• Naval Forces and Warfare
• Other Warfare and Defence Issues
• Peace Studies and Conflict Resolution
• Weapons and Equipment

• < Previous chapter
• Next chapter >

12 Qualitative Legal Research: A Methodological Discourse

• Published: January 2020
• Cite Icon Cite
• Permissions Icon Permissions

Qualitative legal research aims to study things in their natural settings, understand and interpret their social realities and provide inputs on various aspects of social life. It focuses on people’s feelings, perceptions, and experiences. It differs from quantitative research in matters of nature of data, theoretical basis, and kinds of tools employed for data collection. The combination of two methods brings synergy. Worthy features of qualitative legal research consist of description of social setting, interpretation of social data, verification of assumptions, and evaluation of policies. Its steps include framing of specific questions, choice of data collection tools, sampling, data collection, analysis, and interpretation. This method allows for a mature understanding of the problematic world.

Signed in as

Institutional accounts.

• Google Scholar Indexing
• GoogleCrawler [DO NOT DELETE]

Personal account

• Sign in with email/username & password
• Get email alerts
• Save searches
• Purchase content
• Activate your purchase/trial code

Institutional access

• Sign in with a library card Sign in with username/password Recommend to your librarian
• Institutional account management
• Get help with access

Access to content on Oxford Academic is often provided through institutional subscriptions and purchases. If you are a member of an institution with an active account, you may be able to access content in one of the following ways:

IP based access

Typically, access is provided across an institutional network to a range of IP addresses. This authentication occurs automatically, and it is not possible to sign out of an IP authenticated account.

Sign in through your institution

Choose this option to get remote access when outside your institution. Shibboleth/Open Athens technology is used to provide single sign-on between your institution’s website and Oxford Academic.

• Click Sign in through your institution.
• Select your institution from the list provided, which will take you to your institution's website to sign in.
• When on the institution site, please use the credentials provided by your institution. Do not use an Oxford Academic personal account.
• Following successful sign in, you will be returned to Oxford Academic.

If your institution is not listed or you cannot sign in to your institution’s website, please contact your librarian or administrator.

Sign in with a library card

Enter your library card number to sign in. If you cannot sign in, please contact your librarian.

Society Members

Society member access to a journal is achieved in one of the following ways:

Sign in through society site

Many societies offer single sign-on between the society website and Oxford Academic. If you see ‘Sign in through society site’ in the sign in pane within a journal:

• Click Sign in through society site.
• When on the society site, please use the credentials provided by that society. Do not use an Oxford Academic personal account.

If you do not have a society account or have forgotten your username or password, please contact your society.

Sign in using a personal account

Some societies use Oxford Academic personal accounts to provide access to their members. See below.

A personal account can be used to get email alerts, save searches, purchase content, and activate subscriptions.

Some societies use Oxford Academic personal accounts to provide access to their members.

Viewing your signed in accounts

Click the account icon in the top right to:

• View your signed in personal account and access account management features.
• View the institutional accounts that are providing access.

Signed in but can't access content

Oxford Academic is home to a wide variety of products. The institutional subscription may not cover the content that you are trying to access. If you believe you should have access to that content, please contact your librarian.

For librarians and administrators, your personal account also provides access to institutional account management. Here you will find options to view and activate subscriptions, manage institutional settings and access options, access usage statistics, and more.

Our books are available by subscription or purchase to libraries and institutions.

• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Rights and permissions
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

• High contrast
• Our mandate
• Our history
• Annual report
• PRESS CENTRE

Search UNICEF

For every child, answers

Research and foresight that drive change for children

Latest work

Youth, Protests and the Polycrisis

Exploring how youth protests can help to build public support for change

Early Childhood Education Systems in Pacific Islands

Status report

Cash Plus Model for Safe Transitions to Healthy Adulthood

Examining the impacts of “Ujana Salama” (‘Safe Youth’ in Swahili), a cash plus programme targeting adolescents in the United Republic of Tanzania

The Impact of Valor Criança

Social cash transfer pilot programme in Angola

The Impact of the Cash Transfer Intervention

In the commune of Nsélé in Kinshasa, Democratic Republic of the Congo

Mitigating the socioeconomic impacts of COVID-19

With a cash transfer in peri-urban Kinshasa, Democratic Republic of the Congo

Prospects for Children: A Global Outlook 2024

Cooperation in a Fragmented World: Discover the eight trends that will define the year ahead for children and young people.

Data Must Speak: Chad

Reports and project briefs

Areas of work

Adolescent participation and civic engagement

Child protection

Climate crisis and the environment

Digital technology

Education and human capital

Health and well-being

Inclusion and equity

Poverty and social protection

Social and behaviour change

The State of the World’s Children

UNICEF’s flagship report – the most comprehensive analysis of global trends affecting children

Changing Childhood Project

What is childhood like today?

Prospects for Children: Global Outlook

An annual analysis of trends shaping the world and their impact on children

Report Card

Understanding child well-being everywhere

Our approach

UNICEF Innocenti works for and with children and young people to seek solutions to their most pressing challenges. As we focus on the rights and lives of children and young people, we always ask: Who else can we include? Will this work cause unintended harm? Are there events that could surprise us? Does this work drive change?

Events and insights

The Antidote to Ageism

Understanding the importance of intergenerational collaboration

Celebrating women in education

A closer look at female teachers and school leaders

As they move

Child and youth experiences of migration, displacement and return in Afghanistan

Parenting programmes can reduce violence against children

UNICEF, Prevention Collaborative and Equimundo launch three new evidence briefs

Launch of UNICEF's Youth Foresight Playbook

28 November 2023, Dubai Future Forum

Expert consultation on age-related public expenditure

12-13 April 2023

The Third Annual KIX Symposium

12-13 October 2022

UNICEF at the International SBCC Summit 2022

5-9 December 2022

Become an Innocenti Insider

Receive the latest research and event invites in your inbox once a month

Imaging and Analysis Core (Mayo Clinic Pirnie Translational Polycystic Kidney Disease Center)

Protocol development and study design.

The Imaging and Analysis Core can assist with developing protocols and standard operating procedures for image acquisition and image analysis.

Image acquisition protocols include:

• Minimum imaging requirements.
• Imaging acquisition parameters and subject positioning.
• Image submission requirements.

The core's standard operating procedures are step-by-step instructions for routine image analysis operations that are customized for each project.

We also offer research study design services for image acquisition and image analysis. For internal and external studies, we help with the collection, storage and analysis of anonymized imaging data used in translational PKD research and provide customized reporting for different imaging biomarkers.

Internal studies workflow

The laboratory requesting image analysis services is responsible for collecting, de-identifying and formatting the radiology images. Our team then processes the images using automated algorithms.

The outputs of these algorithms undergo a quality-review process usually performed by the requesting laboratory. Finally, we calculate the parameters of interest and send them to the requesting laboratory as a report.

For first-time users, we provide training, standard operating procedure materials, and software to perform the image retrieval, formatting and quality-control assessment.

External studies workflow

External studies can include one or multiple participant sites. Each site is responsible for image de-identification.

The images then undergo a quality-control process before they are sent for image analysis. We then generate the project-specific automated segmentations and perform the quality assessment and quantification of imaging biomarkers. Finally, we send a report with the calculated biomarkers to the external research organization.

Data collection

The Imaging and Analysis Core has an information system infrastructure that enables the transfer, storage, organization and management of PKD-related images. This open, easily accessible database allows participating investigators to correlate imaging data and results with a variety of genetic, pharmaceutical and clinical parameters.

Email us for more information about protocol development and study design services offered through the Imaging and Analysis Core.

More about research at Mayo Clinic

• Research Faculty
• Laboratories
• Core Facilities
• Centers & Programs
• Departments & Divisions
• Clinical Trials
• Institutional Review Board
• Postdoctoral Fellowships
• Training Grant Programs
• Publications

Mayo Clinic Footer

• Request Appointment
• About Mayo Clinic
• About This Site

Legal Conditions and Terms

• Terms and Conditions
• Privacy Policy
• Notice of Privacy Practices
• Notice of Nondiscrimination
• Manage Cookies

Advertising

Mayo Clinic is a nonprofit organization and proceeds from Web advertising help support our mission. Mayo Clinic does not endorse any of the third party products and services advertised.

• Advertising and sponsorship policy
• Advertising and sponsorship opportunities

Reprint Permissions

A single copy of these materials may be reprinted for noncommercial personal use only. "Mayo," "Mayo Clinic," "MayoClinic.org," "Mayo Clinic Healthy Living," and the triple-shield Mayo Clinic logo are trademarks of Mayo Foundation for Medical Education and Research.