Manzoli on Legal Taxonomies and Legal Folksonomies

Serena Manzoli, LL.M., has published Taxonomies Make the Law. Will Folksonomies Change It?, at VoxPopuLII.

Here are excerpts from the post:

[...] the problems with legal taxonomies occur when the creators and the users don’t share the same frame of mind. And this is most likely to happen when the creators of the taxonomy are lawyers and the users are not lawyers. [...]

Let’s come to folksonomies now. Here, the mismatch between creators (lawyers) and users’ way of reasoning is less likely to occur. The very same users decide which category to create and what to put into it. Moreover, more tags can overlap; that is, the same object can be tagged more than once. This allows the user to consider the same object from different perspectives. [...]‘

What legal folksonomies bring us is:

• User-centered categories
• Flexible categorization systems. Many items can be tagged more than once and so be put into different categories. Legal stuff can be retrieved through different routes but also considered under different lights.

Will this enhance findability? I think it will, especially if the users are non-lawyers. And services that target the low-end of the legal market usually target non-lawyers. [...]

Prediction #1: Folksonomies will provide the right information architecture for non-legal users. [...]

Prediction #2: legal folksonomies in legal teaching would keep lawyers’ minds flexible. [...]

Prediction #3 Legal folksonomies will make the law apply differently.

Let’s wait and see. Let the users tag. Where this tagging is going to take us is unpredictable, yes, but if you look at where taxonomies have taken us for all these years, you may find a clue.

I have a gut feeling that folksonomies are going to change the way we search, teach, and apply the law.

For more details, please see the complete post.

HT @squarelaw

Lu and Conrad on Bringing Order to Legal Documents: An Issue-based Recommendation System via Cluster Association

Qiang Lu and Jack G. Conrad, both of Thomson Reuters, will present a paper entitled Bringing Order to Legal Documents: An Issue-based Recommendation System via Cluster Association, at KEOD 2012: The 4th International Conference on Knowledge Engineering and Ontology Development, to be held 4-7 October 2012 in Barcelona, Catalonia, Spain.

Here is the abstract:

The task of recommending content to professionals (such as attorneys or brokers) differs greatly from the task of recommending news to casual readers. A casual reader may be satisfied with a couple of good recommendations, whereas an attorney will demand precise and comprehensive recommendations from various content sources when conducting legal research. Legal documents are intrinsically complex and multi-topical, contain carefully crafted, professional, domain-specific language, and possess a broad and unevenly distributed coverage of issues. Consequently, a high quality content recommendation system for legal documents requires the ability to detect significant topics from a document and recommend high quality content accordingly. Moreover, a litigation attorney preparing for a case needs to be thoroughly familiar the principal arguments associated with various supporting opinions, but also with the secondary and tertiary arguments as well. This paper introduces an issue-based content recommendation system with a built-in topic detection/segmentation algorithm for the legal domain. The system leverages existing legal document metadata such as topical classifications, document citations, and click stream data from user behavior databases, to produce an accurate topic detection algorithm. It then links each individual topic to a comprehensive pre-defined topic (cluster) repository via an association process. A cluster labeling algorithm is designed and applied to provide a precise, meaningful label for each of the clusters in the repository, where each cluster is also populated with member documents from across different content types. This system has been applied successfully to very large collections of legal documents, O(100M), which include judicial opinions, statutes, regulations, court briefs, and analytical documents. Extensive evaluations were conducted to determine the efficiency and effectiveness of the algorithms in topic detection, cluster association, and cluster labeling. Subsequent evaluations conducted by legal domain experts have demonstrated that the quality of the resulting recommendations across different content types is close to those created by human experts.

For full text of the paper, please contact the authors.

Thanks to Jack for allowing me to post the abstract.

Updated: Lists of Legal Metadata and Legal Knowledge Representation Resources

I’ve recently updated the list of legal metadata resources and the list of legal knowledge representation resources at Legal Information Systems and Legal Informatics Resources.

The list of legal metadata resources contains mostly schemas and standards for legal descriptive or structural metadata.

The list of legal knowledge representation resources lists resources including legal ontologies, Linked Data resources, subject headings lists, classification systems, and authority files.

The lists are licensed under a Creative Commons Attribution-Noncommercial-ShareAlike 3.0 United States License.

If you know of other legal metadata or legal knowledge representation resources missing from those lists, please feel free to mention them in the comments to this post.

Nevelow Mart & Luftig on Curation of Legal Resources, and Digest and Citator Results in Wexis

Professor Susan Nevelow Mart of the University of Colorado Boulder School of Law, and Professor Dr. Jeffrey T. Luftig of the University of Colorado, Boulder, have posted the abstract of a new paper entitled The Case for Curation: The Relevance of Digest and Citator Results in Westlaw and Lexis.

Here is the abstract:

Humans and machines are both involved in the creation of legal research resources. For legal information retrieval systems, the human-curated finding aid is being overtaken by the computer algorithm. But human-curated finding aids still exist. One of them is the West Key Number system. The Key Number system’s headnote classification of case law, started back in the nineteenth century, was and is the creation of humans. The retrospective headnote classification of the cases in Lexis’s case databases, started in 1999, was created primarily although not exclusively with computer algorithms. So how do these two very different systems deal with a similar headnote from the same case, when they link the headnote to the digesting and citator functions in their respective databases? This paper continues an investigation into this question, looking at the relevance of results from digest and citator search run on matching headnotes in ninety important federal and state cases, to see how each performs. For digests, where the results are curated – where a human has made a judgment about the meaning of a case and placed it in a classification system – humans still have an advantage. For citators, where algorithm is battling algorithm to find relevant results, it is a matter of the better algorithm winning. But no one algorithm is doing a very good job of finding all the relevant results; the overlap between the two citator systems is not that large. The lesson for researchers: know how your legal research system was created, what involvement, if any, humans had in the curation of the system, and what a researcher can and cannot expect from the system you are using.

This paper was presented at AALL 2012: American Association of Law Libraries’ Annual Meeting, held 21-24 July 2012, in Boston Massachusetts, USA.

Agnoloni et al.: Annotation Schema for Legal Doctrine: A Case Study on DoGi Database = Schema di annotazione per la dottrina giuridica: il caso di studio della banca dati DoGi-Dottrina Giuridica

Tommaso Agnoloni, Dr. Ginevra Peruginelli, Maria Teresa Sagri, and Dr. Daniela Tiscornia, all of ITTIG-CNR: Istituto di Teoria e Tecniche dell’Informazione Giuridica, have published Annotation Schema for Legal Doctrine: A Case Study on DoGi Database = Schema di annotazione per la dottrina giuridica: il caso di studio della banca dati DoGi-Dottrina Giuridica, JLIS.it: Italian Journal of Library and Information Science = rivista italiana di biblioteconomia, archivistica e scienza dell’informazione (2012).

Here is the abstract:

Interoperability today is the key term for the enhancement of databases published on the web: the data, when isolated, have little value, on the contrary, their value increases significantly when different datasets, produced and published independently by different providers, can be reused and freely mashed by third parties. The use of data for new purposes not foreseen by organizations and individuals who publish “raw data” is one of the advantages of linked open data model. To achieve these benefits content and relationships between the entities described in the dataset should be explicitly represented in standard web formats (XML, RDF, URI). The DoGi-Legal Literature database, one of the most valuable sources for online access to legal doctrine, created and managed by the Institute of Legal Information Theory and Techniques of the CNR is following this direction. This paper will define the schema of the data representing the database in RDF format. This will make the DoGi database interoperable between different data and service providers (libraries, publishers, information services for accessing national and European legal information), allowing the creation of new advanced services to be made available on the web of data. In particular, the contribution will focus on the goal to promote semantic interoperability between the DoGi classification schema and other semantic indexing tools in legal domain.

Nevelov Mart, A Study of West’s Headnotes and Key Numbers and LexisNexis’s Headnotes and Topics

Susan Nevelow Mart of the University of California Hastings College of Law has published The Relevance of Results Generated by Human Indexing and Computer Algorithms: A Study of West’s Headnotes and Key Numbers and LexisNexis’s Headnotes and Topics, 102 Law Library Journal No. 2, pages 221-249 (2010). Here is the abstract:

This article begins the investigation into the different ways results are generated in West’s “Custom Digest” and in LexisNexis’s “Search by Topic or Headnote” and by KeyCite and Shepard’s. The author took ten pairs of matching headnotes from important federal and California cases and reviewed the results sets generated by each classification and citator system for relevance. The differences in the results sets for classification systems and for citator systems raise interesting issues about the efficiency and comprehensiveness of any one system, and the need to adjust research strategies accordingly.