Caselaw is Set Free, What Next? by Thomas Bruce, Director, Legal Information Institute, Cornell.
Thomas provides a great history of Google Scholar’s caselaw efforts and its impact on the legal profession.
More importantly, at least to me, were his observations on how to go beyond the traditional indexing and linking in legal publications:
A trivial example may help. Right now, a full-text search for “tylenol” in the US Code of Federal Regulations will find… nothing. Mind you, Tylenol is regulated, but it’s regulated as “acetaminophen”. But if we link up the data here in Cornell’s CFR collection with data in the DrugBank pharmaceutical collection , we can automatically determine that the user needs to know about acetaminophen — and we can do that with any name-brand drug in which acetaminophen is a component. By classifying regulations using the same system
that science librarians use to organize papers in agriculture, we can determine which scientific papers may form the rationale for particular regulations, and link the regulations to the papers that explain the underlying science. These techniques, informed by emerging approaches in natural-language processing and the Semantic Web, hold great promise.All successful information-seeking processes permit the searcher to exchange something she already knows for something she wants to know. By using technology to vastly expand the number of things that can meaningfully and precisely be submitted for search, we can dramatically improve results for a wide swath of users. In our shop, we refer to this as the process of “getting from barking dog to nuisance”, an in-joke that centers around mapping a problem expressed in real-world terms to a legal concept. Making those mappings on a wide scale is a great challenge. If we had those mappings, we could answer a lot of everyday questions for a lot of people.
(emphasis added)
The first line I bolded in the quote:
All successful information-seeking processes permit the searcher to exchange something she already knows for something she wants to know.
captures the essence of a topic map. Yes? That is a user navigates or queries a topic map on the basis of terms they already know. In so doing, they can find other terms that are interchangeable with theirs, but more importantly, if information is indexed using a different term than theirs, they can still find the information.
In traditional indexing systems, think of the Readers Guide to Periodical Literature, Library of Congress Subject Headings, some users learned those systems in order to become better searchers. Still an interchange of what you know for what you don’t know, but with a large front-end investment.
Thomas is positing a system like topic maps that enables a users to navigate by the terms they know already to find information they don’t know.
The second block of text I bolded:
Making those mappings on a wide scale is a great challenge. If we had those mappings, we could answer a lot of everyday questions for a lot of people.
Making wide scale mappings certainly is a challenge. In part because there are so many mappings to be made and so many different ways to make them. Not to mention that the mappings will evolve over time as usages change.
There is growing realization that indexing or linking data results in a very large pile of indexed or linked data. You can’t really navigate it unless or until you hit upon the correct terms to make the next link. We could try to teach everyone the correct terms but as more correct terms appear everyday, that seems an unlikely solution. Thomas has the right of it when he suggests expanding the target of “correct” terms.
Topic maps are poised to help expand the target of “correct” terms, and to do so in such a way as to combine with other expanded targets of “correct” terms.
I first saw this in a tweet by Aaron Kirschenfeld.
Update: Tarlton Law Libary (University of Texas at Austin) Legal Research Guide has a great page of tips and pointers on the Google Scholar caselaw collection. Bookmark this guide.