Bruce, T. R., and Richards, R. C. (2011). Examples of Specialized Legal Metadata Adapted to the Digital Environment, from The U.S. Code of Federal Regulations

Examples of Specialized Legal Metadata to the Digital Environment, From the U.S. Code of Federal Regulations

Thomas R. Bruce, Legal Information InstituteRobert C. Richards, Jr., University of Washington

dg.o 2011: 12th Annual International Conference on Digital Government Research, 14 June 2011, University of Maryland, College Park http://dgo2011.dgsna.org/

The Problem: “Islands”

•Governments create multiple sources of law

•The sources are interrelated, but exist as isolated “islands” of legal knowledge & information

•How can one efficiently discover all sources of law related to a particular source of law?

The Problem: Example•Example: How to find all regulations

issued pursuant to US Food, Drug, & Cosmetic Act, 21 U.S.C. ch. 9?

•Two “Islands”: The statute is in the U.S. Code, while the regulations are in the Code of Federal Regulations

One Solution: “Ponts”•In the print environment, specialized legal

metadata sources were created, to make explicit relationships between different sources of law. We call these sources “ponts,” because they function as “bridges” between “islands” of legal information

Ponts: Proprietary vs. Public Domain

•Proprietary ponts are of limited use in digital environment because of usage restrictions & license fees• e.g., West’s American Digest System

• Public domain ponts—like those created by U.S. federal government, which are free from copyright, 17 U.S.C. § 105—lack usage restrictions & license fees, have great potential in digital domain▫e.g., PTOA, CONAN, Cong. Rec. History of Bills

Example of a Pont: The PTOA

•Parallel Table of Authorities & Rules (PTOA)

•Metadata in the Code of Federal Regulations (CFR)

•Links statutes to regulations they authorize

•Created by U.S. federal government, public domain, free from use restrictions/license fees

PTOA: Excerpt

• 1 U.S.C. 112.................................................................1 Part 2 112a--112b....................................................22 Part 181 113.................................................................1 Part 2 133..............................................................32 Part 151 • 2 U.S.C. 136..............................................................36 Parts 701, 702, 703, 705 170..............................................................36 Part 705

PTOA in Print: Human-Dependent

•Most ponts created for print environment require human intervention to ensure connection between the different legal sources they seek to link

•PTOA in print requires human intervention

PTOA: Preparing It for Digital

• Goals:

▫Disintermediation: Make PTOA processable by software without

human intervention

▫Foster interoperability & re-use

▫Create “generative resource” (Zittrain)

▫Foster innovation

PTOA: Preparing It for Digital (cont’d)

• Recommended formats:▫XML ▫RDF/OWL

• Why XML & RDF/OWL?▫Open, international standards▫Widely used and understood▫Enable re-use and interoperability▫Enable “generative” uses▫Foster innovation: developers are equipped to

create new systems to process them

PTOA: Use Cases

• Information Retrieval & Discovery▫Bidirectional discovery▫Revelation of implicit relationships▫Automated retrieval▫Cross-language retrieval▫Linked Data

• Scholarly Research• Public Administration• eParticipation• GIS• Machine Learning: Automatic Creation of Ponts

PTOA: Obstacles to Preparation for Digital Use

•Semantics (Ambiguity)

•Granularity

•Directionality

•Data Quality

PTOA Obstacles: Semantics

•1. Relationships between sources are ambiguous

•Relationships represented in a PTOA row may be of four possible types:▫“Is Express Authority For”▫“Is Implied Authority For”▫“Is Applied By”▫“Is Interpreted By”

PTOA Obstacles: Semantics (cont’d)

• 2. Some PTOA rows list multiple sources on one or both sides:

• 1 U.S.C. 112..................................................................................1 Part 2 112a--112b.................................................................22 Part 181 113..................................................................................1 Part 2 133...............................................................................32 Part 151 • 2 U.S.C. 136............................................................................. 36 Parts 701, 702, 703, 705 170...............................................................................36 Part 705

PTOA Obstacles: Semantics (cont’d)

•Result: In many PTOA rows, relationships between sources are multiple and complex

•Result: In most rows, the precise meaning of relationships is implicit & often not discernible by software

PTOA Obstacles: Granularity

•PTOA regulation cites refer only to the “Part” level of CFR

•But the relationships intended to be represented in PTOA usually occur at more granular levels: “section” or “sub-section”

PTOA Obstacles: Granularity: Example

“1 U.S.C. […]“112a--112b................................22 Part 181”

• 1 U.S.C. section 112b (specifically subsection (f)) expressly provides authority for components of 22 C.F.R. part 181 (specifically sections 181.1 through 181.7).

• 1 U.S.C. section 112a (specifically subsection (d)) implicitly provides authority for components of 22 C.F.R. part 181 (specifically sections 181.8 and 181.9).

PTOA Obstacles: Granularity (cont’d)

•So each PTOA row must be analyzed & divided into multiple rows at accurate level of granularity

PTOA Obstacles: Directionality

•In PTOA, retrieval and discovery can only occur in one direction: from statute to regulation

•1 U.S.C. […] 112a--112b................................22 Part 181

PTOA Obstacles: Directionality

•But in digital world, PTOA could add great value if it were bidirectional: if it enabled discovery from regulations to statutes, as well as from statutes to regulations

PTOA Obstacle: Data Quality

•Production of PTOA is decentralized: each individual agency creates rows for its regulations

•Result: Inconsistent quality of PTOA data

•Need: For Digital PTOA to express editor’s evaluation of data quality, in machine-processable metadata

Digital PTOA: XML Example: Barebones, No Fixes

<?xml version="1.0" encoding="UTF-8"?> <ptoa> <ptoaentry> <!-- Example 1 --> <authority> <uscode> <title>1</title> <sectrange> <start>112a</start> <end>112b</end> </sectrange> </uscode> </authority> <authorized> <cfr> <title>22</title> <part>181</part> </cfr> </authorized> </ptoaentry> </ptoa></?xml>

Digital PTOA: XML: Now with URNs, Granularity, Ranges

<?xml version="1.0" encoding="UTF-8"?> <ptoa> <ptoaentry> <authority type="implicit_authority"> <uscode> <title>1</title> <section urn="urn:lex:us:federal:codified.statute:2010;1.usc.112a@official;house.gov:en$text-html:legal.information.institute">112a</section> <sectionfragment>d</sectionfragment> </uscode> </authority> <authorized> <cfr> <title>22</title> <part urn="urn:lex:us:federal:codified.regulation:2010;22.cfr.181@official;gpo.gov:en$text-xml">181</part> <section urn="urn:lex:us:federal:codified.regulation:2010;22.cfr.181.8@official;gpo.gov:en$text-xml">181.8</section> <section urn="urn:lex:us:federal:codified.regulation:2010;22.cfr.181.9@official;gpo.gov:en$text-xml">181.9</section> </cfr> </authorized> </ptoaentry> </ptoa></?xml>

Digital PTOA: RDFS/OWL: Bidirectionality & Disambiguation

<owl:ObjectProperty rdf:ID="implicitlyAuthorizes"> <owl:inverseOf> <owl:ObjectProperty rdf:ID="isImplicitlyAuthorizedBy"/> </owl:inverseOf> <rdfs:range rdf:resource="#AuthorizedItem"/> <rdfs:domain rdf:resource="#AuthorizingItem"/> <rdfs:subPropertyOf> <owl:ObjectProperty rdf:ID="isAuthorityRefFor"/> </rdfs:subPropertyOf> </owl:ObjectProperty>

Digital PTOA: RDFS/OWL: Granularity

<owl:ObjectProperty rdf:ID="hasUSCSectionFragment"> <rdfs:domain rdf:resource="#USCodeSection"/> <owl:inverseOf> <owl:ObjectProperty rdf:ID="isUSCSectionFragmentOf"/> </owl:inverseOf> <rdfs:range rdf:resource="#USCodeSectionFragment"/></owl:ObjectProperty>

Challenges to Adapting the PTOA for the Digital Environment

•Much relevant information is implicit, might not be automatable▫Need experiments to determine▫Likely will require labor by humans trained

in law▫Possible approach: partial automation:

application recommends options to human coders

Challenges to Adapting the PTOA for the Digital Environment (cont’d)

•Inter-coder reliability needs to be tested & kept at high level

•Paucity of law-related Linked Data resources, http://legalinformatics.wordpress.com/2009/08/19/linked-data-and-law/

Related Research

•Earlier studies of print-based ponts introduced into digital environment: Al-Kofahi et al. (2001); Dabney (1986); McDermott (1986)

•Findings:▫a. New uses of ponts arose in digital

environment ▫b. Ponts positively influenced retrieval

performance

Similar Projects

•Legislation.gov.uk (Legislative Information Retrieval): Table of Legislative Effects, CEN MetaLex (legislative status)

•AGILE (Public Administration System): CEN MetaLex & OWL, http://ceur-ws.org/Vol-582/paper4.pdf

Other Ponts to Examine

•Already Known:▫Congressional Record: “History of Bills &

Resolutions,” http://tinyurl.com/432awbw ▫CFR List of Subjects & Subject Index,

http://tinyurl.com/3udaqa2 ▫United States Code Subject Index▫Constitution of the United States Annotated

(CONAN), http://tinyurl.com/3w5xm6q

Other Ponts to Examine (cont’d)

•To Be Discovered:

▫Legal information professionals might examine legal research bibliographies & legal research systems to identify additional public domain ponts

▫Especially state & local jurisdictions, or respecting particular areas of law

Digital PTOA: Next Steps

•Spring 2011: Receive input from colleagues at conferences

•Summer & Fall 2011: Build prototype

References (1/7)• Administrative Conference of the United States. 1971. Report of the

Committee on Information, Education, and Reports in Support of Recommendation no. 3. In Recommendations and Reports of the Administrative Conference of the United States, January 8, 1968-June 30, 1970 (Vol. 1). US GPO, Washington, DC, 63-65.

• Al-Kofahi, K., Tyrrell, A., Vachher, A., Travers, T., and Jackson, P. 2001. Combining multiple classifiers for text categorization. In Proceedings of the 10th International Conference on Information and Knowledge Management (Atlanta, Georgia, November 05 - 10, 2001). CIKM '01. ACM, New York, NY, 97-104. DOI=10.1145/502585.502603.

• Alvite Díez, M. L., Pérez-León, B., Martínez González, M., and Blanco, D. F. J. V. 2010. Propuesta de representación del tesauro Eurovoc en SKOS para su integración en sistemas de información jurídica. Scire 16, 2 (July-Dec. 2010), 47-51.

• Axel-Lute, P. 1979. Federal documents, 1978. Law Libr. J. 72, 2 (Spr. 1979), 222-234, 228.

• Bartolini, R., Lenci, A., Montemagni, S., Pirrelli, V., and Soria, C. 2004. Automatic classification and analysis of provisions in Italian legal texts: A case study. In Proceedings of the OTM Confederated International Workshops and Posters (Cyprus, October 25-29, 2004). OTM ’04. Springer, Berlin. 593-604. DOI=10.1007/978-3-540-30470-8_72.

References (2/7)

• Bennett, D. and Harvey, A. 2009. Publishing Open Government Data: W3C Working Draft 8 September 2009. World Wide Web Consortium. http://www.w3.org/TR/2009/WD-gov-data-20090908/ .

• Boer, A. 2009. The Agile project (late 2008-2010). Presentation given at Jacquard Bijeenkomst 2009 (The Hague, The Netherlands, December 11, 2009). http://www.jacquard.nl/8/assets/File/December2009/Jacquard-2009-12-11-Agile-zoals-gegeven.ppt .

• Boer, A. and Van Engers, T. 2009. The Agile project: Reconciling agility and legal accountability. In Proceedings of the 2nd International Conference on ICT Solutions for Justice (Skopje, Macedonia, September 24, 2009). ICT4JUSTICE ’09. CEUR Workshop Proceedings 582. CEUR, Aachen, Germany, 41-49, http://ceur-ws.org/Vol-582/paper4.pdf

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• Congressional Research Service. 2004. The Constitution of the United States of America: Analysis and Interpretation. US GPO, Washington, DC.

References (3/7)

• Dabney, D. P. 1986. The curse of Thamus: An analysis of full-text legal document retrieval. Law Libr. J. 78, 1 (Win. 1986), 5-40.

• Dini, L., Peters, W., Liebwald, D., Schweighofer, E., Mommers, L., and Voermans, W. 2005. Cross-lingual legal information retrieval using a WordNet architecture. In Proceedings of the 10th International Conference on Artificial Intelligence and Law (Bologna, Italy, June 06 - 11, 2007). ICAIL '05. ACM, New York, NY, 163-167. DOI=10.1145/1165485.1165510.

• Ekstrom, J. A. and Lau, G. T. 2008. Exploratory text mining of ocean law to measure overlapping agency and jurisdictional authority. In Proceedings of the 9th Annual International Conference on Digital Government Research (Montreal, Canada, May 18 - 21, 2008). dg.o ’08. ACM, New York, NY, 53-62.

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• Francesconi, E., Montemagni, S., Peters, W., and Tiscornia, D., Eds. 2010. Semantic Processing of Legal Texts: Where the Language of Law Meets the Law of Language. Springer, Berlin.

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• Mersky, R. M. and Dunn, D. J. 2002. Fundamentals of Legal Research. 8th ed. Foundation Press, New York, NY.

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• Office of the Federal Register. 1949. Parallel tables of statutory authorities and rules. In Code of Federal Regulations (Vol. 2). US GPO, Washington, DC, 19-144.

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•Thomson Reuters. 2010. Using Related Materials on WestlawNext. Thomson Reuters, Eagan, MN.

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Contacts

•Tom Bruce, Legal Information Institute, trb2 [at] cornell.edu

•Robert Richards, University of Washington, robertrichards03 [at] gmail.com