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 Institute
Robert 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>

<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:ObjectPropertyrdf:ID="implicitlyAuthorizes">
<owl:inverseOf>
<owl:ObjectProperty
rdf:ID="isImplicitlyAuthorizedBy"/>
</owl:inverseOf>
<rdfs:rangerdf:resource="#AuthorizedItem"/>
<rdfs:domainrdf: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. Scire16, 2 (July-Dec. 2010), 47-51.
Axel-Lute, P. 1979. Federal documents, 1978. Law Libr. J. 72, 2 (Spr. 1979), 222-234, 228.
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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
Bontouri, L., Papatheodorou, C., Soulikias, V., and Stratis, M. 2009. Metadata interoperability in public sector information. J. Inform. Sci. 35, 2 (Apr. 2009), 204-231. DOI=10.1177/0165551508098601.
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.
Farina, C. R., Katzen, S., Bruce, T. R., et al. 2008. Achieving the Potential: The Future of Federal E-rulemaking: A Report to Congress and the President. American Bar Association, Chicago, IL.
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.

References (4/7)
García, R. and Gil, R. 2008. A Web ontology for copyright contracts management. Int. J. Electron. Comm. 12, 4 (Sum. 2008), 99-114. DOI=10.2753/JEC1086-4415120404.
Krippendorff, K. 2004. Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage, Thousand Oaks, CA.
Library of Congress. Policy and Standards Division. 2010. Library of Congress Subject Headings (32nd ed.). Library of Congress, Cataloging Distribution Service, Washington, DC.
Marchetti, A., Megale, F., Seta, E., and Vitali, F. 2002. Using XML as a means to access legislative documents: Italian and foreign experiences. ACM SIGAPP Appl. Comput. Rev. 10, 1 (Spring 2002), 54-62. DOI=10.1145/568235.568246.
McDermott, J. 1986. Another analysis of full-text legal document retrieval. Law Libr. J. 78, 2 (Spr. 1986), 337-344.

References (5/7)
Mersky, R. M. and Dunn, D. J. 2002. Fundamentals of Legal Research. 8th ed. Foundation Press, New York, NY.
Nadah, N., Dulong de Rosnay, M., and Bachimont, B. 2007. Licensing digital content with a generic ontology: Escaping from the jungle of rights expression languages. In Proceedings of the 11th International Conference on Artificial Intelligence and Law (Stanford, California, June 04 - 08, 2007). ICAIL '07. ACM, New York, NY, 65-69. DOI=10.1145/1276318.1276330.
National Archives. 2010. Table of Legislative Effects. National Archives, London, UK. http://www.statutelaw.gov.uk/help/Table_of_Legislative_Effects.htm.
Office of the Federal Register. 2004. Code of Federal Regulations List of Subjects. Office of the Federal Register, NARA, Washington, DC. http://www.archives.gov/federal-register/cfr/subjects.html .
Office of the Federal Register. 2009. CFR Index and Finding Aids, Revised as of January 1, 2009. US GPO, Washington, DC, 1-776.

References (6/7)
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.
Office of the Federal Register. 2009. Parallel table of authorities and rules. In CFR Index and Finding Aids, Revised as of January 1, 2009. US GPO, Washington, DC, 779-888.
Ortiz-Rodríguez, F. 2007. EGODO and applications: Sharing, retrieving and exchanging legal documentation across e-government. In Proceedings of the Workshop on Semantic Web Technology for Law (Stanford, California, June 08, 2007). SW4Law ’07. VrijeUniversiteit Amsterdam Department of Computer Science, Amsterdam, 21-26.
Robinson, D. G., Yu, H., Zeller, W., and Felten, E. W. 2009. Government data and the invisible hand. Yale J. Law & Technol. 11, 1 (Fall 2009), 160-175, http://ssrn.com/abstract=1138083 .
Sheridan, J. L. 2010. Legislation.gov.uk. VoxPopuLII(Aug. 15, 2010). http://blog.law.cornell.edu/voxpop/2010/08/15/legislationgovuk/ .

References (7/7)
Thomson Reuters. 2010. Using Related Materials on WestlawNext. Thomson Reuters, Eagan, MN.
United States. 2008. United States Code (2006 ed.) (Vols. 33-36). US GPO, Washington, DC.
Zittrain, J. 2009. The Future of the Internet—And How to Stop It. Yale University Press, New Haven, CT.

Contacts
Tom Bruce, Legal Information Institute, trb2 [at] cornell.edu
Robert Richards, University of Washington, robertrichards03 [at] gmail.com

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

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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 Presentation Transcript