REGNET Stanford University Gloria Lau Dr. Shawn Kerrigan Dr. Kincho Law Dr. Gio Wiederhold WITS’03 Dec 13th, 2003 An Information Infrastructure for Government Regulations

1 Motivation  Multiple sources of regulations  E.g. federal, state, local  Different formats  Conflicting ideas  Need for a repository  Locate relevant information  E.g. small business  Need for analysis tool  Complexity of regulations  Multiple sources  Understanding of regulations & their relationships

2 Example 1 ADAAG Appendix … Such a curb ramp opening must be located within the access aisle boundaries, not within the parking space boundaries. CBC 1129B.4.3 … Ramps shall not encroach into any parking space. Exception: 1. Ramps located at the front of accessible parking spaces may encroach into the length of such spaces …  CBC allows curb ramps encroaching into accessible parking stall access aisles, while ADA disallows encroachment into any portion of the stall.

3 Example 2 ADAAG Slope. …Transitions from ramps to walks, gutters, or streets shall be flush and free of abrupt changes… CBC 1127B.5.5 Beveled lip. The lower end of each curb ramp shall have a ½ inch (13mm) lip beveled at 45 degrees as a detectable way- finding edge for persons with visual impairments.  ADAAG focuses on wheelchair traversal; CBC focuses on the visually impaired when using a cane.

4 Scope  Repository development  Shallow parser  Feature extraction  Ontology development  Automated extraction of related provisions  Feature matching  Structural matching  Application to e-rulemaking  Compliance assistance using a Q&A system  FOPC logic implementation  Q&A compliance check

5 Repository development

6 Shallow parser  Data Source  Accessibility standards  US, UK and Scotland  Drinking water standards in Environmental regulations  Federal and California  Current standard: HTML, PDF, hardcopy...  Our system standard: XML  Unit of extraction: section Fixed or built-in seating,...

7 Automated Translation to Hierarchical Structure PART 279—Standards For The Management Of Used Oil Subpart B – Applicability … § Prohibitions. (a) Surface impoundment prohibition. Used oil shall not be managed in surface impoundments or waste piles unless the units are subject to regulation under parts 264 or 265 of this chapter. (b) Use as a dust suppressant. The use of used oil as a dust suppressant is prohibited, except when such activity takes place in one of the states listed in § (c). (c) Burning in particular units. Off-specification used oil fuel may be burned for energy recovery in only the following devices: (1) Industrial furnaces identified in § of this chapter; (2) Boilers, as defined in § of this chapter, that are identified as follows: (i) Industrial boilers located on the site of a facility engaged in a manufacturing process where substances are transformed into new products, including the component parts of products, by mechanical or chemical processes; …. Subsection (a) Subsection (b) Subsection (c) 40 CFR 279 Subpart ASubpart BSubpart I Section Section Section … …… contains … (a) Surface impoundment prohibition. Used oil shall not be managed in surface impoundments or waste piles unless the units are subject to regulation under parts 264 or 265 of this chapter. (a) Surface impoundment prohibition. Used oil shall not be managed in surface impoundments or waste piles unless the units … Example:

8 Ontology View

9 Feature extraction  Generic features  Concepts  Exceptions  Definitions  Domain-specific features  Glossary terms  Author-prescribed indices  Effective dates  Measurements  Chemicals, e.g., drinking water contaminants

10 XML regulation with features added Original section b from the 40 CFR § Maximum contaminant levels for inorganic chemicals. (a) The maximum contaminant level for arsenic applies only to community water systems... (b) The maximum contaminant level for arsenic is 0.05 milligrams per liter for community water systems until January 23, Refined section b in XML format... The maximum contaminant level for arsenic is 0.05 milligrams per liter for community water systems until January 23, 2006.

11 Similarity Analysis

12 Similarity Score computation  Feature matching  f 0 = (  i = features f i ) / # features i  Features  Concept & index match  tf  idf vector  tf = term frequency  idf = inverse document frequency = log( n / n i )  Chemical match  Measurement match  Exception match  Effective date match  Glossary/definition term match

13 Score refinements  Near-tree neighbors  Self vs. parent-sibling-child (psc), f s-psc  psc vs psc, f psc-psc

14 Score refinements  Reference distribution, f rd  Not-so-immediate neighbor effect on score  E.g. f (A5.3, U6.4(a)) updates f (A2.1, U3.3)

15  Phrasing difference between American and British regulations ufas Door Hardware. Handles, pulls, latches, locks, and other operating devices on accessible doors shall have a shape that is easy … bs Door Furniture. Door handles on hinged and sliding doors in accessible bedrooms should be easy to grip …  Neighbor similarities imply similarity between the interested nodes Preliminary results: UFAS vs BS8300

16  Application domain: e-rulemaking  Comparison between draft of rules and the associated public comments  ADAAG Chapter 11, rights-of-way draft  Less than 15 pages  Over 1400 public comments received within 4 months  Comments ~ 10MB in size; most are several pages long  New regulation draft can easily generate a huge amount of data that needs to be reviewed and analyzed Preliminary results: e-rulemaking

17 Preliminary results: e-rulemaking

18  Related draft section and public comment Adaag Where signal timing is inadequate for full crossing of all traffic lanes or where the crossing is not signalized, cut-through medians … Deborah Wood, October 29, 2002 … This often means walk lights that are so short in duration that by the time a person who is blind realizes …  No identified related section Donna Ring, September 6, 2002 If you become blind, no amount of electronics … will make you safe … You have to learn modern blindness skills from a good teacher. You have to practice your new skills …  Concern not addressed in the draft Preliminary results: e-rulemaking

19 Compliance Assistance System

20 Compliance Issues

21 Conclusions  An infrastructure for  Repository development  Shallow parser  Feature extraction  Ontology development  Automated extraction of related provisions  Feature matching  Structural matching  Application to e-rulemaking  Compliance assistance using a Q&A system  FOPC logic implementation  Q&A compliance check  Future Directions  Application on other semi-structured documents  Inconsistency identification

22 Thank You! Questions?