Linked Data Model for Legal Information Processing System

Context & Background

Legal information typically includes both structured databases (court dates, parties, judges) and highly unstructured documents (evidence transcripts, case judgments). Retrieving relevant precedents across heterogeneous, siloed databases is a major barrier for legal professionals.

Problems to be Addressed

There is no standard database format or warehousing protocol across Indian courts. Keyword search tools fail to contextually understand query intent (e.g. queries on 'freedom of speech' or 'highway land disputes').

Aims and Objectives

1. Design an RDF-based linked data model for Indian legal documents.
2. Implement a faceted search engine with semantic filters.
3. Convert legacy databases (MongoDB, SQL) into unified cognitive stores.

Methodology

Case records are parsed, cleaned, and converted into Resource Description Framework (RDF) formats to build legal ontologies. The project designs SPARQL endpoints and user-friendly web query interfaces. Faceted navigation categories group cases by judge, court, timeline, and dispute topic.

Expected Outcomes

A semantic search web platform for legal case retrieval, open-access legal databases, and publications in database management conferences.