For over 50 years, lawyers have used process models to describe how information and decisions move. Lexipedia, developed by the Center for Civic Innovation and the University of Virginia, describes legal processes using modern procedural standards such as BPMN (Business Process Model Notation) and Petri Nets.
Process models describe how things happen, but offer no convenient discovery mechanism. Lexipedia's latest release adds linking to pull Wikidata entries in directly, plus a QuickStatements generator for the Lexipedia Wikibase — where laws, case law, and other content not yet ready for the Wikidata ecosystem can await community review.
Linked data adds further value through specific legal ontologies: Akoma Ntoso, which correlates legal axioms across global legal systems, and deontic logic, which defines logic from language.
Cross-referencing legal concepts is self-explanatory; deontic logic is more nuanced. For example, if one MUST do something, it's implied there's a consequence for not doing it. In legal texts these statements often aren't adjacent, and get left out of models. Describing content with deontic logic lets us run a baseline "legal linting" pass that improves models and simplifies review.
See how the Georgia Tech Library designed and built a dataset of notable architecture alumni in Wikidata, for outreach and development. We will talk about the research need that led to the development of the dataset, reflect on the design and implementation challenges encountered along the way, and future plans for further development.
What does openness mean when data cannot leave a restricted environment? This lightning talk discusses how linked data principles are being adapted within the National Security Research Center (NSRC) at Los Alamos National Laboratory, where more than eighty years of secrecy have made access control a defining feature of knowledge organization.
At the NSRC, security requirements function as design parameters for semantic modeling, metadata standardization, and relationship building. These efforts support access and interoperability in an environment where data cannot be published on the open web. Here, openness takes shape through deliberate choices about what can be connected, who can follow those connections, and under what conditions.
Bridging library metadata to the semantic web sounds simple — until you're staring at a fuzzy title match and wondering whether "Emma" the Wikidata item is actually "Emma" the Jane Austen novel. This talk walks through a working pipeline that reconciles MARC records and spreadsheets against Wikidata before generating BIBFRAME RDF — deliberately in that order.
MARC's fixed fields, controlled identifiers, and $0/$1 authority links are a more reliable reconciliation substrate than post-conversion RDF would be: decades of cataloging discipline mean an ISBN or an LC name-authority code can be trusted at face value, in a way a freshly-generated triple can't yet be. Reconciling at this stage — while those signals are still intact — lets Wikidata's enormous, freely-reusable graph of works, people, and places get folded directly into the RDF as it's built, rather than bolted on after. MARC turns out to be less a legacy format to escape and more infrastructure in service of the linked data it produces.
The core mechanism is a tiered confidence system: identifiers auto-accept, fuzzy titles get a second look only when independently confirmed by author identity, and everything else is flagged rather than guessed at. I'll also cover verifying the BIBFRAME modeling itself against real production records — which caught errors theory alone missed.
