Finding where to contribute on Wikidata isn't always straightforward, especially with structured and lexicographical data spread across multiple WikiProjects and languages. Identifying a gap, and knowing how to act on it, can be harder than making the edit itself.
This session introduces Dustpan and Broomstick, two tools developed by Wikicollabs that help contributors discover opportunities to improve Wikidata. Dustpan helps contributors find Items with missing information by selecting a WikiProject, a category of missing information, and, where available, an additional scope. For example, contributors working with WikiProject Sum of All Paintings can use Dustpan to find paintings that are missing information, such as the creator or material used. Broomstick focuses on lexicographical data, helping contributors uncover Lexemes that can be improved across different languages, including issues involving Senses, Forms, and misplaced statements.
Through live demonstrations, participants will see how finding a gap leads to a specific edit they can make on Wikidata. By the end of the session, participants will be able to use Dustpan and Broomstick to find where to contribute on Wikidata. We also welcome suggestions for which WikiProjects and languages the tools should support next.
This session will provide an overview of Wiki Loves Names and its contribution to Wiktionary. It will highlight the importance of documenting personal names, their meanings, origins, pronunciations, linguistic forms, and cultural contexts, particularly names from underrepresented languages and communities.
The session will explore how Wiki Loves Names supports the preservation and visibility of naming traditions by encouraging contributors to add well-sourced information about names to Wiktionary. It will also highlight the value of Wiktionary as a free, multilingual dictionary and how name-related contributions can help improve knowledge about languages and cultures that are often underrepresented online.
The session will share the objectives, approach, progress, and potential impact of the initiative, while showcasing examples of contributions and opportunities for community participation. It will be an introductory overview rather than a hands-on training session.
Designed for digital humanities research, Semantic Kompakkt is a free, open-source platform for exploring and semantically annotating visual media in an interconnected open-data environment. Semantic Kompakkt, provides accessible features through graphical interfaces while Wikibase manages metadata storage as linked open data, thus enabling the publication and annotation of 2D, 3D, and audiovisual media.
The proposed talk shares lessons from an evaluation of the metadata presented on Semantic Kompakkt field names as reviewed by digital archaeologists. The review was done as part of a project to reduce fuzziness within the platform. Fuzziness, also referred to as wobbliness, serves as an overarching concept encompassing indistinguishable combinations of uncertainty and vagueness within statements or datasets, as well as broader informational ambiguities such as unreproducible literature claims or imprecise ontological mappings.
As a result some key field names were updated, which include; the “persons and institutions” which became “actors”; and descriptions on object types, provenance, material, dimensions, collection and other such, which were re-directed to the original object data from the existing collection. This resulted in having to re-upload the items on Wikibase with all the new statements so as to better serve the objects on display in Semantic Kompakkt.
Agentic AI coding tools such as Claude Code, OpenAI Codex, and the open source OpenCode enable users to create sophisticated software applications from natural-language feature descriptions. This approach, often called “vibe coding,” allows people without software development experience to build applications. It also changes how experienced developers can iteratively orchestrate AI agents to engineer software within highly compressed time frames.
This presentation describes an experiment conducted over a single weekend: developing a static-site RDF editor that uses a graph-based editing approach rather than the form-based interfaces used by tools such as Sinopia, Marva, and Share-VDE’s JCricket. The editor is available at https://ld4p.github.io/graph-editor/, and its source code is hosted at https://github.com/LD4P/graph-editor/.
Software Engineer, Stanford University Libraries, Software Developer
Jeremy Nelson is a software engineer at Stanford University Libraries. He is on the team that migrated Stanford to FOLIO and is active developer in the Sinopia Linked Data Editor and Blue Core projects. His research interests include applying AI to improving library workflows.
Tuesday September 29, 2026 3:20pm - 3:50pm EDT TBA
In this presentation, the PCC Sinopia Cataloging Affinity Group will share updates to the Sinopia editor made for Blue Core, including updates to the interface, functionality, and seed data. We will provide an overview of Sinopia, compare Sinopia Classic to Sinopia for Blue Core, and highlight plans for production cataloging in BIBFRAME. We will review recent developments to operational metadata such as data associated with the BIBFRAME AdminMetadata class, and outline ways to get started with BIBFRAME cataloging in Sinopia.
