WikidataCon 2025

WikidataCon 2025

Tiago Lubiana

I earned my PhD in 2024, studying Wikidata and cell types at USP, and then spent six wonderful months as Wikimedian at the Biodiversity Heritage Library. I love studying nature, building software, and organizing knowledge in computational structures. I find the life sciences exquisitely beautiful and believe in open knowledge as a tool for happier lives.


Sessions

10-31
19:30
30min
Wikidata and Biodiversity — a match made for Earth
Tiago Lubiana

We love Wikidata. We love biodiversity. And we connect both!

This presentation will build on the Wikimedia and Biodiversity Data session at Living Data 2025 (https://meta.wikimedia.org/wiki/Event:Living_Data_2025).

It will be a whirlwind through some biodiversity+Wikidata activities, including connections with iNaturalist, GBIF, the Biodiversity Heritage Library, and the WikiProject Biodiversity. Participants will see fun tools, beautiful images, and a thriving community.

Providing the World with Good Data
One and Only
11-01
10:00
60min
Rewrite scholarly SPARQL queries for the graph split + Federating SPARQL involving Wikibase
Tiago Lubiana, Daniel Mietchen

Rewriting scholarly SPARQL queries for the graph split: Tiago Lubiana
Building on a previous presentation at WikiCite 2025, we will show an overview of the process that led to the graph split on Wikidata and walk participants through rewriting SPARQL queries. The session will present some of the tricks for adapting queries to the split, including internal federation and Blazegraph hints. The session will build capacity towards the rewrite of scholarly queries, with a particular focus on supporting the Scholia platform, as well as briefly discuss how queries can be prepared for a future transition (hint: staying as close as the core syntax of the SPARQL standard as possible).

Federating SPARQL queries involving Wikibase instances: Daniel Mietchen
Federated queries make it possible to connect knowledge across different SPARQL endpoints, enabling richer insights than any single dataset can provide. For the Wikibase ecosystem, this is especially powerful, as researchers, institutions, and community projects often maintain their own Wikibase instances, and being able to query across several of them (including Wikidata) opens new opportunities for discovery, reuse, and collaboration.

The Future of Wikidata
One and Only