2025-11-01 –, One and Only
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.
Part 1: Presentation (30 mins)
Part 2: Workshop (30 mins)
Part 1:
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).
Links:
The session will be a remix of this WikiCite presentation:
https://commons.wikimedia.org/wiki/File:WikiCite_2025_-WDQS_Graph_Split%E2%80%94_Overview_and_Query-a-thon.pdf
It is based on the process of documenting the graph split for the WikiCite 2025 conference, available at:
https://meta.wikimedia.org/wiki/WikiCite/WDQS_graph_split
Part 2:
The workshop will cover practical aspects of enabling, designing and running SPARQL federation involving Wikibase instances. We will cover the basics of how federated queries work in Wikidata’s now-split Query Service, demonstrate typical use cases, and highlight common challenges such as performance, endpoint reliability, and differences in data modeling. Real examples will show how queries can combine data fom Wikibase instances with external resources to enrich context, validate data or link domain-specific knowledge back to the wider Linked Open Data world.
Participants will come away with a better understanding of when and how to use federation effectively, what pitfalls to avoid, and how to make the most of federated queries in their own projects. In preparation, participants are invited to share their own experiences as well as common problems and how to tackle them.
Daniel Mietchen is a biophysicist interested in integrating open research and education workflows with the web. His research spans multiple scales and disciplines: from subcellular processes to whole organisms, from fossils to developing embryos, and from biodiversity informatics to mathematics and data science. He is particularly interested in how these diverse perspectives connect with sustainable development. With experience across many stages of the research cycle, Daniel has explored a wide range of practices in collaboration, sharing, and reproducibility. Beyond that, he has been an active contributor to Wikipedia and other Wikimedia projects for nearly twenty years, working to strengthen the ties between the Wikimedia and research communities, particularly through Wikidata.
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.