Wikidata is a large, collaborative database. Each artist, artwork, exhibition, and museum becomes an item with standardized fields. Instead of searching separate catalogues, you query a single environment. There you find clear connections among people, works, places, and concepts. The result is a networked view that makes it easier to discover relationships, compare information, and verify sources.
For those working in contemporary art, curatorial practice, and digital methods, this brings structure and transparency. A lesser-known artist receives a stable identifier—the QID—and becomes findable. A digital artwork is no longer “just a video.” It can record its software, programming language, dependencies, and exhibition context. Curatorial choices become easier to explain because every statement requires a reference.
The workflow is practical. First, define your project’s scope. Next, reconcile your list of names with items in Wikidata. Complete the fields using trustworthy sources. Finally, ask questions that cut across databases and languages. Over time, scattered data turns into a coherent research map.
Wikidata also functions as a public layer of infrastructure. It connects spreadsheets, catalogues, institutional repositories, and artists’ websites. Reconciling names with QIDs eliminates homonyms and noise, opening the door to complex questions—for example: how many artists have worked with augmented reality in Brazilian public institutions since 2018, or which artworks use software as material and are held in Latin American collections. SPARQL queries answer these questions in a reproducible, auditable way. You don’t need to be a programmer: there are visual editors, ready-made examples, and communities to help. Structured data lets you move from one-off cases to patterns, from anecdote to demonstrable trend.
For curatorial work, the impact is methodological. The curatorial cut stops being a rhetorical statement and becomes a verifiable trail. You can see which fields were used, which filters were applied, and which sources support each inclusion. This favours living catalogues that remain up to date even after an exhibition opens. It also strengthens mediation. Audiences can understand how the selection was made and how it engages with systemic gaps. A curatorial practice grounded in Wikidata can diagnose asymmetries—say, Euro-Atlantic concentration, a predominance of a few languages, or the absence of peripheral collectives—and act on them by inviting under-represented artists, requesting open metadata, or proposing descriptors that match current practices. Rather than treating the graph as a mirror of the world, we treat it as a co-authored text in which intervention is part of the research.
Digital art adds particular layers. Many works depend on code, frameworks, software versions, and spatial configurations. When these elements become explicit properties, documentation stops being vague. It supports conservation, re-staging, and teaching. You can record the programming language, code repository, technical dependencies, and the version used in installation. That reduces information loss when a piece needs updating and makes it easier to mount exhibitions that require specific infrastructure. Pedagogically, students see that materiality and concept travel together. A responsive installation isn’t merely “interactive”: it involves sensors, protocols, and a version history worth documenting.
This tool comes with limits and responsibilities. Wikidata reflects where contributors are most active. Countries, languages, and institutions with greater technical capacity tend to appear in more detail. That bias doesn’t disqualify the tool, but it does call for critical reading. In classrooms and studios, it’s worth turning the recognition of bias into practical activity: identify gaps, correct imprecise classifications, add reliable sources, and translate labels into other languages. Ethical care is part of the method too: respect image rights, avoid sensitive data, cite the origin of each statement, and log discussions in the edit history so others can audit or replicate the work.
Basic glossary:
- QIDs — Unique identifiers for Wikidata items. Each item—an artist, work, exhibition, technique, or institution—receives a code beginning with “Q” followed by a number (for example, Q42, Q5593). The code is stable, language-independent, and serves as an unambiguous reference when there are homonyms or spelling variants. In practice, a QID is the item’s unique ID within the graph: you use QIDs to reconcile spreadsheets in OpenRefine, write SPARQL queries, link data across repositories, and cite an item precisely regardless of its label in English, Portuguese, etc. Items have QIDs; properties have PIDs (such as P170 for “creator”); lexemes have LIDs—keeping those straight avoids confusion. When duplicate items are merged, one QID redirects to the other, preserving history and links. If you have the QID, you hold the key to the item’s statements, sources, and connections in Wikidata. “QID” simply means “Q identifier.” In Wikidata:
– Items start with Q (e.g., Q42, Q5593) → “QID.”
– Properties start with P (e.g., P170 for “creator”).
– Lexemes start with L (with components using S and F, etc.).
In short, “QID” = the item’s identifier (“Q + number”), not an acronym spelled out as words. - SPARQL — A query language for interrogating structured data in RDF graphs. It lets you select, filter, group, and combine information connected by relationships. It’s similar in spirit to SQL, but designed for graphs, using triple patterns—subject, predicate, object—to find matches. It supports joins, filters, property paths to traverse multiple edges in sequence, federated queries across multiple sources, and returns results in tabular formats like CSV or JSON. In Wikidata, SPARQL is what turns the graph into practical answers. With it you can count artists who took part in certain exhibitions, map works by technique and period, find coverage gaps by language or country, and generate tables, maps, and networks directly from published, referenced data.
- Wikidata — A collaborative, multilingual, open knowledge base maintained by the Wikimedia Foundation, where information about entities (people, works, places, concepts) is stored as structured data in a semantic graph. Each entity is an “item” identified by a QID (Q + number) and described by property–value pairs (properties have PIDs), accompanied by references and qualifiers. Content is licensed under CC0 for broad reuse and accessed via the web interface, APIs, and SPARQL queries through the Wikidata Query Service. In art research, it serves as a hub for reconciliation and discovery that connects GLAM collections, catalogues, and repositories, making comparison, mapping, and source audit more transparent and reproducible.