Navigating the Maze of Wikidata Query Logs

Abstract

This paper provides an in-depth and diversified analysis of the Wikidata query logs, recently made publicly available. Although the usage of Wikidata queries has been the object of recent studies, our analysis of the query traffic reveals interesting and unforeseen findings concerning the usage, types of recursion, and the shape classification of complex recursive queries. Wikidata specific features combined with recursion let us identify a significant subset of the entire corpus that can be used by the community for further assessment. We considered and analyzed the queries across many different dimensions, such as the robotic and organic queries, the presence/absence of constants along with the correctly executed and timed out queries. A further investigation that we pursue in this paper is to find, given a query, a number of queries structurally similar to the given query. We provide a thorough characterization of the queries in terms of their expressive power, their topological structure and shape, along with a deeper understanding of the usage of recursion in these logs. We make the code for the analysis available as open source. CCS CONCEPTS • Information systems → Query log analysis; Query languages for non-relational engines; World Wide Web; Information retrieval query processing; • Theory of computation → Database query languages (principles).

Approximate Querying on Property Graphs

“…While not as general as SPARQL, our fragment already captures more than 60% of the property paths found in practice in SPARQL query logs [8]. Moreover, it captures property path queries, as found in the large Wikidata corpus studied in [9]. Indeed, almost all the property paths in the considered logs contain Kleenestar expressions over single labels.…”

SHARQL: Shape Analysis of Recursive SPARQL Queries

“…Property path visualization and related types. Property paths are extremely common in Wikidata query logs [4]. However, they can consist of complex expressions and can therefore quickly overcrowd the visualization.…”

“…As large SPARQL query logs are being disclosed to the community, more and more queries are becoming available for advanced analytics [2,4,7]. Examples are the recently publicly available Wikidata query logs and the DBpedia logs which can be obtained from OpenLink Software.…”

“…In contrast, Web-based query endpoints are making this knowledge acquisition possible and desirable for guiding the research community in many directions, such as graph query evaluation and optimization, graph query language design, and graph database tuning. In this demo, we focus on the presentation of massive SPARQL query logs, amounting to a corpus of roughly 0.8B queries from disparate data sources (including DBpedia and Wikidata as the most significant subsets of the corpus), as result of our previous work in the area [2,4]. SHARQL builds on DARQL [3], a system deployed on top of a relational DBMS (PostgreSQL 10) with a web-based front end alongside a batch processing system (for loading and analyzing query logs, writing to files) and initially conceived for DBpedia queries.…”

Finite Controllability for Ontology-Mediated Query Answering of CRPQ

“…• Conjunctive regular path queries (CRPQ) possibly with inverse navigation roles (C2RPQ) and unions thereof (UC2RPQ) in the role of Q. These are basic extensions of CQs and UCQs (the most studied query languages in OMQA) with a simple form of recursion, and an integral part of the W3C standard for querying RDF data (SPARQL 1.1) and often popular for querying ontologies, as revealed by recent studies (Malyshev et al 2018;Bonifati, Martens, and Timm 2019).…”