Visual Queries in Distributed Knowledge Graphs Visual and multi-modal rich data queries over standalone and distributed knowledge graphs.
Visual Tool	We implement our ideas in ViziQuer tool (follow this link also for previous research and wider context explanation).
News	To be announced ..
Project aims	The project aims to develop and validate a method for creation and management of visual and multi-modal rich data queries over standalone and distributed knowledge graphs by data professionals and lay users. The vision of the project is to provide an option for seamless creating of rich visual queries, allowing query scaffolding from visual data schema exploration or from natural language texts and providing context-aware meaningful auto-completion over the data sets of practical size and heterogeneity (including DBPedia, Wikidata and large custom data sets), with support for distributed queries. The methods for automated and incremental data schema extraction from the variety of the real-world data sets shall support the vision.
Project data	Research project lzp-2021/1-0389, financed by Latvian Science Council. Time frame: January 2022 - December 2024 Implemented at Institute of Mathematics and Computer Science, University of Latvia. Contact project leader Dr. Kārlis Čerāns
Project team	Prof. Kārlis Čerāns Dr. Lelde Lāce Dr. Uldis Bojārs Jūlija Ovčiņņikova Mikus Grasmanis We work at Institute of Mathematics and Computer Science, University of Latvia
Open source code	Check the branch dss-based-schemata from Viziquer repository in GitHub for the visual tool version that works with a separate data schema server. The data shape server (serving the names for auto-completion) is in its own repository on GitHub. Check also ViziQuer main page for open source data schema retrieval options.