Details
| Original language | English |
|---|---|
| Title of host publication | Digital Libraries for Open Knowledge |
| Subtitle of host publication | 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings |
| Editors | Antoine Doucet, Antoine Isaac, Koraljka Golub, Trond Aalberg, Adam Jatowt |
| Place of Publication | Cham |
| Publisher | Springer Verlag |
| Pages | 200-214 |
| Number of pages | 15 |
| ISBN (electronic) | 9783030307608 |
| ISBN (print) | 9783030307592 |
| Publication status | Published - 30 Aug 2019 |
| Event | 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019 - Oslo, Norway Duration: 9 Sept 2019 → 12 Sept 2019 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11799 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Keywords
- EVENTSKG dataset, Query builder, Scientific events, SPARQL endpoint, User Interaction
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Proceedings. ed. / Antoine Doucet; Antoine Isaac; Koraljka Golub; Trond Aalberg; Adam Jatowt. 1. ed. Cham: Springer Verlag, 2019. p. 200-214 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11799 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Human-Friendly Query Generation Frontend for a Scientific Events Knowledge Graph
AU - Fathalla, Said
AU - Lange, Christoph
AU - Auer, Sören
N1 - Funding information: This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536).
PY - 2019/8/30
Y1 - 2019/8/30
N2 - Recently, semantic data have become more distributed. Available datasets should serve non-technical as well as technical audience. This is also the case with our EVENTSKG dataset, a comprehensive knowledge graph about scientific events, which serves the entire scientific and library community. A common way to query such data is via SPARQL queries. Non-technical users, however, have difficulties with writing SPARQL queries, because it is a time-consuming and error-prone task, and it requires some expert knowledge. This opens the way to natural language interfaces to tackle this problem by making semantic data more accessible to a wider audience, i.e., not restricted to experts. In this work, we present SPARQL-AG, a human-Friendly front-end that automatically generates and executes SPARQL queries for querying EVENTSKG. SPARQL-AG helps potential semantic data consumers, including non-experts and experts, by generating SPARQL queries, ranging from simple to complex ones, using an interactive web interface. The eminent feature of SPARQL-AG is that users neither need to know the schema of the knowledge graph being queried nor to learn the SPARQL syntax, as SPARQL-AG offers them a familiar and intuitive interface for query generation and execution. It maintains separate clients to query three public SPARQL endpoints when asking for particular entities. The service is publicly available online and has been extensively tested.
AB - Recently, semantic data have become more distributed. Available datasets should serve non-technical as well as technical audience. This is also the case with our EVENTSKG dataset, a comprehensive knowledge graph about scientific events, which serves the entire scientific and library community. A common way to query such data is via SPARQL queries. Non-technical users, however, have difficulties with writing SPARQL queries, because it is a time-consuming and error-prone task, and it requires some expert knowledge. This opens the way to natural language interfaces to tackle this problem by making semantic data more accessible to a wider audience, i.e., not restricted to experts. In this work, we present SPARQL-AG, a human-Friendly front-end that automatically generates and executes SPARQL queries for querying EVENTSKG. SPARQL-AG helps potential semantic data consumers, including non-experts and experts, by generating SPARQL queries, ranging from simple to complex ones, using an interactive web interface. The eminent feature of SPARQL-AG is that users neither need to know the schema of the knowledge graph being queried nor to learn the SPARQL syntax, as SPARQL-AG offers them a familiar and intuitive interface for query generation and execution. It maintains separate clients to query three public SPARQL endpoints when asking for particular entities. The service is publicly available online and has been extensively tested.
KW - EVENTSKG dataset
KW - Query builder
KW - Scientific events
KW - SPARQL endpoint
KW - User Interaction
U2 - 10.1007/978-3-030-30760-8_18
DO - 10.1007/978-3-030-30760-8_18
M3 - Conference contribution
AN - SCOPUS:85072873693
SN - 9783030307592
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 200
EP - 214
BT - Digital Libraries for Open Knowledge
A2 - Doucet, Antoine
A2 - Isaac, Antoine
A2 - Golub, Koraljka
A2 - Aalberg, Trond
A2 - Jatowt, Adam
PB - Springer Verlag
CY - Cham
T2 - 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019
Y2 - 9 September 2019 through 12 September 2019
ER -