SEMANTiCS 2017 is an international event on Linked Data and the Semantic Web where business users, vendors and academia meet. Our members have actively participated in 13th SEMANTiCS 2017, which took place in Amsterdam, Nederland, Sept 11-14.
We are very pleased to announce that we got 7 papers accepted at SEMANTiCS 2017 for presentation at the main conference. Additionally, we also had 4 Posters and 2 Demo papers accepted at the same.
Furthermore, adding a feather to our hat, our colleague Harsh Thakkar (@harsh9t) secured a Best Research and Innovation Paper Award for his work “Trying Not to Die Benchmarking – Orchestrating RDF and Graph Data Management Solution Benchmarks Using LITMUS” (Github Org., Website, Docker, PDF).
Abstract. Knowledge graphs, usually modelled via RDF or property graphs, have gained importance over the past decade. In order to decide which Data Management Solution (DMS) performs best for specific query loads over a knowledge graph, it is required to perform benchmarks. Benchmarking is an extremely tedious task demanding repetitive manual effort, therefore it is advantageous to automate the whole process. However, there is currently no benchmarking framework which supports benchmarking and comparing diverse DMSs for both RDF and property graph DMS. To this end, we introduce, the rst working prototype of, LITMUS which provides this functionality as well as ne-grained environment configuration options, a comprehensive set of DMS and CPU-specific key performance indicators and a quick analytical support via custom visualization (i.e. plots) for the benchmarked DMSs.
The audience displayed enthusiasm during the presentation appreciating the work and asking questions regarding the future of his work and possible synergy with industrial partners/projects.
— SDA Research (@SDA_Research) September 14, 2017
Furthermore, an interested mass also indulged in the Poster & Demo session for their first-hand experience with LITMUS.
— iKeeda (@Harsh9t) September 12, 2017
Among the other presentations, our colleagues presented the following research papers:
- Ontology-guided Job Market Demand Analysis: A Cross-Sectional Study for the Data Science field. by Elisa Margareth Sibarani, Simon Scerri, Camilo Morales, Sören Auer and Diego Collarana.
Elisa Margareth Sibarani presented her work on Ontology-guided Job Market Demand Analysis.
- Semantic Similarity based Clustering of License Excerpts for Improved End-User Interpretation by Najmeh Mousavi Nejad, Simon Scerri, Sören Auer.
Najmeh Mousavi Nejad presented her work on Semantic Similarity based Clustering of License Excerpts for Improved End-User Interpretation.
- SMJoin: A Multi-way Join Operator for SPARQL Queries by Mikhail Galkin, Kemele M. Endris, Maribel Acosta, Diego Collarana, Maria-Esther Vidal, Sören Auer.
Mikhail Galkin presented his work on introducing a concept and practical approach for multi-way joins applicable in SPARQL query engines. Multi-way joins refer to operators of n-arity, i.e., supporting more than two inputs. A set of optimizations were proposed to increase the performance of a multi-way operator. The audience was particularly interested in experimental results, the impact of query selectivity and operator optimizations.
- Benchmarking Faceted Browsing Capabilities of Triplestores by Henning Petzka, Claus Stadler, Georgios Katsimpras, Bastian Haarmann and Jens Lehmann
Henning Petzka presented his work on the Benchmarking of Faceted Browsing.
- Matching Natural Language Relations to Knowledge Graph Properties for Question Answering. by Isaiah Onando Mulang’, Kuldeep Singh, Fabrizio Orlandi.
Isaiah Onando Mulang’ presented his work on Matching Natural Language Relations to Knowledge Graph Properties for Question Answering. A major feedback from the audience was that we could evaluate this work in a fully integrated QA System which is planned for the second iteration of our evaluation.
- IDOL: Comprehensive & Complete LOD Insights by Ciro Baron Neto, Dimitris Kontokostas, Amit Kirschenbaum, Gustavo Publio, Diego Esteves, and Sebastian Hellmann.
The presents challenges and technical barriers at identifying and linking the whole linked open data cloud using a probabilistic data structure called Bloom Filter. The audience was most interested in questions related to the problem of cross-dataset error correction as well as the generation of further analytics and heuristics metadata.
SEMANTiCS was a great venue to meet the community, create new connections, talk about current research challenges, share ideas and settle new collaborations. We look forward to the next SEMANTiCS conference.