Abstract

After years of research and development, standards and technologies for semantic data are sufficiently mature to be used as the foundation of novel data science projects that employ semantic technologies in various application domains such as bio-informatics, materials science, criminal intelligence, and social science. Typically, such projects are carried out by domain experts who have a conceptual understanding of semantic technologies but lack the expertise to choose and to employ existing data management solutions for the semantic data in their project. For such experts, including domain-focused data scientists, project coordinators, and project engineers, our tutorial delivers a practitioner's guide to semantic data management. We discuss the following important aspects of semantic data management and demonstrate how to address these aspects in practice by using mature, production-ready tools: i) storing and querying semantic data; ii) understanding, iii) searching, and iv) visualizing the data; v) automated reasoning; vi) integrating external data and knowledge; and vii) cleaning the data.

Material

• Slides of Part 1 (Introduction)
• Slides of Part 2 (Storage and Querying)
• Slides of Part 3 (Understanding the Data)
• Slides of Part 4 (Full-Text Search in the Data)
• Slides of Part 5 (Visualizing the Data)
• Slides of Part 6 (Automated Reasoning)
• Slides of Part 7 (Data Cleaning)
• Slides of Part 8 (Integrating)

Presenters

Olaf Hartig is an Assistant Professor at the Department of Computer and Information Science of Linköping University. Olaf holds a Ph.D. in Computer Science from the Humboldt-Universität zu Berlin, Germany. His research interests are related to various areas of data management with a particular focus on Web data, graph data, and semantic data management. He has published 1 book, 2 book chapters, 5 journal articles, and 15 research papers in top international conferences in the fields of the Semantic Web and Databases. Moreover, Olaf presented 8 tutorials at such conferences including WWW 2010, WWW 2013, WWW 2017, and ICDE 2014; and he was lecturer at the 2011 Indian-Summer School on Linked Data.

Olivier Curé is a tenured associate professor in computer science at the University of Paris-Est Marne la Vallée (UPEM) in France. He obtained his Ph.D. in Artificial Intelligence at the Université Paris V, France. His research interests are data and knowledge base management systems, semantic information and reasoning. He has published 1 book ("RDF Database Systems: Triples Storage and SPARQL Query Processing", Morgan Kaufmann, 2014), 4 book chapters, 12 journal papers, and over 60 research papers in international, peer-reviewed conferences on Databases, Semantic Web, and Big Data.