Johannes Frey

Johannes Frey
Address Work
Goerdelerring 9, Room Institut fuer Angewandte Informatik (InfAI), 2. OG, AKSW/KILT Office, 04109 Leipzig
Email Office
Phone Work
+49-341-229037-92
Fax Work
+49-341-229037-99

Homepage

About

Johannes studied computer science at Leipzig University with focus on database technologies, computer networks & distributed systems and Semantic Web. During his bachelors he worked as a student assistant at the business information systems department for the “Leipzig Data” project and developed PHP-based semantic solutions for publishing and visualizing RDF data. In his bachelor thesis he created a WordPress plugin for the humanities to author, manage, publish and visualize RDF data within WordPress. In the beginning of 2015 he joined the Knowledge Integration and Linked Data Technologies competence center (KILT) of the Institute of Applied Informatics (InfAI) as graduate assistant. Within this work he supported the creation of an open industry knowledge graph in the “Smart Data Web” research project. In his master thesis he evaluated and benchmarked metadata representation models in RDF stores and wrote Java-based tools for flexible metadata storage and querying.

Since August 2017 he is employed as research assistant of Leipzig University in the KILT group.

His primary research interests in the scope of the Semantic Web are:

  • Data integration & knowledge fusion
  • Metadata(management) in knowledge graphs
  • RDF store benchmarking
  • Scalable & distributed data processing architectures

Reviews & PC Memberships

  • reviewer for ISWC 2016 Poster & Demo
  • reviewer for ICWE 2017
  • reviewer for EACL 2017
  • reviewer for ESWC 2017
  • PC member of Poster & Demo track of Semantics 2017

Awards

Workshops & Talks

  • Talk about knowledge fusion and id management for DBpedia in "Interlinking and Metadata" Session of semantics17 workshop "A Reliable Linked Data ecosystem for media"

Teaching

  • practical course of software engineering lecture 2016
  • practical course of software engineering lecture 2017

Current Projects

  • DBpediaQuerying Wikipedia like a Semantic Database
  • NLP2RDFConverting NLP tool output to RDF
  • Smart Data WebCreation of an industry knowledge base for the German industry.

Publications

Filters

by (Editors: ) [BibTex of ]

News

DBpedia Tutorial @ Knowledge Graph Conference 2021 ( 2021-04-09T13:20:50+02:00 by Julia Holze)

2021-04-09T13:20:50+02:00 by Julia Holze

On May 4, 2021 we will organize a tutorial at the Knowledge Graph Conference (KGC) 2021. Read more about "DBpedia Tutorial @ Knowledge Graph Conference 2021"

DBpedia @ Google Summer of Code program 2021 ( 2021-03-15T09:41:22+01:00 by Julia Holze)

2021-03-15T09:41:22+01:00 by Julia Holze

DBpedia, one of InfAI’s community projects, will participate in the Google Summer of Code (GSoC) program for the 10th time. The GsoC program has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code program 2021"

DBpedia’s New Website ( 2021-01-28T12:42:40+01:00 by Julia Holze)

2021-01-28T12:42:40+01:00 by Julia Holze

We are proud to announce the completion of the new DBpedia website. Read more about "DBpedia’s New Website"

SANSA 0.7.1 (Semantic Analytics Stack) Released ( 2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann)

2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann

We are happy to announce SANSA 0.7.1 – the seventh release of the Scalable Semantic Analytics Stack. SANSA employs distributed computing via Apache Spark and Flink in order to allow scalable machine learning, inference and querying capabilities for large knowledge graphs. Read more about "SANSA 0.7.1 (Semantic Analytics Stack) Released"

More Complete Resultset Retrieval from Large Heterogeneous RDF Sources ( 2019-12-05T15:46:09+01:00 Andre Valdestilhas)

2019-12-05T15:46:09+01:00 Andre Valdestilhas

Over recent years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laundromat and SPARQL endpoints provide access to hundreds of thousands of RDF datasets, representing billions of facts. Read more about "More Complete Resultset Retrieval from Large Heterogeneous RDF Sources"