Dr. Michael Martin

Dr. Michael Martin
Depiction of Dr. Michael Martin
Address Work
Goerdelerring 9, Room 101a, 04109 Leipzig
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+49-341-229037-51
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+49-341-229037-99

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Dr. Michael Martin is a postdoctoral researcher at the University of Leipzig and heads the research group Emergent Semantics, which is part of the AKSW network. His research interests include Engineering of Web Applications using Semantic Web Technologies, Data Science and Management of Linked (Open) Data and Open Data. Michael is currently involved in several research projects, such as LEDS - Linked Enterprise Data Services (funded by the German Federal Ministry of Education and Research - BmBF) and the EU funded project SlideWiki. In the past years, he was amongst others involved in the multi-national Research and Software development projects LOD2, LATC, LE4SW, OntoWiki, CubeViz and the Open Data Portal as well as the Digital Agenda Scoreboard of the European Commission. Furthermore, he has (co-)authored more than 40 peer-reviewed publications at international journals, conferences and workshops and holds lectures as well as seminars at the University of Leipzig in the research areas E-Business, Software Engineering and Software Management.

Current Projects

  • 5. Leipziger Semantic Web Tag (LSWT2013) – Von Big Data zu Smart Data
  • 6. Leipziger Semantic Web Tag (LSWT2018) – Linked Enterprise Data Services
  • 7. Leipziger Semantic Web Tag (LSWT2019) – Linking Research and Enterprise
  • CSVImport – Representing multi-dimensional statistical data as RDF using the RDF Data Cube Vocabulary
  • CubeViz – The RDF DataCube Browser.
  • Erfurt – PHP5 / Zend based Semantic Web API for Social Semantic Software
  • FTS – RDF Version of the Financial Transparency System of the European Commission
  • GeoKnow – Making the Web an Exploratory for Geospatial Knowledge
  • LIMBO – Linked Data Services for Mobility
  • LODStats – a statement-stream-based approach for gathering comprehensive statistics about RDF datasets
  • OntoWiki – a tool providing support for agile, distributed knowledge engineering scenarios
  • Query Cache – Adaptive SPARQL Query Cache
  • ReDD-Observatory – Using the Web of Data for Evaluating the Research-Disease Disparity
  • SlideWiki – revolutionise how educational materials can be authored, shared and reused
  • SlideWiki.eu – Large-scale pilots for collaborative OpenCourseWare authoring, multiplatform delivery and Learning Analytics.
  • SparqlAnalytics – I Know What You Did Last Query

Past Projects

  • Digital Agenda Scoreboard – A Statistical Anatomy of Europe's way into the Information Age
  • LATC – LOD Around-the-Clock
  • LE4SW – Regional Technology Platform of Social Semantic Collaboration
  • LEDS – Linked Enterprise Data Services
  • OntoWiki.eu – Social Semantic Collaboration for EKM, E-Learning & E-Tourism

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News

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"

DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released ( 2019-09-24T22:41:46+02:00 by Simon Bin)

2019-09-24T22:41:46+02:00 by Simon Bin

Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released"

DBpedia Day @ SEMANTiCS 2019 ( 2019-08-01T10:35:05+02:00 Sandra Bartsch)

2019-08-01T10:35:05+02:00 Sandra Bartsch

 We are happy to announce that SEMANTiCS 2019 will host the 14th DBpedia Community Meeting at the last day of the conference on September 12, 2019. Read more about "DBpedia Day @ SEMANTiCS 2019"

LDK conference @ University of Leipzig ( 2019-03-22T09:21:41+01:00 by Julia Holze)

2019-03-22T09:21:41+01:00 by Julia Holze

With the advent of digital technologies, an ever-increasing amount of language data is now available across various application areas and industry sectors, thus making language data more and more valuable. Read more about "LDK conference @ University of Leipzig"