LEDS Linked Enterprise Data Services

Innovative Regional Growth Core in the Area of Leipzig

 

The innovative growth core project Linked Enterprise Data Services (LEDS) is aiming at developing, establishing and merchandising the next generation of semantic, interlinked data driven applications and services based on the Linked Data paradigm. In order to achieve this goal, LEDS develops a technology platform, which will include competences, methods and concrete technological building blocks. The project is directly in line with the development of Web 3.0 and with the 2020 strategy for eGovernment. 

 

Conference Participation

LEDS project partners are part of the SEMANTiCS2016 organisation team and will give research and industry talks during the conference. LEDS representatives are members of the programme committees and are nominated as Poster Chair and as Sponsoring Chair. In addition to that, we have chosen the SEMANTiCS2016 as our first public outcome event.

Topics


In the research and industry programme we will focus on the following topics:

  • Versioning and Co-Evolution of Linked Data
  • Linking and Knowledge Extraction in the Context of Linked Enterprise Data
  • Lighting Talks of current and upcoming tools and research in this field
  • Open eGovernment Data
  • Semantic eCommerce
  • Natural Language Processing
  • Corporate Memory and Big Data / Linked Data Integration.

Talks


This includes but is not limited to the following talks:

  • Jörg Unbehauen and Michael Martin: “Executing SPARQL Queries over Mapped Document Stores with SparqlMap-M”
  • Michael Krug, Martin Seidel, Frank Burian and Martin Gaedke: “KESeDa: Knowledge Extraction from Heterogeneous Semi-Structured Data Sources”
  • Natanael Arndt, Norman Radtke and Michael Martin: “Distributed Collaboration on RDF Datasets Using Git: Towards the Quit Store”
  • Marvin Frommhold, Ruben Navarro Piris, Natanael Arndt, Sebastian Tramp, Niklas Petersen and Michael Martin: “Towards Versioning of Arbitrary RDF Data” 

Posters

       
  Stand No. Title Authors
  6 Adding Semantics to Model Driven ApplicationDevelopment with CVtec and SparqlMap Jörg Unbehauen, Andreas Nareike and Johannes Schmidt
  18 Towards Reputation-Aware Expert Finding with Linked Open Data Sebastian Heil, Stefan Wild, Michael Krug and Martin Gaedke
  26 Using DevOps principles to continuously monitor RDF data quality Roy Meissner and Kurt Junghanns
  28 Enforcing scalable authorization on SPARQL queries Joerg Unbehauen, Marvin Frommhold and Michael Martin
  32 OntoWiki 1.0: 10 Years of Development - What's New in OntoWiki Philipp Frischmuth, Natanael Arndt and Michael Martin
  34 Quit Diff: Calculating the Delta Between RDF Datasets under Version Control Natanael Arndt and Norman Radtke

 

Cross-cutting project topics

The project is funded by the German Federal Ministry of Education and Research. The three-year project started in 2015 and is split into six work areas which tackle the most crucial aspects of semantic applications: speed, capacity, scalability, complexity and interactivity.

In detail the LEDS partners push the limits in regards to:

  • Enterprise Linked Data & Data Integration
  • Semantic Information Management
  • Management of background knowledge with regard to co-evolution, curation and orchestration
  • Data quality assurance
  • Data coherence
  • Knowledge Discovery & Intelligent Search
  • Scalable search on Linked Data
  • Knowledge extraction from unstructured, semi-structured and other non-RDF data sources
  • Business Models, Governance & Data Strategies
  • eCommerce and application of Linked Data in online shop systems
  • Interlinking public, commercial and administrative data

The following research topics announced for the SEMANTiCS2016 programme are covered by the LEDS project:

  • Corporate Knowledge Graphs
  • Economics of Data, Data Services and Data Ecosystems 
  • Big Data & Text Analytics
  • Data Portals & Knowledge Visualization
  • Semantic Information Management
  • Smart Connectivity, Networking & Interlinking
  • Smart Data & Semantics in IoT
  • Industry & Engineering
  • Public Administration
  • Publishing, Marketing & Advertising

 

 

Partners

LEDS is a joint research project addressing the evolution of classic enterprise IT infrastructure to semantically linked data services. The research partners are the Leipzig University and Technical University Chemnitz as well as the semantic technology providers Netresearch, Ontos, brox IT-Solutions, Lecos and eccenca. 

brox IT-Solutions GmbH

Leipzig University

Ontos GmbH

TU Chemnitz

Netresearch GmbH & Co. KG

Lecos GmbH

eccenca GmbH

 

Supported by

 

Speakers


 

 

 

LEDS Linked Enterprise Data Services

Distributed Collaboration on RDF Datasets Using Git: Towards the Quit Store

Collaboration is one of the most important topics regarding the evolution of the World Wide Web and thus also for the Web of Data.

LEDS Linked Enterprise Data Services

Executing SPARQL Queries over Mapped Document Stores with SparqlMap-M

With the increasing adoption of NoSQL data base systems like MongoDB or CouchDB more and more applications store structured data according to a non-relational, document oriented model.

LEDS Linked Enterprise Data Services

KESeDa: Knowledge Extraction from Heterogeneous Semi-Structured Data Sources

A large part of the free knowledge existing on the Web is available as heterogeneous, semi-structured data, which is only weakly interlinked and in general does not include any semantic classi fication.

LEDS Linked Enterprise Data Services

Towards Versioning of Arbitrary RDF Data

Coherent and consistent tracking of provenance data and in particular update history information is a crucial building block for any serious information system architecture.

Robert Isele
Head of Data Integration Unit
eccenca GmbH

LEDS Linked Enterprise Data Services

eccenca CorporateMemory - Semantically integrated Enterprise Data Lakes

Large corporations have to master vast amounts of heterogeneous data in order to stay competitive.

Christian Opitz
Head of innovation management
Netresearch GmbH & Co. KG

LEDS Linked Enterprise Data Services

Semantic E-Commerce - Use Cases in Enterprise Web Applications

Semantic technologies offer a wide range of benefits in an increasing number of application fields such as data management, business intelligence, machine learning etc.

LEDS Linked Enterprise Data Services

Streaming-based Text Mining using Deep Learning and Semantics

Since the most of the world’s data is unstructured, the mining of required information from text was, is and will be essential.

CEO of eccenca GmbH and brox IT-Solutions GmbH
eccenca GmbH

LEDS Linked Enterprise Data Services

LEDS Linked Enterprise Data Services

The innovative growth core project Linked Enterprise Data Services (LEDS) is aiming at developing, establishing and merchandising the next generation of semantic, interlinked data driven applications and services based on the Linked Data paradigm.

LEDS Linked Enterprise Data Services

Enterprise Knowledge Graphs

In the last years, Big Data as well as Linked Data technologies gained wide attention. The primary goal of Big Data technologies is the high-performance analysis of large-scale data (volume and velocity), while Linked Data aims at integrating distributed, heterogeneous data (Variety).

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