WS29 LEDSPLaY17

The biggest challenge for data-driven enterprise and e-commerce applications in the next decade is the transition from the integration of static and homogeneously structured data to the dynamic integration of heterogeneous, distributed, and semantically structured data (e.g., along value chains). Many companies, especially in the Industry 4.0 context, are increasingly focusing on the transformation and interconnection of existing data using semantic approaches (RDF).

Semantically annotated data can easily be connected to information from other domains, which would be expensive or unaffordable for companies that follow a classical data generation approach. By integrating and interconnecting several knowledge sources, companies automatically benefit from the dynamic growth and continuous improvement of different data sources. As a consequence, the quality of their own products and services as well as cross-company value chains can be significantly improved. The advantages of the linked-data approach against conventional data integration techniques are, among other things, an increased data model flexibility, better scalability on a large number of data sources, and richer context information through relationship effects. This significantly improves the technological basis and quality of many existing applications. Entirely new enterprise services and applications are thus possible, especially in the E-Commerce and E-Government application domain.

The LEDSPLaY17 workshop addresses these challenges and wants to bring together scientists, practitioners and domain experts to discuss current issues and new research approaches in the area of Linked Enterprise Data Management. We would like to focus on data and quality management, versioning, evolution and provenance, as well as on linking and data fusion of company data. Trends and ongoing technological developments can be presented, as well as current questions and problems from science and practice can be discussed with a broad specialist audience. We are also very interested in actual use cases as well as possible solutions in the areas of public administration and enterprise data management.

The workshop will focus on:

• Data/Information Quality and Policies
• Formal Models for Data Quality
• Data Quality Measurement and Metrics
• Evolution of Data Quality
• Versioning and Co-Evolution of Linked Data
• Provenance Tracking and Exploitation
• Link and Knowledge Extraction
• Corporate Memory and Big Data/Linked Data Integration
• Data Lakes
• Data Curation
• Smart Data Management and Data Fusion
• Corporate Data and Enterprise Application Development
• Requirements and Business Use Cases for Linked Data
• Open eGovernment Data
• Semantic eCommerce

Natanael Arndt; Toralf Kirsten; André Langer; Michael Martin; Thomas Riechert; Leander Seige;

Workshop opening and Impulse Talk

Sebastian TrampRoy Meissner; Marcus Kastner
A mapping approach for configuration management tools to close the gap between two worlds and to regain trust

Natanael Arndt; Norman Radtke
A Method for Distributed and Collaborative Curation of RDF Datasets Utilizing the QuitStack

Jörg Unbehauen; Michael Martin
SPARQL Update queries over R2RML mapped data sources

Coffee break

Session 1.2 – Modelle / Models (11:00 – 12:30)

Jan-Patrick Weiß; Jens Rauch; Jens Hüsers; Jan-David Liebe; Frank Teuteberg; Ursula Hübner
Entwicklung eines Datenmodells für ein umfassendes Forschungsdatenmanagement zur flexiblen Analyse longitudinaler Daten

Thomas Riechert; Edgard Marx
Anwendung des Heloise Common Research Modells in den Digital Humanities und Vorstellung des Projektes Professorale Karrieremuster der Frühen Neuzeit

Toralf Kirsten; Alexander Kiel; Jonas Wagner; Mathias Rühle; Markus Löffler
Selecting, Packaging, and Granting Access for Sharing Study Data

Lunch break

Session 2.1 – Search and Discovery Applications (14:00 – 15:30)

André Langer; Michael Krug; Luis Moreno; Martin Gaedke
Utilizing Linked Data Structures for Social-aware Search Applications

Konrad Abicht; Georges Alkhouri; Natanael Arndt; Roy Meissner; Michael Martin
CubeViz.js: A Lightweight Framework for Discovering and Visualizing RDF Data Cubes

Andreas Varwig; Friedemann Kammler; Oliver Thomas
Smarte Datenintegration durch Benchmarking-as-a-Service – Vorschlag eines Vorgehensmodells zur Entwicklung eines unternehmensübergreifenden Informationssystems mittels Data Envelopment Analysis

Konrad Abicht; Simeon Ackermann; Michael Martin
Discover Barrier-free Accessible Locations with the Location Navigator

Coffee break

Session 2.2 – Prozesse / Processes (16:00 – 17:30)

Marius Politze; Bernd Decker; Thomas Eifert
pSTAIX – A Process-Aware Architecture to Support Research Processes

Andreas Henkel; Danny Ammon; Kutaiba Saleh
Austausch medizinischer Forschungsdaten auf der Basis von IHE: Motivation, Modell, Erfahrungen

Markus Löffler; Hans Binder; Toralf Kirsten; Frank Meineke
Der Leipzig Health Atlas

Discussion: What have Scientific Data Management and Linked Enterprise Data Services in common?
Services · Prozesse · Informationssysteme · Linking · Datenqualität · Provenance