Der Wachstumskern LEDS veröffentlicht regelmäßig wissenschaftliche Papers, welche im Rahmen des Forschungsprojektes Linked Enterprise Data Services entstehen. Auf der SEMANTiCS 2016 werden wir zusätzlich zu den Akzeptierten Papers im Research Track weitere fünf Poster und Demos präsentieren, welche von den beteiligten Hochschulen Universität Leipzig und der Technischen Universität Chemnitz eingereicht wurden. Alle Publikationen sind auch in dem Bereich „Publikationen“ verfügbar.
„Quit Diff: Calculating the Delta Between RDF Datasets under Version Control“ Natanael Arndt und Norman Radtke
Distributed actors working on a common RDF dataset regularly encounter the issue to compare the status of one graph with another or generally to synchronize copies of a dataset. A versioning system helps to synchronize the copies of a dataset, combined with a difference calculation system it is also possible to compare versions in a log and to determine, in which version a certain statement was introduced or removed. In this demo we present Quit Diff, a tool to compare versions of a Git versioned quad store, while it is also applicable to simple unversioned RDF datasets. We are following an approach to abstract from differences on a syntactical level to differences on the level of the RDF data model, while we leave further semantic interpretation on the schema and instance level to specialized applications. Quit Diff can generate patches in various output formats and can be directly integrated in the distributed version control system Git which provides a foundation for a comprehensive co-evolution work flow on RDF datasets.
„Protecting Enterprise Linked Data - Enforcing scalable authorization on SPARQL queries“ Jörg Unbehauen, Marvin Frommhold und Michael Martin
With the adoption of the Linked Data Paradigm in the enterprise context effective measures for securing sensitive data are in higher demand than ever before. Exemplary, integrating enterprise systems containing millions of assets and fine granular access control rules with large public background knowledge graphs leads to both a high number of triples and a high number of access control axioms, which traditional methods struggle to process. Therefore, we introduce novel approaches for enforcing access control on SPARQL queries and evaluate their implementation using an extension of the Berlin SPARQL Benchmark. Additionally, we discuss strengths and weaknesses of the respective approaches and outline future work.
„Towards Reputation-Aware Expert Finding with Linked Open Data“ Sebastian Heil, Michael Krug, Stefan Wild und Martin Gaedke
Distributed social networks allow creating new work patterns, addressing the workforce of a company as crowd. Here, finding suitable workers for specific functions is important for work quality, but largely relies on human assessment. In web-scale environments this assessment exceeds human capability. Linked open data has proven to be successful in providing semantic descriptions and discoverability of distributed resources. Hence, we leverage linked open data, so that each worker can have a semantic profile based on WebID and reference co-workers, skills, projects, etc. To recommend suitable experts for a given task, supporting systems are required, which use this profile data. In this paper, we extend our previous work on CRAWL towards reputation-aware expert finding in distributed social networks. We outline three major aspects – Endorsements, Achievements and Meta Reputation – to achieve reputation awareness and report on our progress, showcase open challenges and present a roadmap for future work.
„OntoWiki 1.0: 10 Years of Development - What’s New in OntoWiki“ Philipp Frischmuth, Natanael Arndt und Michael Martin
In this demonstration (with supportive poster) we present the semantic data wiki OntoWiki, which was released in version 1.0 just recently. We focus on the changes introduced to the tool in the latest release and showcase the generic data wiki, improvements we made with regard to the documentation as well as three success stories where OntoWiki was adapted and deployed.
„Adding Semantics to Model-Driven Software Development: A Practical Experience Report“ Andreas Nareike, Jörg Unbehauen und Johannes Schmidt
Model-driven software development tools and methods allow fast bootstrapping of software applications and can improve their quality. Using a domain model and adhering to a framework specific set of conventions leverages the generation of objects and services in both frontend and backend and an accompanying database schema. However, rapid application development frameworks like JHipster or Spring Roo lack a deep integration of semantic technologies which allow exploration and analytics beyond the operations defined as services. A post-deployment integration of semantic technologies into an existing application can be cumbersome, as knowledge about the domain model can get lost and additional components require deployment. We therefore enrich UML domain models in order to generate database mappings and additional ontologies for exposing both the conceptual model and instance data as RDF. Ultimately, this allows using the expressive power of SPARQL for analytic queries while still using established development frameworks for implementing enterprise applications.