Funded Projects

EIS is currently funded with the following regional, national and European research projects


The Web not only gives rise to new forms of crime, it also enables new technology for crime investigation. Suspects leave traces on the Web, items are being sold and bought on the Web, and a wealth of public open data about organizations and places is available on the Web. LiDaKrA aims at a holistic approach to extract, network and fuse crime-relevant information from public and private sources such as: the Web in general, the Social Web (social networks, blogs or wikis), Deep Web (eCommerce databases such as ebay or Amazon Marketplace), Dark Web (informations from the Tor network), Data Web (open data such as DBpedia or GeoNames). The technical components will be implemented in an integrated platform and will be evaluated in concrete use cases with multiple stakeholders from crime investigation authorities. Read more about LiDaKrA


OSCOSS is concerned with Opening Scholarly Communication in the Social Sciences. Read more about OSCOSS


SeReCo (Semantics, Coordination and Reasoning) is a German-French doctoral college. Its scientific purpose of SeReCo is to explore the spectrum of technologies related to semantics, reasoning and coordination in distributed and open environments (such as the Web). Read more about SeReCo

Community Projects

EIS is currently launched the following Community Projects


This semantic wiki at OpenResearch aims at making the world of science more visible and accessible. Information about scientific events, research projects, publishers, journals etc. is scattered around on the Web. For researchers (especially young ones without decades of experience) it is often difficult to find the relevant venues, people or tools. Also research is increasingly dynamic and multi-disciplinary, so the boundaries between communities blur and new research directions emerge. With this semantic Wiki, we aim to make information about scientific events, research groups, tools, journals etc. more accessible. OpenResearch is not restricted to any field of science. Read more about OpenResearch


A vocabulary representing the Supply Chain Organizations Reference (SCOR). Read more about SCORvoc

Vocabulary Projects

EIS is currently launched the following Vocabulary Projects


The Skills and Recruitment Ontology (SARO) is a domain ontology representing occupations, skills and recruitment. It is modelled by considering several similar context models, but is mainly inspired by the European Skills, Competences, Qualifications and Occupations ontology (ESCO) and The ontology is structured along four dimensions: job posts, skills, qualifications and users. Read more about SARO


A vocabulary representing the Supply Chain Organizations Reference (SCOR). Read more about SCORvoc

Incubator Projects

EIS Incubator projects


iRap is an RDF update propagation framework that propagates only interesting parts of an update from the source dataset to the target dataset. iRap filters interesting parts of changesets from the source dataset based on graph-pattern-based interest expressions registered by a target dataset user. Read more about iRap

OpenCourseWare observatory

OpenCourseWare observatory is a currently a survey to assess quality of Open CourseWare. A number of selected courses from different OCW systems is assessed based on predefined metrics. The objectives of this study is to determine the quality of OCW which helps to: identify renowned OCW creators and publishers, diagnose the strengths and weaknesses of particular OCW, evaluate the employed creation and curation methods as well as predict the future performance of OCW. Read more about OpenCourseWare observatory

Open Source Projects

Open Source Projects

Demand and Supply as a Service

The data value chain is an important concept that involves identifying the various activities and roles in manufacturing a non-tangible data product. In our information society, data increasingly becomes a commodity and the basis for many products and services. With this portal we strive to balance the demand and supply of data, with the aim of generating a new Economic Data Ecosystem that has the Web of Data as its core. Through the Demand and Supply as a Service (DSAAS), we enable data producers to advertise the data they produce, and thus data consumers can search for the data they require. The data consumers can also publish a request for specific data, if this is not already provided by a producer. In this way, we aim to enable and encourage data re-use and exploitation, providing the means to generate value through a data product. Read more about Demand and Supply as a Service


A major obstacle to the wider use of semantic technology is the perceived complexity of RDF data by stakeholders who are not familiar with the Linked Data paradigm, or are otherwise unaware of the dataset's underlying schema. In order to help overcome this barrier, we introduce the concept of RDF softening, which aims to preserve the semantic richness of the data model while catering for simplified and workable views of the data. We address the softening objective with the ExConQuer Framework, which facilitates the publication and consumption of RDF in a variety of generic formats. Through the Query Builder Tool, we aim to lower the entry barrier for any stakeholder requiring the use of Linked Open Data. We enable the user to explore existing Linked Data and generate a SPARQL query, then proceed to download and convert the results in a number of formats. Through the PAM Tool, the user is able to explore existing queries executed on various datasets through filters, and re-load them on the Query Builder tool to edit or re-run them. Read more about ExConQuer


Luzzu is a Quality Assessment Framework that provides an integrated platform that: (1) assesses Linked Data quality using a library of generic and user-provided domain specific quality metrics in a scalable manner; (2) provides queryable quality metadata on the assessed datasets; (3) assembles detailed quality reports on assessed datasets. Furthermore, we aim to create an infrastructure that:

  • can be easily extended by users by creating their custom and domain-specific pluggable metrics, either by employing a novel declarative quality metric specification language or conventional imperative plugins;
  • employs a comprehensive ontology framework for representing and exchanging all quality related information in the assessment workflow;
  • implements quality-driven dataset ranking algorithms facilit- ating use-case driven discovery and retrieval.
Read more about Luzzu


MULDER (Molecule-based Query Decomposition for RDF) is an adaptive federated query engine for federation of Web access interfaces. MULDER describes Web interfaces in terms of RDF molecule templates, i.e., abstract RDF graphs that characterize the accessible data. Moreover, MULDER utilizes molecule templates for selecting relevant Web interfaces, query decomposition, and execution. As a result, MULDER exploits the query features of SPARQL endpoints and Linked Data Fragments for obtaining complete answers for federated queries of arbitrary complexity. Read more about MULDER


Ontario is a Semantic Data Lake capable of storing and querying heterogeneous data (e.g., csv, xml, rdf) in its original format. Ontario uses the RDF molecules approach as a logical representation of the heterogeneous data. MULDER federated query engine leverages RDF molecules metadata to efficiently perform query decomposition, source selection, query planning, and query execution. Read more about Ontario


SemAnn allows you to semantically annotate (using RDF triples) text in PDFs. These annotations are then used for recommending similar PDF documents that the reader might find relevant. Read more about SemAnn


Vocabularies typically reflect a consensus among experts in a certain application domain. They are thus implemented in collaboration of domain experts and knowledge engineers. Particularly the presence of domain experts with little technical background requires a low-threshold vocabulary engineering methodology. This methodology should be im- plementable without dependencies on complex software components, it should provide collaborators with comprehensible feedback on syntax and semantics errors in a tight loop, and it should give access to a human- readable presentation of the vocabulary. Inspired by agile software and content development methodologies, we define the VoCol methodology to address these requirements. We implemented a prototype based on a loose coupling of validation and documentation generation components on top of a standard Git repository. All of these components, even the repository engine, can be exchanged with little effort. By evaluating the usefulness of error feedback of different tools in the realistic setting of an emerging mobility vocabulary we prove, however, that our choice of the crucial validation component is workable. Read more about VoCol

Alumni Projects

In the EIS group, we currently have a number of Master and Lab students. Some of these projects have reached a stable state, but are currently not actively maintained and further developed.