Goals

CODE will address the following research objectives:

  1. Data Enrichment & Integration: Our goal is to develop services for enriching and linking academic publications into the LOD cloud. The focus will be on workflows and methods that enable domain experts to develop rule bases and statistical enrichment & integration models, share those models with other users and easily apply them on large amounts of research publications. As a result, domain experts will be able to extract facts from research papers, integrate them with existing facts and sell/offer them to the community.
  2. Data Querying, Aggregation and Provenance: Our goal is to develop decentralized querying and statistical aggregation services for structured queries over Linked Data infrastructures. The focus will be on federated querying and statistical aggregation/summarization mechanism (e.g. mean, sum, variance over triples) and on integrating trust and provenance information in Linked Data. As a result, domain experts and analysts will be enabled to search existing Linked Open Data repositories, integrate the results into their analysis and link it to unstructured information.
  3. Visual Linked Data Analysis: Our goal is to develop web-based visual analysis and correlation services for decentralized Linked Data repositories. The focus will be on HTML5 based, ontology driven user interface elements exploiting the self-describing nature of RDF data in order to be easily adaptable to new scenarios. As a result, visual analysis will enable consumers and analysts to analyse and present the underlying data in an effective and intuitive manner. The resulting usage data can be utilized as feedback information to improve enrichment, integration and querying, yielding to an overall improved quality of service.
  4. Socio-Economic Mechanisms: Our goal is to investigate potential web based marketplace ecosystems, targeted roles for such ecosystems, underlying trust and reputation mechanisms for establishing value creation chains as well as possible revenue streams. The focus will be on social, content and usage based trust assessment, new revenue models and roles involved in a data marketplace. As a result, CODE’s research will enable a sustainable, commercial market place around Linked Science Data.

CODE shall advance today’s data marketplaces. As we will show, this advancement requires us to go beyond-state-of-the art on

  • technical and algorithmic aspects, where we have to develop new semantic enrichment, integration and web-based visual analytics methods
  • socio-economic aspects, where we have to research roles to be supported in data marketplaces, possible revenue sharing models and methods to capture trust and provenance information.