SINTEF is Scandinavia’s largest independent research organization. SINTEF is multidisciplinary, with international top-level expertise in a wide range of technological and scientific disciplines, including areas such as ICT, medicine, and the social sciences. SINTEF’s company vision is “technology for a better society”, and it is an important aspect of SINTEF’s societal role to contribute to the creation of more jobs. SINTEF acts as an incubator, commercialising technologies through the establishment of new companies. SINTEF is represented in proDataMarket by Information and Communication Technology (SINTEF ICT) through the department for Networked Systems and Services (NSS).
Role in the project: SINTEF is the project leader of proDataMarket, and in addition serves as a technology provider in the project. SINTEF’s technical focus is on the technical infrastructure of the proDataMarket platform related to data management technologies, in particular data publishing and access, helping organizations with cost-effective solutions for (linked open) data management. Our goal is to promote standardisation with mechanisms for defining structure and semantics of data, as well as improve the interoperability and transparency among data publishers and consumers through leveraging the linked data format. Technically, we are constructing a software framework that consists of a frontend and a set of platform services that support reusable data cleaning and reconfiguration based on pluggable static, dynamic or streaming input in various formats (e.g., relational databases, CSV files, WMS/WFS services, etc.). Outputs will be published on the proDataMarket platform and available to end users and other publishers through a secured set of platform services such as SPARQL query endpoints and RESTful APIs. This framework is meant to provide automation for significantly reducing the manual effort involved in the highly laborious process of data retrieval and aggregation.
In proDataMarket, SINTEF reuses and extends its data reconfiguration solutions from the DaPaaS project. In particular, we plan to further develop the Grafterizer tool for data cleaning and linked data mapping of tabular inputs.