TF8 Big Data

 Led by Francisco Cid (ITI – ES), Marten Van Sinderen (University of Twente – NL) and Daniel Saez Domingo (ITI – ES)


Missions & Objectivesbig-data-blog-header-image

Enterprise networks are becoming complex, tigthtly connected, and very dynamic, in response to changing demands, fluctuating markets, and low margins. These networks highly rely on data interoperability networks, which in several cases need to deal with large volumes of data (Volume), coming from different sources and formats (Variety), and/or characterised by massive and continuous data flows (Velocity). The intersection of these three dimensions (Volume, Variety, and Velocity, among others) at large scales is challenging, and thus within active research  in the Big Data field.

The objective of this task force is to deal with the challenges of Big Data (Volume, Variety, Velocity) in the field of enterprise data interoperability and data integration. Powerful tools can be applied to collect, store, analyse, process, and visualize huge amounts of data, in order to improve resource allocation, quality of service, maintenance, marketing, decision making, … along a global value chain and create a significant advantage for European Industry. Data coming from different sources and from all the actors in the value chain will influence the decision making process. Interoperability and integration of datasets are essential for a wide adoption and impact within and across sectors.

This task force expects to gather knowledge and experience from different fields, join efforts, and lead the advance of data interoperability and integration techniques in line with current and emerging industry needs. That is, dealing with large volumes of data, from different sources and different formats, and requiring fast processing times. This would require an effective and efficient management of interacting components from different systems, the automation of data transformations, processing and analysis, as well as driving the adoption of standardized data bridging models for different industry sectors to enable an easy and rapid connection and processing. These data interoperability and integration layer will provide a base for the application of analysis techniques to increase efficiency and sustainability along a value chain.