@inbook{2ff44b72f0af4be49b8ca7c547e5ddef,
title = "Workshop C2 Report - Big Data Interoperability for Enterprises",
abstract = "Cost-efficient use of big data by enterprises is challenging. Data from multiple heterogeneous sources are typically combined. This data needs to be handled by various interacting components in different systems for automated transformation, filtering, processing and analysis, as well as for representation according to adopted industry standards and interpretation according to prevailing industry models. The derived information may be shared with many other systems, and applied for many purposes. Hence, big data interoperability and integration is a major concern that must be addressed at different levels and along the (extended) value chain. The Big Data Interoperability for Enterprises Workshop comprises eight paper presentations covering data interoperability problems and solutions at different points in the value chain and for different industrial sectors and application areas.",
keywords = "Analysis, Big data interoperability, METIS-319463, IR-102547, Data wrangling, EWI-27319, Prediction, Enterprise interoperability, Multi-level modelling, SCS-Services",
author = "{van Sinderen}, {Marten J.} and Iacob, {Maria Eugenia}",
note = "eemcs-eprint-27319 ",
year = "2016",
month = sep,
language = "Undefined",
isbn = "9781847040442",
publisher = "International Society for Technology in Education",
pages = "268--269",
editor = "Martin Zelm and Guy Doumeingts and Mendonca, {Joao Pedro}",
booktitle = "Enterprise Interoperability in the Digitized and Networked Factory of the Future",
}