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Efficient use of data and data technology

Data are flooding almost every sector of the Belgian economy. With the emergence of the Internet of Things (IoT) these increasing volumes of data are being collected in a wide range of fields. Against this backdrop, a growing number of methods were developed in recent years to extract new insights from these data. Sirris's Data Innovation experts provide companies with information and support regarding the efficient use of data and data technology.

Gathering and making use of these data demands innovation with regard to analysis and interpretation. Therefore, more and more innovation is based on exploiting and interpreting the abundance of available data.

Although it is generally recognised that data-driven innovation has huge potential, effective methods to exploit such data still pose the main challenge facing us. Sirris plays a role in addressing this by applying acquired knowledge from industrial research with a view to creating a more efficient, healthier and happier society with stronger, more competitive companies.

Projects in 2016

WITH-ME - helping overweight people lose weight through a digital coaching platform

The WITH-ME project aimed to build a digital coaching platform to help overweight people with a high cardiovascular risk to acquire and maintain a healthier lifestyle. The coaching platform was tested through four pilots, one of which in the context of helping overweight people with a cardiovascular risk to reduce weight. Sirris's main contribution involved the extraction of relevant information from both subjective data directly provided by coaches and coachees, and objective data supplied by sensors. WITH-ME was an ARTEMIS/ECSEL R&D project, involving 19 companies and research institutions from four European countries, which ended in September 2016.

EluciDATA Starter Kits help companies to start to innovate with data

While the opportunities created by data are manifold and recognised in most companies, their potential is still underutilised. Therefore, two years ago, Sirris initiated the EluciDATA project, focusing on accelerating data innovation. The goal of this project is to support companies in exploiting their data by analysing their collective needs and challenges and investigating solutions using existing technology.


In collaboration with the EluciDATA user group, a number of concrete industrial use cases have been identified in various domains. For each of these use cases, a starter kit is being developed, to illustrate the potential of data innovation for a specific use case, thereby allowing companies to embark on data innovation more quickly.

In December 2016, there was another development in this regard with the launch of the EluciDATA Starter Kit Portal.

Moments of inspiration

Data innovation dealt with in mastercourse

As part of the EluciDATA project, Sirris launched a new cycle of training sessions in autumn 2016. The objective of this new cycle is to cover the different aspects of data innovation with a view to raising awareness of data science's valuable contribution to industrial innovation. The different sessions offer a pragmatic and industry-oriented introduction to data-driven innovation and discuss a specific topic from the data science process. The first session (which took place in 2016) was entitled 'The business perspective on innovating with data' and focused on the business aspect of data innovation. This first session was a real success with 13 participants from different industrial sectors (automotive, energy…). Further training sessions will be organised in 2017.

Using data to optimise fleets of machines

Increasingly, machines are being equipped with sensors and connected to the Internet, making it possible to gather data on a central platform. Therefore, Sirris’s Data Innovation team organised a dedicated seminar on 24 October 2016 as a forum for testimonials from industrial partners with which Sirris is participating in several research projects on the topic of operational optimisation of fleets and portfolios of industrial assets. The presentations focused on the opportunities and the challenges of using data acquired from a fleet of machines with a view to optimising their operation and maintenance, as a lot of companies operate a number of machines that have a similar, almost identical behaviour in terms of internal operation, application and usage. By comparing and combining patterns in the operation of similar machines, it is possible to derive insights into normal and anomalous behaviour across the entire fleet of machines. The analysis of these data can also help service and maintenance personnel to achieve more optimized operation and efficient maintenance planning.