- Data Science
- Semantic web
- Linked data
As our world continues to digitalise, the scope and diversity of data exchange is growing. At the same time, data sharing is becoming more complex. The rapid introduction of big data, Internet of Things (IoT), machine learning, artificial intelligence (AI) and other data-driven innovations only increases the complexity and challenge of keeping IT systems manageable.
In recent years, work has been carried out in various sectors on message standards that can achieve more efficient cooperation. For example, the sector organisation SETU (Stichting Elektronische Transacties Uitzendbranche) has been developing reporting standards, which have a predefined structure, for the temporary employment sector for the past fifteen years. With these SETU standards, temporary employment agencies can link their customers electronically. As a result, the integration of IT systems of temporary employment agencies and customers has become faster, more straightforward and reusable.
However, there is a need for a more flexible way of solving IT integration issues within the temporary employment sector. This is why a broad consortium of temporary employment agencies, software suppliers, SETU and TNO is working on the development of new generation data standards for the flexible staffing industry. In addition to SETU and TNO, Adecco, Akyla, Driessen, Easyflex Services, FlexForceMonkey, Manpower, Pivoton, Randstad, Solid Online, Timing and USG People are participating in this TKI project 'FIT with ontologies'. Within the project, so-called semantic technology is used to share data and develop a future-proof infrastructure.
The consortium has developed a proof of concept that demonstrates the operation and applicability of semantic data sharing technology. Linked data technology can connect data and give it meaning. Semantic standards concern the unity of language when using data and messages. The project thus provides a common language in the form of the SETU ontology that allows the sharing of a demand-driven composition of data, unlike current message standards. The upshot is that data-driven analyses, decisions and process control are more reliable. This results in a flexible way of solving integration issues. In addition, it is essential that the data is self-descriptive, so that other systems can interpret the data without human intervention. An example of this is compliance with GDPR regulations.
Through this project, the temporary employment sector has become one of the first in the Netherlands to use semantic technology to share data and thus develop a future-proof infrastructure. Other sectors, such as healthcare and the smart industry, also face similar challenges where semantic technology can offer a solution.
Would you like to know more or collaborate with us? Please contact Michiel Stornebrink.