Internet and Web have created the worldwide platform for ‘e-innovation’: novel forms of exploiting digital information and conducting associated business. The rise and fall of so many e-commerce initiatives are testimony to the fact that the general idea is simple, but reality is much harder than expected. Many technological and socio-economic challenges are therefore still awaiting real scientific solutions. The User Centric Data Science (UCDS) program aims at a better understanding of e-innovation that integrates both technology and business considerations.
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The User Centric Data Science Section takes part in the SIKS Onderzoek School
The key research themes of the User Centric Data Science Section are:
- Ontology engineering and Semantic Web
Definition and standardization of the basic ontology languages, libraries, and smart web services to realize the vision of a future Semantic Web.
- Intelligent systems and services
Designing and experimenting with ontology-based IS applications, innovative e-services, and business processes enabled by knowledge-intensive system methods, in several industry sectors and knowledge domains.
- Networked business modelling and eBusiness
Understanding and influencing the businessmarket logics that determine the critical economic success factors and social adoption of smart web-based innovations in networked enterprise constellations.
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Ontology engineering and the Semantic Web
The current World Wide Web is an interesting and useful, but also passive and unstructured storage place of information resources. This problem becomes even more pressing with the further scaling up of the Web. The vision of the Semantic Web is to transform the Web from a passive information store into a proactive service facility for its users. This is done by equipping it with information management services, based on semantic and knowledge-based methods, that let the Web act — in the eyes of its users — as understanding the contents and meaning (rather than just the syntax) of the many information resources it contains. The User Centric Data Science program contributes to key components for the Semantic Web: generic semantic infrastructure (such as web ontology languages and libraries) and associated generic smart web services (such as semantic search and browsing, knowledge processing and ontology management services).
Intelligent systems and services
Though challenging and interesting, this is a necessary but certainly not sufficient condition to realize the full potential of the Web. In addition to the Web becoming smarter, it is also becoming more universal in that it not only connects computers, but essentially any device. This is variously referred to as ‘universal connectivity’, ‘ubiquitous computing’ and ‘ambient intelligence’ (e.g., by the European Commission). Distributed Web applications are just one step in this direction. Basically all equipment, including personal audio and video, telecoms and even home appliances such as heaters, will become integrated into the Internet and Web. This enables a broad spectrum of new e-services: digital media entertainment and education, smart buildings, decentralized large-scale control, e-government, e-health, and other industrial and customer services. An important research question therefore is: What innovative domain, business, and user/customer applications can be created in view of the future Web? How should they be constructed? In collaboration with different industry branches, User Centric Data Science works at innovative concepts and prototypes in knowledge management, e-business, and agent-based e-services.
Networked business modelling and eBusiness
All these envisaged innovations are technically highly challenging, but they will also require different behaviours from their users as well as from the businesses delivering these e-services. This generates further crucial questions. What are the benefits? What is the business case? Why would businesses, markets and individuals be willing to adopt such innovations? In other words, the (Semantic) Web should lead to the creation of value webs. In our view, academic research in Information Science cannot be content with only answering the technology-related questions: it must deal with the corresponding socio-economic aspects as well, in an integrated interdisciplinary fashion. Thus, in addition to new technology the User Centric Data Science program develops scientifically grounded business analysis tools that help understand and design the intertwined business-technology aspects of the next wave of intelligent information processing.