A new way to manage web data
The internet has revolutionised access to the huge amount of information available on a global scale. However, gathering and managing all this information requires advanced software that is fast, efficient and reliable. The EU-funded WEBDAM (Foundations of web data management) project developed a new model for web data management that facilitates the development of the web in a better way, enhancing its functionality and performance. To illustrate, an individual may have information on different home and office devices, as well as on different platforms, systems and social networks. To manage the diversity of data effectively, the project envisioned a distributed knowledge base for both data and metadata, including access control and localisation information, under one holistic environment. This enables users to overcome complex web data management that would otherwise require in-depth expertise, thanks to the automatic reasoning of the inference engine of the knowledge base. To achieve its aims, the project team developed an innovative rule-based language dubbed Webdamlog that integrates the proposed concept of delegation, enabling peers to exchange knowledge and distribute computation. It then built a system that exploits Webdamlog and assessed its performance. The project's work also involved overcoming imprecise and uncertain data from the web through probabilistic databases, particularly XML. The team then tackled the issue of organising how various systems can work together, particularly in sequencing tasks. This relied on the use of business artefacts to document the intrinsic nature of workflows shared by collaborative systems. Armed with these developments and progress, WEBDAM placed significant emphasis on dissemination and education. In 2009 it published a textbook on web data management aimed at advanced undergraduate or graduate level and made it available free of charge online. In 2002, the project also published a book in French titled Data Sciences, From First Order Logic to the Web, also available to download online at no cost. The project's results and publications contribute to a new way of collating, processing and exploiting information available on the web.
Keywords
WEBDAM, web data management, inference engine, probabilistic databases, business artefacts
