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The correspondence between the terminology used for querying and the one used in content objects to be retrieved, is a crucial prerequisite for effective retrieval technology. However, as terminology is evolving over time, a growing gap opens up between older documents in (long-term) archives and the active language used for querying such archives. Thus, technologies for detecting and systematically handling terminology evolution are required to ensure "semantic" accessibility of (Web) archive content on the long run. As a starting point for dealing with terminology evolution this paper formalizes the problem and discusses issues, first ideas and relevant technologies.
The scientific innovation process embraces the steps from problem definition through the development and evaluation of innovative solutions to their successful exploitation. The challenges imposed by this process can be answered by the creation of a powerful and flexible next-generation e-Science infrastructure, which exploits leading edge information and knowledge technologies and enables a comprehensive and intelligent means of supporting this process. This paper describes our vision of a Knowledge-based eScience infrastructure, which is based on the results of an in-depth study of the researchers requirements. Furthermore, it introduces the Fraunhofer e-Science Cockpit as a first implementation of our vision.
Web archives created by the Internet Archive (IA) (https://archive.org), national libraries and other archiving services contain large amounts of information collected for a time period of over twenty years. These archives constitute a valuable source for research in many disciplines, including the digital humanities and the historical sciences by offering a unique possibility to look into past events and their representation on the Web.
Most Web archive services aim to capture the entire Web (IA) or national top-level domains and are therefore broad in their scope, diverse regarding the topics they contain and the time intervals they cover. Due to the large size and the broad scope it is difficult for interested researchers to locate relevant information in the archives as search facilities are very limited. Many users are more interested in studying smaller and topically coherent event-centric collections of documents contained in a Web archive [1,2]. Such collections can reflect specific events such as elections, or natural disasters, e.g. the Fukushima nuclear disaster (2011) or the German federal elections.