Knowledge and its articulations are strongly influenced by diversity in, e.g., cultural backgrounds, schools of thought, geographical contexts. Judgements, assessments and opinions, which play a crucial role in many areas of democratic societies, including politics and economics, reflect this diversity in perspective and goals. For the information on the Web (including, e.g., news and blogs) diversity - implied by the ever increasing multitude of information providers - is the reason for diverging viewpoints and conflicts. Time and evolution add a further dimension making diversity an intrinsic and unavoidable property of knowledge.
The vision inspiring LivingKnowledge is to consider diversity an asset and to make it traceable, understandable and exploitable, with the goal to improve navigation and search in very large multimodal datasets (e.g., the Web itself). LivingKnowledge will study the effect of diversity and time on opinions and bias, a topic with high potential for social and economic exploitation. We envisage a future where search and navigation tools (e.g., search engines) will automatically classify and organize opinions and bias (about, e.g., global warming or the Olympic games in China) and, therefore, will produce more insightful, better organized, easier-to-understand output.
LivingKnowledge employs interdisciplinary competences from, e.g., philosophy of science, cognitive science, library science and semiotics. The proposed solution is based on the foundational notions of context and its ability to localize meaning, and the notion of facet, as from library science, and its ability to organize knowledge as a set of interoperable components (i.e., facets). The project will construct a very large testbed, integrating many years of Web history and value-added knowledge, state-of-the-art search technology and the results of the project. The testbed will be made available for experimentation, dissemination, and exploitation.
The overall goal of the LivingKnowledge project is to bring a new quality into search and knowledge management technology, which makes search results more concise, complete and contextualised. On a provisional basis, we take as referring to the process of compacting knowledge into digestible elements, completeness as meaning the provision of comprehensive knowledge that reflects the inherent diversity of the data, and contextualisation as indicating everything that allows us to understand and interpret this diversity.