The Digital Earth as knowledge engine

Abstract

The Digital Earth [13] aims at developing a digital representation of the planet. It is motivated by the need for integrating and interlinking vast geo-referenced, multi-thematic, and multi-perspective knowledge archives that cut through domain boundaries. Complex scientific questions cannot be answered from within one domain alone but span over multiple scientific disciplines. For instance, studying disease dynamics for prediction and policy making requires data and models from a diverse body of science ranging from medical science and epidemiology over geography and economics to mining the social Web. The näıve assumption that such problems can simply be addressed by more data with a higher spatial, temporal, and thematic resolution fails as long as this more on data is not supported by more knowledge on how to combine and interpret the data. This makes semantic interoperability a core research topic of data-intensive science. While the Digital Earth vision includes processing services, it is, at its very core, a data archive and infrastructure. We propose to redefine the Digital Earth as a knowledge engine and discuss what the Semantic Web has to offer in this context and to Big Data in general. ’Considerable data regarding the environment are available through the myriad of remote-sensing programs, however, this data is not directly compatible with the models. It has been observed that scientists and engineers spend more than 60% of their time just preparing the data for model input or data-model intercomparison. This is an inefficient use of the precious time of NASA scientists and engineers.’ [28] Beyond the General-Purpose Web Initially, the Semantic Web [3,17] was proposed as a successor of the document Web that makes the stored content understandable to software agents and enables them to extract, process, and combine this information. At this time, the Web was still dominated by authoritative sources and different from the social read-write Web that we know today. During these early days, data on the Web was assumed to be relatively stable, authoritative, and fit for a given, predefined purpose. Thus, in analogy to catalogs, it was assumed that data providers would invest in creating intelligent metadata to improve retrieval and reuse. This made semantic technologies capable of handling sophisticated ontologies a promising research vision. These days, however, the Web is based on fundamentally different principles. The volume of data is growing at a higher rate than our capacities for long-term archiving. New data is added at a velocity, surpassing our ability to consume it. Instead of a limited number of data providers and formats, data is contributed by a myriad of human users, software agents, and technical sensors in a variety of different multi-media formats. While these three V ’s are characteristic for the omnipresent Big Data, we argue that a fourth V addressing the value of the created data is relevant as well. Finally, the general-purpose Web in itself is losing ground with traffic constantly declining since more than 10 years and the increasing success of single-purpose apps [1]. 1570-0844/12/$27.50 c © 2012 – IOS Press and the authors. All rights reserved

DOI: 10.3233/SW-2012-0070

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Cite this paper

@article{Janowicz2012TheDE, title={The Digital Earth as knowledge engine}, author={Krzysztof Janowicz and Pascal Hitzler}, journal={Semantic Web}, year={2012}, volume={3}, pages={213-221} }