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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/7A6AD56D-57AE-4F14-B65C-A5945E37DA25 | ||
| Year | 2022 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | G. Antoniou, K. Atkinson, G. Baryannis, S. Batsakis, L. di Caro, G. Governatori, L. Robaldo, G. Siragusa, and I. Tachmazidis, “Explainable reasoning with legal big data: a layered framework,” J. Appl. Log.- IfCoLoG, vol. 9, no. 4, pp. 1155-1170, July 2022. https://www.collegepublications.co.uk/ifcolog/?00056 | ||
| Appears in Collections |
Knowledge representation and reasoning in the legal domain has primarily focused on case studies where knowledge and data can fit in main memory. However, this assumption no longer applies in the era of big data, where large amounts of data are generated daily. This paper discusses new opportunities and challenges that emerge in relation to reasoning with legal big data and the concepts of volume, velocity, variety and veracity. A four-layer legal big data framework is proposed to manage the complete lifecycle of legal big data from sourcing, processing and storage, to reasoning, analysis and consumption. Within each layer, a number of relevant future research directions are also identified, which can facilitate the realisation of knowledge-rich legal big data solutions.
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