An architecture for establishing legal semantic workflows in the context of integrated law enforcement
Stumptner, Markus (University of South Australia)
Mayer, Wolfgang (University of South Australia)
Grossmann, Georg (University of South Australia)
Liu, Jixue (University of South Australia)
Li, Wenhao (University of South Australia)
Casanovas, Pompeu (Universitat Autònoma de Barcelona)
De Koker, Louis (La Trobe University)
Mendelson, Danuta (Deakin University)
Watts, David (La Trobe University)
Bainbridge, Bridget (La Trobe University)

Publicació:	Springer 2018
Descripció:	15 pag.
Resum:	Traditionally the integration of data from multiple sources is done on an ad-hoc basis for each to "silos" that prevent sharing data across different agencies or tasks, and is unable to cope with the modern environment, where workflows, tasks, and priorities frequently change. Operating within the Data to Decision Cooperative Research Centre (D2D CRC), the authors are currently involved in the Integrated Law Enforcement Project, which has the goal of developing a federated data platform that will enable the execution of integrated analytics on data accessed from different external and internal sources, thereby providing effective support to an investigator or analyst working to evaluate evidence and manage lines of inquiries in the investigation. Technical solutions should also operate ethically, in compliance with the law, and subject to good governance principles.
Ajuts:	Ministerio de Economía y Competitividad DER2012-39492
Nota:	A previous version of this paper was presented at the Third Workshop on Legal Knowledge and the Semantic Web (LK&SW-2016), EKAW-2016, November 19th, Bologna, Italy
Drets:	Tots els drets reservats.
Llengua:	Anglès
Col·lecció:	Lecture Notes in Computer Science book series (LNCS) ; 10791
Document:	Capítol de llibre ; Versió acceptada per publicar
Matèria:	Legal natural language processing of legal texts ; Law enforcement investigation management
Publicat a:	AI Approaches to the Complexity of Legal Systems. AICOL 2015, AICOL 2016, AICOL 2016, AICOL 2017, AICOL 2017, 2018, p. 124-139, ISBN 9783030001780

DOI: 10.1007/978-3-030-00178-0_8

Postprint 15 p, 504.2 KB

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