Authors:
Kurt Englmeier
1
and
Hugo Román
2
Affiliations:
1
Schmalkalden University of Applied Science, Germany
;
2
Soluciones S.A., Chile
Keyword(s):
Data Discovery, Information Integration, Language Pattern, Natural Language, Data Governance, Simplicity, Information Extraction, Metadata.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Communication, Collaboration and Information Sharing
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Metadata and Structured Documents
;
Symbolic Systems
Abstract:
People dealing with information in IT-based environments tend to develop a data-driven mindset that constitutes shallow engineering knowledge and turns them into tech-savvy information consumers. We argue that these consumers can manage data discovery and information sharing on their own without explicit support from IT. We argue furthermore that user-driven discovery can even be mandatory when mainstream discovery concentrates on facts appearing massively in data and bypasses the little and unspectacular facts consumers expect to discover in their data. Finally we argue that tech-savvy users can depict blueprints of these facts using a pattern language that combines the user’s work jargon with a simple syntax. We present a working solution for such an easy-to-learn pattern language for self-service data discovery and information sharing (DISL). The language has been developed in an industry-academia partnership and was applied in the area of assessment in the real estate sector in C
hile. A prototypical discovery service operating on DISL gathers information from contracts and related certificates and prepares the discovered facts for information sharing.
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