Authors:
Christof Bornhoevd
;
Robert Kubis
;
Wolfgang Lehner
;
Hannes Voigt
and
Horst Werner
Affiliation:
LLC, United States
Keyword(s):
Schema-flexible Database Management System, Graph Database, Flexible Information Management.
Related
Ontology
Subjects/Areas/Topics:
Architectural Concepts
;
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cardiovascular Technologies
;
Collaboration and e-Services
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Data Management and Quality
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
e-Business
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Information Integration
;
Information Systems Analysis and Specification
;
Integration/Interoperability
;
Knowledge Engineering and Ontology Development
;
Knowledge Management
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Semi-Structured and Unstructured Data
;
Society, e-Business and e-Government
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
Data management is not limited anymore to towering data silos full of perfectly structured, well integrated data. Today, we need to process and make sense of data from diverse sources (public and on-premise), in different application contexts, with different schemas, and with varying degrees of structure and quality. Because of the necessity to define a rigid data schema upfront, fixed-schema database systems are not a good fit for these new scenarios. However, schema is still essential to give data meaning and to process data purposefully. In this paper, we describe a schema-flexible database system that combines a flexible data model with a powerful data query, analysis, and manipulation language that provides both required schema information and the flexibility required for modern information processing and decision support.