Data integration systems and bibliometrics

Probabilistic Data Integration Systems

Current data integration techniques are successful at managing well-defined and wellunderstood data integration tasks, but do not cope well with uncertainty. However, the amount of uncertain data is growing with the number and variety of data sources being integrated, both in traditional data integration tasks s.a. enterprise data integration, and in next generation integration problems, s.a. c...

Data Quality Evaluation in Data Integration Systems

IPAS Implementation Issues: Data and Systems Integration

Data Integration and Interoperability of Systems and Data

The role of the GSDI Association, in essence, is to facilitate better global outcomes through utilisation of geographic information and spatial data infrastructures (SDIs). This role directly complements the proposal to establish a United Nations Committee on Global Geographic Information Management (UNCGGIM). The GSDI Association's view of the changes now taking place in the geographic informa...

Analyzing and Evaluating Data Freshness in Data Integration Systems

Data freshness has been identified as one of the most important data quality attributes in information systems. This importance increases particularly in the context of systems composed of a large set of autonomous data sources where integrating data having different freshness may lead to semantic problems. This paper addresses the problem of evaluating data freshness in a data integration syst...