The development of the Internet in recent years has made it possible and useful to access
many different information systems anywhere in the world to obtain information. While there …

Big data management for information centralization (ie making data of interest findable) and
integration (ie making related data connectable) in health research is a defining challenge in …

An ontology typically provides a vocabulary describing a domain of interest and a
specification of the meaning of terms in that vocabulary. Depending on the precision of this …

Data integration is a pervasive challenge faced in applications that need to query across
multiple autonomous and heterogeneous data sources. Data integration is crucial in large …

What exactly is smart grid? Why is it receiving so much attention? What are utilities, vendors,
and regulators doing about it? Answering these questions and more, Smart Grids …

In recent times, construction industry is enduring pressure to take drastic steps to minimise
waste. Waste intelligence advocates retrospective measures to manage waste after it is …

This paper reports our first set of results on managing uncertainty in data integration. We
posit that data-integration systems need to handle uncertainty at three levels and do so in a …

Information integration in the enterprise Page 1 LARGE ENTERPRISES SPEND a great deal of
time and money on “information integration”—combining information from different sources into …

Model management is a generic approach to solving problems of data programmability
where precisely engineered mappings are required. Applications include data warehousing …

Materialized views are queries whose results are stored and maintained in order to facilitate
access to data in their underlying base tables. In the SQL setting, they are now considered a …