Recent advances in computing, communications, and digital storage technologies, together
with development of high throughput data acquisition technologies have made it possible to …

The paper presents the D ata I ntegration and C leansing E nvironment—DICE. Its
embedded modeling method supports the data understanding and data preparation phases …

We introduce a statistical, process-oriented metadata model to describe the process of
medical research data collection, management, results analysis and dissemination. Our …

Abstract Public Administrations (PAs) are facing profound institutional and organizational
changes requiring managers, stakeholders, and responsible statesmen to increase their …

Statistical data processing makes use of data matrices and tables as primary structures for
data representation. Embedding these structures into processing-relevant context …

The World-Wide Web provides an ever-increasing source of diverse information. We focus
on query agents, in particular the matching and negotiation agents that are responsible for …

The extension of Classical Data Analysis into Symbolic Data Analysis leads to more
complex data types and tables, thus making the handling underlying concepts a more …

An integrated, semantically rich statistical metadata model is designed to cover the major
stages of the statistical information processing (data collection and analysis including …

R&D manipulation is a subjective manipulation of R&D accounting accounts by
management that ignores the facts about R&D. It has a negative impact on the innovation …

This paper describes the technologies developed for the extraction and publication of large
volumes of statistical information, such as are produced by public data collection …