Data Cleaning publication categorizer

Data integration in complex domains, such as the
life sciences, involves either manual data curation,
offering highest information quality at highest
price, or follows a schema integration and mapping
approach, leading to moderate information quality
at a moderate price. We suggest a radically differ-
ent integration approach, called ALADIN, for the
life sciences application domain. The predominant
feature of the ALADIN system is an architecture
that allows almost automatic integration of new
data sources into the system, i.e., it offers data in-
tegration at almost no cost.
We suggest a novel combination of data and text
mining, schema matching, and duplicate detection
to combat the reduction in information quality that
seems inevitable when demanding a high degree of
automatism. These heuristics can also lead to the
detection of previously unknown or unseen rela-
tionships between objects, thus directly supporting
the discovery-based work of life science research-
ers. We argue that such a system is a valuable con-
tribution in two areas. First, it offers challenging
and new problems for database research. Second,
the ALADIN system would be a valuable knowl-
edge resource for life science research.