There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.
A questionnaire dealing with the incidence of traumatic injuries was sent to 1,000 randomly selected 3rd-year university students in Finland; 617 students responded adequately. Of those, 177 (28.7%) reported a combined total of 281 accidents and 323 separate injuries requiring medical or dental treatment during the preceding 3 years. The accidents resulted in 1,061 days of official sick leave, and one third of the accidents caused permanent sequelae to the affected students. Almost half of all accidents had been sustained during sports activities and 14% in traffic. Only 0.5% of the accidents were classified as having occurred in the university environment or during activities directly related to studies. Alcohol was involved in 10.1% of the accidents; 45% of the injuries affected the lower extremities, and 22% the upper extremities. Most of the injuries were related to the students' active lifestyles and keen interest in sports.
We present a deductive data model for conceptbased query expansion. It ]s based on three abstraction levels: the conceptual, linguistic and occurrence levels. Concepts and relationships among them are represented at the conceptual level. The expression level represents natural language expressions for concepts. Each expression has one or more matchmg models at the occurrence level. The models specify the matching of the expression in database Indices built in varying ways. The data model supports a concept-based query expansion and formulation tool, the ExpansionTool, for heterogeneous IR system envirom ments, Expansion is controlled by adjustable matching reliability.
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