Malleable Schemas: A Preliminary Report Xin Luna Dong and Alon Y. Halevy   View Paper (PDF)   Return to Poster Papers Abstract Large-scale information integration, and in particular, search on the World Wide Web, is pushing the limits on the combination of structured data and unstructured data. By its very nature, as we combine a large number of information sources, our ability to model the domain in a completely structured way diminishes. We argue that in order to build applications that combine structured and unstructured data, there is a need for a new modeling tool. We consider the question of modeling an application domain whose data may be partially structured and partially unstructured. In particular, we are concerned with applications where the border between the structured and unstructured parts of the data is not well defined, not well known in advance, or may evolve over time. We propose the concept of malleable schemas as a modeling tool that enables incorporating both structured and unstructured data from the very beginning, and evolving one's model as it becomes more structured. A malleable schema begins the same way as a traditional schema, but at certain points gradually becomes vague, and we use keywords to describe schema elements such as classes and properties. The important aspect of malleable schemas is that a modeler can capture the important aspects of the domain at modeling time without having to commit to a very strict schema. The vague parts of the schema can later evolve to have more structure, or can remain as such. Users can pose queries in which references to schema elements can be imprecise, and the query processor will consider closely related schema elements as well. ©2006 Association for Computing Machinery