In this chapter we investigate the crucial problem that poses the bases to the concept of dataspaces: the need for human interaction/intervention in the process of organizing (getting the structure of) unstructured data. We survey the existing techniques behind dataspaces to overcome that need, exploring the structure of a dataspace along three dimensions: dataspace profiling, querying and searching and application domain. We will further explore existing projects focusing on dataspaces, induction of data structure from documents, and data models where data schema and documents structure overlaps will be reviewed, such as Apache Hadoop, Cassandra on Amazon Dynamo, Google BigTable model and other DHT-based flexible data structures, Google Fusion Tables, iMeMex, U-DID, WebTables and Yahoo! SearchMonkey. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Atzori, M., & Dessì, N. (2011). Dataspaces: Where structure and schema meet. Studies in Computational Intelligence, 375, 97–119. https://doi.org/10.1007/978-3-642-22913-8_5
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