Extracting information from heterogeneous information sources using ontologically specified target views

People want to know! And so do government agencies, information providers, search-and-retrieval companies, electronic publishers, corporate enterprises, and business professionals. But they’re swamped with volumes of structured and unstructured data spewed forth from databases, data warehouses, search engines, corporate intranets, news feeds, and the increasing global Internet. They want critical information extracted and integrated in a personalized view, all automatically at the level of a human expert. In conjunction with collective efforts of data and knowledge workers, we attack this problem head on by offering, in this paper, a framework for addressing these problems. In our proposed framework we assume that a target view is specified ontologically and independently of any of the sources, and we model both the target and all the sources in the same modeling language. Then, for a given target and source we generate a target-to-source mapping, that has the necessary properties to enable us to load target facts from source facts. The mapping generator raises specific issues for a user’s consideration, but is endowed with defaults to allow it to run to completion with or without user input. In addition to a resulting target-to-source mapping, the mapping generator records alternative possibilities in a table, which thus holds the answers to what possibilities were considered and why the selected possibilities were chosen, and which also provides for confidence factors to measure the confidence in the mapping selected. The framework is based on a formal foundation, and we are able to prove that when a source has a valid interpretation, the part of the target loaded from the source according to a generated source-to-target mapping also has a valid interpretation. Given individual target-to-source mappings for several sources, the framework ∗Research for this paper was done during a sabbatical leave from Brigham Young University, Provo, Utah 84602, U.S.A.