QUEST: QUery-driven Exploration of Semistructured Data with ConflicTs and partial knowledge, CleanDB

Abstract

An important reality when integrating scientific data is the fact that data may often be “missing”, partially specified, or conflicting. Therefore, in this paper, we present an assertion-based data model that captures both value-based and structure-based “nulls” in data. We also introduce the QUEST system, which leverages the proposed model for Query-driven Exploration of Semistructured data with conflicT s and partial knowledge. Our approach to integration lies in enabling researchers to observe and resolve conflicts in the data by considering the context provided by the data requirements of a given research question. In particular, we discuss how pathcompatibility can be leveraged, within the context of a query, to develop a high-level understanding of conflicts and nulls in data. 1 Motivation and Related Work Through a joint effort of archaeologists and computer scientists, we are developing an integrated framework of knowledge-based collaborative tools that will provide the foundation for a shared information infrastructure for archaeology and contribute substantially to a shared knowledge infrastructure of science [21]. Today, the incapacity to integrate data across projects cripples archaeologists ’ and other scientists’ efforts to recognize phenomena operating on large spatio-temporal scales and to conduct crucial comparative studies [20, 21]. A major challenge with integration of data is that the meaning of an archaeological observation is rarely self-evident