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Paper: Astronomical Data Integration Beyond the Virtual Observatory
Volume: 495, Astronomical Data Analysis Software and Systems XXIV (ADASS XXIV)
Page: 513
Authors: Lemson, G.; Laurino, O.
Abstract: "Data integration" generally refers to the process of combining data from different source data bases into a unified view. Much work has been devoted in this area by the International Virtual Observatory Alliance (IVOA), allowing users to discover and access databases through standard protocols. However, different archives present their data through their own schemas and users must still select, filter, and combine data for each archive individually. An important reason for this is that the creation of common data models that satisfy all sub-disciplines is fraught with difficulties. Furthermore it requires a substantial amount of work for data providers to present their data according to some standard representation. We will argue that existing standards allow us to build a data integration framework that works around these problems. The particular framework requires the implementation of the IVOA Table Access Protocol (TAP) only. It uses the newly developed VO data modelling language (VO-DML) specification, which allows one to define extensible object-oriented data models using a subset of UML concepts through a simple XML serialization language. A rich mapping language allows one to describe how instances of VO-DML data models are represented by the TAP service, bridging the possible mismatch between a local archive's schema and some agreed-upon representation of the astronomical domain. In this so called local-as-view approach to data integration, “mediators" use the mapping prescriptions to translate queries phrased in terms of the common schema to the underlying TAP service. This mapping language has a graphical representation, which we expose through a web based graphical “drag-and-drop-and-connect" interface. This service allows any user to map the holdings of any TAP service to the data model(s) of choice. The mappings are defined and stored outside of the data sources themselves, which allows the interface to be used in a kind of crowd-sourcing effort to annotate any remote database of interest. This reduces the burden of publishing one's data and allows a great flexibility in the definition of the views through which particular communities might wish to access remote archives. At the same time, the framework easies the user's effort to select, filter, and combine data from many different archives, so as to build knowledge bases for their analysis. We will present the framework and demonstrate a prototype implementation. We will discuss ideas for producing the missing elements, in particular the query language and the implementation of mediator tools to translate object queries to ADQL
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