The Aspect-Oriented Architecture of the CAPS Framework for Capturing, Analyzing and Archiving Provenance Data
نویسندگان
چکیده
With aspect-oriented programming techniques, modularity may be achieved via separating cross-cutting concerns. Data provenance can be considered as a crosscutting concern: code for collecting provenance data is usually scattered across various places in a software system. Aspect-oriented programming allows to seamlessly integrate cross-cutting concerns into existing software applications without interference with the original system. Following this approach, CAPS is a framework to weave provenance-capturing mechanisms into existing Java applications, which are not yet provenance aware. The CAPS framework employs AspectJ [5], the Kieker framework [7,4], the Java Management Extensions JMX, and some Java security mechanisms to automatically collect the provenance information. Woven inside the application as a minimal-invasive integration of the provenance capturing mechanisms, CAPS monitors the execution of the software. Whenever a data set is processed, CAPS creates the corresponding provenance graph entry. The graph itself is stored in an integrated provenance archive build on top of the Neo4j graph database. CAPS is implemented and evaluated in the context of the PubFlow workflow system for semi-automatic research data publication [2]. In particular, workflow-generated provenance data is automatically gathered via CAPS, without mixing program logic with provenance mechanisms. For deployment, CAPS provides a GWT-based web interfaces, which allows the user to upload his own scientific Java applications to the CAPS runtime environment. While uploading the application, the user has to provide basic information about the application and its runtime environment. These include:
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