Abstract. The need for interpretation of provenance data increases with the introduction of further provenance related IT-systems. The interpretation of data only becomes intuitively with providing good and efficient visualization possibilities. During the development of general provenance visualization techniques, provenance users are classified into groups regarding their view to provenance information. The end-user requirements are evaluated on an abstract level to have a basis for research. Different intentions of end-users regarding provenance are identified and put into relationship with standard visualization types. Examples for standard visualization types are given and a brief forecast to future achievements is made.

The need for collaboration between individual scientific fields increases with the wish for more global engineering optimizations and assessment requirements. Since areas of research become more and more fine-grained domains of there own, it is still very desirable to cooperate with other experts with more chance than ever to gain synergies when science is scattered as today. But this exchange of knowledge comes only into consideration if it can be used in a simple way with at most an moderate initial effort. To this end a framework is developed that lets scientists easily use knowledge of others without the need to understand their work and technology completely. Furthermore a generic common data format based on XML technology is developed for exchanging and storing data between different domain-specific applications. To support all implementers, a twofold abstraction layer was introduced to encapsulate their knowledge shielding it from the technical environment.

Abstract. "Why does the build fail currently?" -This and similar questions arise on a daily basis in software development processes (SDP). There is no easy way to answer these questions, the required information is stored throughout different tools, the version control and continuous integration systems in this example. The tools mainly live in isolated worlds and no direct connection between their data exists. This paper proposes a solution to such problems, based on provenance technologies. After outlining the complexity of a SDP, the questions arising on a daily basis are categorized. Finally an approach to make the SDP provenanceaware is proposed based on PRiME, the Open Provenance Model and a SOA architecture using Neo4j to store the data, Gremlin to query it and REST webservices as connection to the tools.