In the study of fine art, provenance refers to the documented history of some art object. Given that documented history, the object attains an authority that allows scholars to appreciate its importance with respect to other works, whereas, in the absence of such history, the object may be treated with some skepticism. Our IT landscape is evolving as illustrated by applications that are open, composed dynamically, and that discover results and services on the fly. Against this challenging background, it is crucial for users to be able to have confidence in the results produced by such applications. If the provenance of data produced by computer systems could be determined as it can for some works of art, then users, in their daily applications, would be able to interpret and judge the quality of data better. We introduce a provenance lifecycle and advocate an open approach based on two key principles to support a notion of provenance in computer systems: documentation of execution and user-tailored provenance queries.

Abstract. Agent-oriented cooperation techniques and standardized electronic healthcare record exchange protocols can be used to combine information regarding different facets of a therapy received by a patient from different healthcare providers at different locations. Provenance is an innovative approach to trace events in complex distributed processes, dependencies between such events, and associated decisions by human actors. We focus on three aspects of provenance in agent-mediated healthcare systems: first, we define the provenance concept and show how it can be applied to agent-mediated healthcare applications; second, we investigate and provide a method for independent and autonomous healthcare agents to document the processes they are involved in without directly interacting with each other; and third, we show that this method solves the privacy issues of provenance in agent-mediated healthcare systems.

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Home Care services are notoriously difficult to deliver efficiently, due to the heterogeneity of the involved actors and the usual co-morbidity of the patients assisted at home. The K4Care platform proposes an agent-based threelayered architecture aimed at addressing these two issues and facilitate the provision of these services. The development of the platform was supported by a methodology to help the automation of the modelling and implementation of the multi-agent system. The intelligent agents of the platform, which personify the Home Care domain actors, have the capability to guide the execution of administrative and medical processes, driving the flux of knowledge and control among all the involved professionals, simplifying their interactions and capturing new medical knowledge emerging from physicians. The platform also provides tools that allow medical practitioners to develop personalised treatments, adapted to the clinical and social circumstances of each patient and based on the standard international recommendations for the most frequent Home Care pathologies. The paper describes the architecture of the system, how personalised treatments are created, and how they are executed through the co-ordinated work of agents. A comparison with other relevant guideline execution systems and an evaluation of the actual state of the work are also provided.