The digital universe is booming, especially metadata and user-generated data. This raises strong challenges in order to identify the relevant portions of data which are relevant for a particular problem and to deal with the lifecycle of data. Finer grain problems include data evolution and the potential impact of change in the applications relying on the data, causing decay. The management of scientific data is especially sensitive to this. We present the Research Objects concept as the means to indentify and structure relevant data in scientific domains, addressing data as first-class citizens. We also identify and formally represent the main reasons for decay in this domain and propose methods and tools for their diagnosis and repair, based on provenance information. Finally, we discuss on the application of these concepts to the broader domain of the Web of Data: Data with a Purpose.
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