In the context of the Open Science movement, metrics and procedures of research assessment are changing. What does this mean for current research information systems (CRIS)? From an analysis of a selection of official documents, our contribution describes the challenges and provides some ideas and perspectives for the further development of the CRIS. In 2012, DORA, the San Francisco Declaration on Research Assessment, invited funding agencies, institutions, publishers, and researchers to improve their practices in research assessment, without “journal-based metrics, such as Journal Impact Factors, as a surrogate measure of the quality of individual research articles, to assess an individual scientist’s contributions, or in hiring, promotion, or funding decisions”. At the same time, DORA recommended more transparency (explicit criteria), more diversity (including datasets and software), quality instead of quantity assessment (content) and open metrics (licensing). Many institutions and organizations signed the DORA declaration. Also, since 2012, an increasing number of international and national organizations published their own declarations, manifestos, reports, and other recommendations in order to shape and to accelerate the transformation of the research assessment landscape; some of them are listed below. Yet, the debate on research assessment is open. While the European Coalition for Advancing Research Assessment (CoARA) published a couple of months ago an Agreement with ten commitments, including the recognition of the “diversity of contributions to, and careers in, research”, the “focus on qualitative evaluation for which peer review is central, supported by responsible use of quantitative indicators” and the “abandon (of) inappropriate uses in research assessment of journal- and publication-based metrics”, the German Research Foundation (DFG), in a recent paper, recalls that its purpose is to fund “research of the highest quality” and that it is “opposed towards transforming research assessment systems with the aim to impose open science as an end in itself”. What does this mean for the development and implementation of research information systems? What does this mean for the underlying data model? Based on our former research and on a review of recent declarations, our contribution will summarize the main issues and provide some ideas and recommendations for CRIS providers and managers.