The vision of the ANC is guided by the ideal that resources in general, and scientific research data in particular, should be used considerately and effectively. In pace with the accelerating movement towards open and transparent science, the ANC reaffirms the value of data beyond the purpose it was originally collected for — advocating for research data to be regarded not only as a by-product of scientific work, but as a reusable and enduring research asset.
Yet, transforming data into such a lasting asset is becoming an increasingly complex task. The current landscape of FAIR data management imposes various requirements, including the use of persistent identifiers, adherence to community-specific standards, and the inclusion of rich, standardized metadata. These demands can be difficult to navigate, especially for those unfamiliar with the technical and domain-specific intricacies involved. Even within neuroscience, multiple competing standards and metadata models exist. Evaluating their quality and relevance for a particular dataset requires both technical and subject-matter expertise. Moreover, adapting data to fit a specific standard can be both time-consuming and challenging.
The ANC maintains that the responsibility for meeting these requirements should not rest solely with individual researchers. To truly enable data reuse and long-term value, researchers must be supported by robust infrastructure and expert guidance. Through its services, the ANC actively supports researchers in transforming their data into meaningful and enduring research outputs.