Good Data, Better Data, and Knowing the Difference


Managing and curating large data is increasingly important from individual research projects through to agency-level data streams. AGU is engaging in two efforts to assist the Earth and space science community.  One is in training and certification of individual scientists and data managers.  The second is aimed at helping repositories, from large to small, assess and adopt best practices in data operations.  For this latter effort, we are adapting the CMMI® Institute’s Data Management Maturity (DMM)SM model and will be offering to work with repositories to determine where their current practices place them within an incremental capability measurement criteria.  Both of these efforts are guided by editorial board members representing repository managers, librarians and researchers.

The DMM Editorial Board is established, held an initial kickoff meeting in June, and provided initial guidance.  We are currently seeking pilots to be conducted this year and working on interpreting the data management maturity model for the Earth and space science community.  The model is scalable and can be applied to a large organization as well as an individual scientist.  It applies to government-funded, institutional-funded, and private programs.  

The DMM SM model is a framework that fosters organizational alignment around data and process improvement for data management.  The framework defines “what” processes need to be in place, not “how” they are to be accomplished.  The model includes best practices for establishing, building, sustaining, and optimizing effective data management across the data lifecycle, from creation through delivery, curation, maintenance, and archiving.

AGU’s specific goals include: provide value to the community in managing data, help our community (funders and users) meet emerging/expanding guidelines, advance science, improve integrity in research output, align with other efforts, and sustainability.



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