In which Figshare is nice, but not branded.

Scientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is based on smaller and shorter term projects at a disadvantage. The volume and variety of data to be managed varies by many factors, only two of which are the number of collaborators and length of the project. As part of an NSF project to conceptualize the Institute for Empowering Long Tail Research, we explored opportunities offered by Software as a Service (SaaS). These cloud-based services are popular in business because they reduce costs and labor for technology management, and are gaining ground in scientific environments for similar reasons. We studied three settings where scientists conduct research in small and medium-sized laboratories. Two were NSF Science and Technology Centers (CENS and C-DEBI) and the third was a workshop of natural reserve scientists and managers. These laboratories have highly diverse data and practices, make minimal use of standards for data or metadata, and lack resources for data management or sustaining access to their data, despite recognizing the need. We found that SaaS could address technical needs for basic document creation, analysis, and storage, but did not support the diverse and rapidly changing needs for sophisticated domain-specific tools and services. These are much more challenging knowledge infrastructure requirements that require long-term investments by multiple stakeholders.

Same old lessons. When will they ever learn...

Background: the emerging role of data management in research libraries I first became aware of research data management as a frontier area of expertise

There is an awful lot of talk about academic libraries providing data curation services for their researchers.  It turns out that in most cases that service amounts to training and …

IMLS (Institute of Museum and Library Services) announced recently that it is funding a $2 million grant for three partners (Digital Public Library of America, Stanford University, and DuraSpace) to develop repository solutions, hosting strategies, and methods for the exchange of information for digital library collections. The project will give libraries, museums, and archives of all types and sizes an out-of-the-box open source solution for managing their digital content and exposing what they have to the world. It will build on the work many academic libraries have done to create institutional repositories for their own organizations.

Libraries exist to provide amazing services and resources to our users.  We are so committed to this vision that we continue to offer these services even after users don't need them. As non-profit ...

Objective: To describe three tiers of research data support services that emerged from national environmental scanning of data management needs and activities. Setting: The University of Massachusetts Amherst (UMass Amherst) is a top fifty recipient of NSF funding, with the agency providing over 40% of the University’s sponsored research, and is classified as a Research University with Very High research activity by the Carnegie Foundation. After determining a need for data management services, a library Data Working Group per-formed national environmental scanning. Environmental scanning used public information available from 18 UMass Amherst peer and model institutions to determine the range of data management and curation services that are available to various research communities. Methods: Environmental scanning activities include a web audit. Results: National practices demonstrate a wide range of potential data management services. UMass Amherst’s Data Working Group has generalized data management services into three tiers, creating a useful rubric for determining one’s current service level and for setting goals to meet the needs of one’s research community. Conclusions: The Tiers of Research Data Support Services, generalized from local needs and national activities, describe different levels of support of increasing cost and involvement scales for supporting researchers’ data management and curation needs: education, consultation, and infrastructure.