The close-out checklist describes a range of activities for helping ensure that research data are properly managed at the end of a project or at researcher departure. Activities include: making stewardship decisions, preparing files for archiving, sharing data, and setting aside important files in a "FINAL" folder. Two versions of the checklist are available: a Caltech Library branded version and a generic editable version.

On so-called "soft skills."

Data Profession Key Positions — Explained

Digital databases offer scientists new ways to study human remains. But without proper oversight, some worry they could be misused.

It is increasingly common for researchers to publish their datasets in open, mediated, or restricted form as a research output. The process of publishing data is complex and there are few guides that are practical or easy to understand. To bridge this gap, the Digital Curation and Data team at the University of Sydney Library initiated a project to develop applied data publication resources. To reflect current University and Library strategies, the team expanded the project to include a cultural competence review of each newly developed resource in order to reflect on the cultural biases that had gone into its creation and the ways in which the resource might appear through alternative cultural lenses, initially focusing on the data publication needs for research relating to Aboriginal and Torres Strait Islander peoples. It may be especially challenging for researchers who are working with culturally sensitive data to find resources that are easy to use and relevant. One initial goal of this project is to ensure that researchers, students and staff can support the ethical and culturally appropriate publication of data relating to Aboriginal and Torres Strait Islander peoples, communities, and knowledges. The team reviewed prototyped resources with researchers who conduct research with Aboriginal and Torres Strait Islander peoples to assess their usefulness and identify gaps. Resources are now being updated to reflect feedback, and additional resources will also be created. The intention is to continue to integrate cultural competence into the University of Sydney’s data curation and publication services and to expand this process to include wider cultural perspectives.  

Broken links, clunky formats, and outdated platforms have both authors and publishers turning to alternative solutions.

As an increasing variety and complexity of environmental issues confront scientists and natural resource managers, assembling the most relevant and informative data into accessible data systems becom...

Today, science involves software. And although many scientists understand that their work stands on the shoulders of others, they may not know how copyright affects their rights to use others' software, or how they can publish their software tools so others can use or cite it. The Copyright Guide to Scientific Software, a joint project of the Harvard Cyberlaw Clinic and the Center for Astrophysics, in association with the Software Preservation Network, aims to fill that gap, by providing clear, easy-to-read answers to common questions about how scientific software and copyright interact.

Why they’re a problem and what to do about it

Public access to the results of federally funded research can accelerate scientific breakthroughs. In 2013, certain federal agencies were directed to...

3D scanning

Higher Education Knowledge Base content management, sharing and collaboration platform.

Learn what master data management it is, why it's important, how to get started and who's involved. Start reading now!

Author(s): Boscoe, Bernadette Marie | Advisor(s): Borgman, Christine L. | Abstract: In compute-heavy and data-driven scientific fields, digital data play a central role in the creation of knowledge. For science fields that rely on data that can only be observed once, the preservation of these data is crucial to analytic processes. Time-domain astronomy is one such field, involving celestial observations such as exploding supernovae and passing comets. This dissertation examines the data and code practices of a university-based astronomy research group who have managed to keep their data “alive” for twenty-three years with limited resources. Keeping data alive means both understanding the knowledge contained within and having the associated technologies operable. The human aspects necessary to keep data alive are equally as important as the technological elements. This three-year ethnographic research project examines the factors involved in analyzing, preserving, and curating astronomy data as these data wend their way through socio-technical, physical, and digital infrastructures that shape and are shaped by the knowledge contained within the data. Dissertation research took place at six field sites: the case study’s university, the observatory of the case study, the archive of the observatory, and three other astronomy archives. The findings of this study show two main ways that data are kept alive in astronomy: 1) Publicly: Data are curated and preserved with the intention to be made available via web interfaces, engendering relationships among stakeholders, and 2) Privately: Data are preserved by astronomy research groups at universities that continually reuse them and their associated code, in a collaborative way. Findings suggest how a better understanding of the relationships between public and private astronomy data can inform scientific data preservation and curation practices.

Dataset Search could be a scientist’s best friend

Objectives: The objective of this study is to evaluate the quality and usability of supplementary data files deposited, between 1971 and 2015, to our university institutional repository. Understanding the extent to which content historically deposited in digital repositories is usable by today’s researchers can help inform digital preservation and documentation practices for researchers today. Methods: I identified all graduate level theses and dissertations (GTDs) in the institutional repository with multiple files as a first pass at identifying documents that included supplementary data files. These GTDs were then individually examined, removing supplementary files that were artifacts of either the upload or digitization process. The remaining “true” supplementary files were then individually opened and evaluated following elements of the DATA rubric of Van Tuyl and Whitmire (2016). Results: Supplementary files were discovered in the repository dating back to 1971 in 116 GTD submissions totalling more than 25,000 files. Most GTD submissions included fewer than 30 files, though some submissions included thousands of individual data files. The most common file types submitted include imagery, tabular data, and databases, with a very large number of unknown file types. Overall, levels of documentation were poor while actionability of datasets was generally middling. Conclusions: The results presented in this study suggest that legacy data submitted to our institutional repository with GTDs is generally in poor shape with respect to Transparency and somewhat less so for Actionability. It is clear from this study and others that researchers have a long road ahead when it comes to sharing data in a way that makes it potentially useable by other researchers.

The Center for Data Innovation spoke with Chris Mentzel, program director for the Data-Driven Discovery Initiative at the Gordon and Betty Moore Foundation [...]