Category: Data Curation, Open Data, and Research Data Management

Reimagined Universities in an “Open, Networked Era”: "The Principles of Tomorrow’s University"

Daniel S. Katz et al. have published "The Principles of Tomorrow's University" [awaiting peer review] in F1000Research.

Here's an excerpt:

In March 2017, 13 mostly early-career research leaders who are building their careers around these traits came together with ten university leaders (presidents, vice presidents, and vice provosts), representatives from four funding agencies, and eleven organizers and other stakeholders in an NIH- and NSF-funded one-day, invitation-only workshop titled "Imagining Tomorrow’s University."…

During the workshop, the participants reimagined scholarship, education, and institutions for an open, networked era, to uncover new opportunities for universities to create value and serve society. They expressed the results of these deliberations as a set of 22 principles of tomorrow's university across six areas: Credit and Attribution (A), Open Scholarship Communities (C), Outreach and Engagement (O), Education (E), Preservation and Reproducibility (P), and Technologies (T):

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"OCLC Research and euroCRIS Release Report on International Research Information Management Practices"

OCLC Research has released "OCLC Research and euroCRIS Release Report on International Research Information Management Practices."

Here's an excerpt:

OCLC Research and euroCRIS, the international organization for research information, have published a joint research report, Practices and Patterns in Research Information Management: Findings from a Global Survey, which examines how research institutions worldwide are applying research information management (RIM) practices.

The report, written by a working group comprised of experts from both organizations, details the complexity of research information management practices. It examines how commercial and open-source platforms are becoming widely implemented across regions, coexisting with many region-specific solutions as well as locally developed systems. It also considers the factors that have led to the need for complex, cross-stakeholder teams to support institutional RIM activities, which increasingly includes the library.

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"Quadcopters or Linguistic Corpora: Establishing RDM Services for Small-Scale Data Producers at Big Universities"

Viola VoB and Gõran Hamrin have published "Quadcopters or Linguistic Corpora: Establishing RDM Services for Small-Scale Data Producers at Big Universities" in LIBER Quarterly.

Here's an excerpt:

Our research hypothesis is that small-scale data producers have similar needs in engineering and the humanities. This hypothesis is based on the similarities in demands from funding agencies on (open) research data and on the assumption that research in different subjects often creates results which are different in content but similar in structure.

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"Digital Data Archives as Knowledge Infrastructures: Mediating Data Sharing and Reuse"

Christine L. Borgman et al. have self-archived "Digital Data Archives as Knowledge Infrastructures: Mediating Data Sharing and Reuse."

Here's an excerpt:

Digital archives are the preferred means for open access to research data. They play essential roles in knowledge infrastructures—robust networks of people, artifacts, and institutions—but little is known about how they mediate information exchange between stakeholders. We open the "black box" of data archives by studying DANS, the Data Archiving and Networked Services institute of The Netherlands, which manages 50+ years of data from the social sciences, humanities, and other domains. Our interviews, weblogs, ethnography, and document analyses reveal that a few large contributors provide a steady flow of content, but most are academic researchers who submit datasets infrequently and often restrict access to their files. Consumers are a diverse group that overlaps minimally with contributors. Archivists devote about half their time to aiding contributors with curation processes and half to assisting consumers. Given the diversity and infrequency of usage, human assistance in curation and search remains essential. DANS' knowledge infrastructure encompasses public and private stakeholders who contribute, consume, harvest, and serve their data—many of whom did not exist at the time the DANS collections originated—reinforcing the need for continuous investment in digital data archives as their communities, technologies, and services evolve.

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"Enforcing Public Data Archiving Policies in Academic Publishing: A Study of Ecology Journals"

Dan Sholler et al. have self-archived "Enforcing Public Data Archiving Policies in Academic Publishing: A Study of Ecology Journals."

Here's an excerpt:

We conducted a qualitative, interview-based study with journal editorial staff and other stakeholders in the academic publishing process to examine how journals enforce data archiving policies. We specifically sought to establish who editors and other stakeholders perceive as responsible for ensuring data completeness and quality in the peer review process. Our analysis revealed little consensus with regard to how data archiving policies should be enforced and who should hold authors accountable for dataset submissions. Themes in interviewee responses included hopefulness that reviewers would take the initiative to review datasets and trust in authors to ensure the completeness and quality of their datasets. We highlight problematic aspects of these thematic responses and offer potential starting points for improvement of the public data archiving process.

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"Supporting FAIR Data Principles with Fedora"

David Wilcox has published "Supporting FAIR Data Principles with Fedora" in LIBER Quarterly.

Here's an excerpt:

Making data findable, accessible, interoperable, and re-usable is an important but challenging goal. From an infrastructure perspective, repository technologies play a key role in supporting FAIR data principles. Fedora is a flexible, extensible, open source repository platform for managing, preserving, and providing access to digital content. Fedora is used in a wide variety of institutions including libraries, museums, archives, and government organizations. Fedora provides native linked data capabilities and a modular architecture based on well-documented APIs and ease of integration with existing applications. As both a project and a community, Fedora has been increasingly focused on research data management, making it well-suited to supporting FAIR data principles as a repository platform. Fedora provides strong support for persistent identifiers, both by minting HTTP URIs for each resource and by allowing any number of additional identifiers to be associated with resources as RDF properties. Fedora also supports rich metadata in any schema that can be indexed and disseminated using a variety of protocols and services. As a linked data server, Fedora allows resources to be semantically linked both within the repository and on the broader web. Along with these and other features supporting research data management, the Fedora community has been actively participating in related initiatives, most notably the Research Data Alliance. Fedora representatives participate in a number of interest and working groups focused on requirements and interoperability for research data repository platforms. This participation allows the Fedora project to both influence and be influenced by an international group of Research Data Alliance stakeholders. This paper will describe how Fedora supports FAIR data principles, both in terms of relevant features and community participation in related initiatives.

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The State of Open Data 2018—Global Attitudes towards Open Data

Figshare has released The State of Open Data 2018—Global Attitudes towards Open Data.

Here's an excerpt from the announcement:

The key finding is that open data has become more embedded in the research community—64% of survey respondents reveal they made their data openly available in 2018. However, a surprising number of respondents (60%) had never heard of the FAIR principles, a guideline to enhance the reusability of academic data.

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"IU Will Lead $2 Million Partnership to Expand Access to Research Data"

Indiana University has released "IIU Will Lead $2 Million Partnership to Expand Access to Research Data."

Here's an excerpt:

A $2 million project to create a secure online database for academic resources, the Shared BigData Gateway for Research Libraries has been awarded nearly $850,000 from the Institute of Museum and Library Services, the primary federal funding agency supporting the nation's libraries and museums. Additional support comes from eight other universities in the Big Ten; the Big Ten Academic Alliance; the National Science Foundation's Big Data Regional Innovation Hubs program; and two private companies: Clarivate Analytics and Microsoft Research.

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"The EnviDat Concept for an Institutional Environmental Data Portal"

Ionuţ Iosifescu Enescu et al. have published "The EnviDat Concept for an Institutional Environmental Data Portal" in Data Science Journal.

Here's an excerpt:

EnviDat supports data producers and data users in registration, documentation, storage, publication, search and retrieval of a wide range of heterogeneous data sets from the environmental domain. Innovative features include (i) a flexible, three-layer metadata schema, (ii) an additive data discovery model that considers spatial data and (iii) a DataCRediT mechanism designed for specifying data authorship.

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"Sharing Health Research Data—The Role of Funders in Improving the Impact"

Robert F. Terry et al. have published "Sharing Health Research Data—The Role of Funders in Improving the Impact" in F1000Research (awaiting peer review).

Here's an excerpt:

Funders need to engage early with the researchers and related stakeholders to understand their concerns and work harder to define the more explicitly the benefits to all stakeholders. Secondly, there needs to be a direct benefit to sharing data that is directly relevant to those people that collect and curate the data. Thirdly more work needs to be done to realise the intent of making data sharing resources more equitable, ethical and efficient. Finally, a checklist of the issues that need to be addressed when designing new or revising existing data sharing resources should be created.

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"High-performance Computing Service for Bioinformatics and Data Science"

Jean-Paul Courneya and Alexa Mayo have published "High-performance Computing Service for Bioinformatics and Data Science" in the Journal of the Medical Library Association.

Here's an excerpt:

Despite having an ideal setup in their labs for wet work, researchers often lack the computational infrastructure to analyze the magnitude of data that result from “-omics” experiments. In this innovative project, the library supports analysis of high-throughput data from global molecular profiling experiments by offering a high-performance computer with open source software along with expert bioinformationist support. The audience for this new service is faculty, staff, and students for whom using the university's large scale, CORE computational resources is not warranted because these resources exceed the needs of smaller projects. In the library's approach, users are empowered to analyze high-throughput data that they otherwise would not be able to on their own computers. To develop the project, the library's bioinformationist identified the ideal computing hardware and a group of open source bioinformatics software to provide analysis options for experimental data such as scientific images, sequence reads, and flow cytometry files. To close the loop between learning and practice, the bioinformationist developed self-guided learning materials and workshops or consultations on topics such as the National Center for Biotechnology Information's BLAST, Bioinformatics on the Cloud, and ImageJ. Researchers apply the data analysis techniques that they learned in the classroom in an ideal computing environment.

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"Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier"

Christine L. Borgman has self-archived "Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier."

Here's an excerpt:

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of 'grey data' about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This paper explores the competing values inherent in data stewardship and makes recommendations for practice, drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.

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"Using ORCID, DOI, and Other Open Identifiers in Research Evaluation"

Laurel L. Haak et al. have published "Using ORCID, DOI, and Other Open Identifiers in Research Evaluation" in Frontiers in Research Metrics and Analytics.

Here's an excerpt:

We describe how identifiers, such as ORCID iDs and DOIs, are being embedded in research workflows across science, technology, engineering, arts, and mathematics; how this is affecting data availability for evaluation purposes: and provide examples of evaluations that are leveraging identifiers. We also discuss the importance of provenance and preservation in establishing confidence in the reliability and trustworthiness of data and relationships, and in the long-term availability of metadata describing objects and their inter-relationships.

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"Surveying the State of Data Curation: a Review of Policy and Practice in UK HEIs"

Amy Pham has self-archived "Surveying the State of Data Curation: a Review of Policy and Practice in UK HEIs."

Here's an excerpt:

Through a three-part methodology, the dissertation research aimed to provide a clear picture of the current state of data curation in UK HEIs, including adherence to best practices and the existence of provisions for data curation efforts. A survey questionnaire was disseminated as the primary method of data collection, and additional information was gathered through a literature review and an analysis of online resources and institutional policies. Data curation practices were found to be mostly inconsistent with best practices and were largely focused on facilitating access to research data. However, there is an awareness of the underdeveloped areas of data curation, especially preservation, and efforts are being made to improve these areas. Institutional policies were found to be mostly documents that defined roles and responsibilities and provided little guidance for follow-through. The role of researchers was repeatedly emphasized in both policy and practice and was essential in understanding the current state of data curation.

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"Facilitating and Improving Environmental Research Data Repository Interoperability"

Corinna Gries et al. have published "Facilitating and Improving Environmental Research Data Repository Interoperability" in Data Science Journal.

Here's an excerpt:

Environmental research data repositories provide much needed services for data preservation and data dissemination to diverse communities with domain specific or programmatic data needs and standards. Due to independent development these repositories serve their communities well, but were developed with different technologies, data models and using different ontologies. Hence, the effectiveness and efficiency of these services can be vastly improved if repositories work together adhering to a shared community platform that focuses on the implementation of agreed upon standards and best practices for curation and dissemination of data. Such a community platform drives forward the convergence of technologies and practices that will advance cross-domain interoperability. It will also facilitate contributions from investigators through standardized and streamlined workflows and provide increased visibility for the role of data managers and the curation services provided by data repositories, beyond preservation infrastructure. Ten specific suggestions for such standardizations are outlined without any suggestions for priority or technical implementation. Although the recommendations are for repositories to implement, they have been chosen specifically with the data provider/data curator and synthesis scientist in mind.

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"Towards a Culture of Open Science and Data Sharing in Health and Medical Research"

Anisa Rowhani-Farid has self-archived "Towards a Culture of Open Science and Data Sharing in Health and Medical Research."

Here's an excerpt:

This [Ph.D] thesis investigated the factors that contribute to the cultural shift towards open science and data sharing in health and medical research, with a focus on the role health and medical journals play. The findings of this research demonstrate that journal data sharing policies are not effective and that journals do not currently provide incentives for sharing. This study contributed to the movement towards more reproducible research by providing empirical evidence for the strengthening of journal data sharing policies and the adoption of an incentive for open research.

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Science as an Open Enterprise

The Royal Society has released Science as an Open Enterprise.

Here's an excerpt:

This report analyses the impact of new and emerging technologies that are transforming the conduct and communication of research. The recommendations are designed to improve the conduct of science, respond to changing public expectations and political culture and enable researchers to maximise the impact of their research. They are designed to ensure that reproducibility and self-correction are maintained in an era of massive data volumes. They aim to stimulate the communication and collaboration where these are needed to maximise the value of data-intensive approaches to science.

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