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

"Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines"

Kathleen Gregory et al. have published "Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines" in the Journal of the Association for Information Science and Technology.

Here's an excerpt:

This review explores the existing data retrieval literature and identifies commonalities in documented practices among users of observational data as a first step toward creating a model describing how users search for and evaluate research data.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Research Computing in the Cloud: Leveling the Playing Field"

Michael Berman has published "Research Computing in the Cloud: Leveling the Playing Field" in EDUCAUSE Review.

Here's an excerpt:

The universal availability of commodity cloud services and high-speed networks can eliminate the requirement that departments must have local HPC resources. The infrastructure available from large cloud providers such as AWS dwarfs and outperforms all but the largest and most-specialized supercomputing facilities. . . .

Moving large data sets on commodity networks, or even on regional research and education networks, simply doesn't work well for hundreds of terabytes or petabytes of data, which is the scale required by modern researchers in many fields. . . .

To begin to address these issues, the Pacific Research Platform (PRP), a collaboration among research universities and CENIC (operator of the CalREN network serving California), has been funded by the National Science Foundation to support the streaming of "elephant flows."

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

What to Keep: A Jisc Research Data Study

Jisc has released What to Keep: A Jisc Research Data Study.

Here's an excerpt:

What to keep in terms of research data has been a recognised issue for some time but research data management and in particular appraisal and selection (i.e. 'what to keep and why') has become a more significant focus in recent years as volumes and diversity of data have grown, and as the available infrastructure for 'keeping' has become more diverse.

The purpose of the What to Keep study is to provide new insights that will be useful to institutions, research funders, researchers, publishers, and Jisc on what research data to keep and why, the current position, and suggestions for improvement.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Bringing Citations and Usage Metrics Together to Make Data Count"

Helena Cousijn et al. have published "Bringing Citations and Usage Metrics Together to Make Data Count" in Data Science Journal.

Here's an excerpt:

Over the last years, many organizations have been working on infrastructure to facilitate sharing and reuse of research data. This means that researchers now have ways of making their data available, but not necessarily incentives to do so. Several Research Data Alliance (RDA) working groups have been working on ways to start measuring activities around research data to provide input for new Data Level Metrics (DLMs). These DLMs are a critical step towards providing researchers with credit for their work. In this paper, we describe the outcomes of the work of the Scholarly Link Exchange (Scholix) working group and the Data Usage Metrics working group. The Scholix working group developed a framework that allows organizations to expose and discover links between articles and datasets, thereby providing an indication of data citations. The Data Usage Metrics group works on a standard for the measurement and display of Data Usage Metrics. Here we explain how publishers and data repositories can contribute to and benefit from these initiatives. Together, these contributions feed into several hubs that enable data repositories to start displaying DLMs. Once these DLMs are available, researchers are in a better position to make their data count and be rewarded for their work.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Data Management Practices in Academic Library Learning Analytics: A Critical Review"

Kristin A. Briney has published "Data Management Practices in Academic Library Learning Analytics: A Critical Review" in the Journal of Librarianship and Scholarly Communication.

Here's an excerpt:

INTRODUCTION Data handling in library learning analytics plays a pivotal role in protecting patron privacy, yet the landscape of data management by librarians is poorly understood. METHODS This critical review examines data-handling practices from 54 learning analytics studies in academic libraries and compares them against the NISO Consensus Principles on User’s Digital Privacy in Library, Publisher, and Software-Provider Systems and data management best practices. RESULTS A number of the published research projects demonstrate inadequate data protection practices including incomplete anonymization, prolonged data retention, collection of a broad scope of sensitive information, lack of informed consent, and sharing of patron-identified information. DISCUSSION As with researchers more generally, libraries should improve their data management practices. No studies aligned with the NISO Principles in all evaluated areas, but several studies provide specific exemplars of good practice. CONCLUSION Libraries can better protect patron privacy by improving data management practices in learning analytics research.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Introducing eLife’s First Computationally Reproducible Article"

eLife has released Introducing eLife's First Computationally Reproducible Article by Giuliano Maciocci, Michael Aufreiter and Nokome Bentley.

Here's an excerpt:

Reproducible manuscripts enrich the traditional narrative of a research article with code, data and interactive figures that can be executed in the browser, downloaded and explored, giving readers a direct insight into the methods, algorithms and key data behind the published research.

Today eLife, in collaboration with Substance, Stencila and Tim Errington, Director of Research at the Center for Open Science, US, published its first reproducible article, based on one of Errington's papers in the Reproducibility Project: Cancer Biology.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

Mini-Grants: "Frictionless Data Tool Fund"

Frictionless Data has released "Frictionless Data Tool Fund."

Here's an excerpt:

The Frictionless Data Tool Fund, supported by the Sloan Foundation, is providing a number of mini-grants of $5,000 to support individuals or organisations in developing an open tool for reproducible science or research built using the Frictionless Data specifications and software. We welcome submissions of interest from 15th Feb 2019 until 30th April 2019.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Expanding the Research Data Management Service Portfolio at Bielefeld University According to the Three-pillar Principle Towards Data FAIRness"

Jochen Schirrwagen et al. have published "Expanding the Research Data Management Service Portfolio at Bielefeld University According to the Three-pillar Principle Towards Data FAIRness" in Data Science Journal (Creative Commons Attribution 4.0 International License).

Here's an excerpt:

Research Data Management at Bielefeld University is considered as a cross-cutting task among central facilities and research groups at the faculties. While initially started as project “Bielefeld Data Informium” lasting over seven years (2010–2015), it is now being expanded by setting up a Competence Center for Research Data. The evolution of the institutional RDM is based on the three-pillar principle: 1. Policies, 2. Technical infrastructure and 3. Support structures. The problem of data quality and the issues with reproducibility of research data is addressed in the project Conquaire. It is creating an infrastructure for the processing and versioning of research data which will finally allow publishing of research data in the institutional repository. Conquaire extends the existing RDM infrastructure in three ways: with a Collaborative Platform, Data Quality Checking, and Reproducible Research.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies"

Costantino Thanos has published "Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies" in Publications (CC BY 4.0).

Here's an excerpt:

High-throughput scientific instruments are generating massive amounts of data. Today, one of the main challenges faced by researchers is to make the best use of the world's growing wealth of data. Data (re)usability is becoming a distinct characteristic of modern scientific practice. By data (re)usability, we mean the ease of using data for legitimate scientific research by one or more communities of research (consumer communities) that is produced by other communities of research (producer communities). Data (re)usability allows the reanalysis of evidence, reproduction and verification of results, minimizing duplication of effort, and building on the work of others. It has four main dimensions: policy, legal, economic and technological. The paper addresses the technological dimension of data reusability. The conceptual foundations of data reuse as well as the barriers that hamper data reuse are presented and discussed. The data publication process is proposed as a bridge between the data author and user and the relevant technologies enabling this process are presented.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories"

Mingfang Wu et al. have published "Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories" in Data Science Journal (CC BY 4.0).

Here's an excerpt:

As data repositories make more data openly available it becomes challenging for researchers to find what they need either from a repository or through web search engines. This study attempts to investigate data users’ requirements and the role that data repositories can play in supporting data discoverability by meeting those requirements. We collected 79 data discovery use cases (or data search scenarios), from which we derived nine functional requirements for data repositories through qualitative analysis. We then applied usability heuristic evaluation and expert review methods to identify best practices that data repositories can implement to meet each functional requirement. We propose the following ten recommendations for data repository operators to consider for improving data discoverability and user’s data search experience:

1. Provide a range of query interfaces to accommodate various data search behaviours.

2. Provide multiple access points to find data.

3. Make it easier for researchers to judge relevance, accessibility and reusability of a data collection from a search summary.

4. Make individual metadata records readable and analysable.

5. Enable sharing and downloading of bibliographic references.

6. Expose data usage statistics.

7. Strive for consistency with other repositories.

8. Identify and aggregate metadata records that describe the same data object.

9. Make metadata records easily indexed and searchable by major web search engines.

10. Follow API search standards and community adopted vocabularies for interoperability.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"Differences in Data Sharing Attitudes and Behaviours"

Flavio Bonifacio has published "Differences in Data Sharing Attitudes and Behaviours" in IASSIST Quarterly.

Here's an excerpt:

This article reports the results of a survey conducted between 18th November and 18th December 2017 about different aspects of data sharing: tools used in building metadata, problems encountered in order to share the data, the propensity to share the data, the satisfaction obtained over different working tasks. After a short description of the data gathering task, the report describes the sample, the univariate distribution of the most important variables related to the work of data archiving and the attitudes concerning the data sharing activity: problems encountered, propensity to share the data, satisfaction obtained. Part of the report illustrates models suitable for interpreting the results and finally gives some advice for promoting data services. Some international comparisons of the results are proposed in the annex.

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

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):

Research Data Curation Bibliography, Version 9 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"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.

Academic Library as Scholarly Publisher Bibliography | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"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.

Academic Library as Scholarly Publisher Bibliography | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap

"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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