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

"Establishing a Research Data Management Service on a Health Sciences Campus"

Kathryn Vela and Nancy Shin have published "Establishing a Research Data Management Service on a Health Sciences Campus" in the Journal of eScience Librarianship.

Here's an excerpt:

Objective: Given the increasing need for research data management support and education, the Spokane Academic Library at Washington State University (WSU) sought to determine the data management practices, perceptions, and needs of researchers on the WSU Spokane health sciences campus.

Methods: A 23-question online survey was distributed to WSU researchers and research support staff through the campus listserv. This online survey addressed data organization, documentation, storage & backup, security, preservation, and sharing, as well as challenges and desired support services.

Results: Survey results indicated that there was a clear need for more instruction with regard to data management planning, particularly as data management planning addresses the areas of metadata design, data sharing, data security, and data storage and backup.

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

"Data Objects and Documenting Scientific Processes: An Analysis of Data Events in Biodiversity Data Papers"

Kai Li, Jane Greenberg, and Jillian Dunic have self-archived "Data Objects and Documenting Scientific Processes: An Analysis of Data Events in Biodiversity Data Papers."

Here's an excerpt:

The data paper, an emerging scholarly genre, describes research datasets and is intended to bridge the gap between the publication of research data and scientific articles. Research examining how data papers report data events, such as data transactions and manipulations, is limited. The research reported on in this paper addresses this limitation and investigated how data events are inscribed in data papers. A content analysis was conducted examining the full texts of 82 data papers, drawn from the curated list of data papers connected to the Global Biodiversity Information Facility (GBIF). Data events recorded for each paper were organized into a set of 17 categories. . . . The findings challenge the degrees to which data papers are a distinct genre compared to research papers and they describe data-centric research processes in a through way.

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

"Researchers May Need Additional Data Curation Support "

Robin E. Miller has published "Researchers May Need Additional Data Curation Support " in Evidence Based Library and Information Practice.

Here's an excerpt:

Twelve data curation activities were identified as "highly rated" services that academic institutions could focus on providing to researchers. Documentation, Secure Storage, Quality Assurance, and Persistent Identifier were the data curation activities that the majority of participants rated as "most important." Participants identified the data curation practices in place at their institutions, including documentation (80%), secure storage (75%), chain of custody (64%), metadata (63%), file inventory or manifest (58%), data visualization (58%), versioning (56%), file format transformations (55%), and quality assurance (52%). Participants reported low levels of satisfaction with their institutions’ data curation activities.

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

"Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty"

Christie A. Wiley and Margaret H. Burnette have published "Assessing Data Management Support Needs of Bioengineering and Biomedical Research Faculty" in the Journal of eScience Librarianship.

Here's an excerpt:

Results: This study revealed the majority of researchers explore broad research topics, various file storage solutions, generate numerous amounts of data and adhere to differing discipline-specific practices. Researchers expressed both familiarity and unfamiliarity with DMP Tool. Roughly half of the researchers interviewed reported having documented protocols for file names, file backup, and file storage. Findings also suggest that there is ambiguity about what it means to share research data and confusion about terminology such as "repository" and "data deposit". Many researchers equate publication to data sharing.

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

"Persistent Identifiers: The Building Blocks of the Research Information Infrastructure"

Alice Meadows et al. have published "Persistent Identifiers: The Building Blocks of the Research Information Infrastructure" in Insights.

Here's an excerpt:

Persistent identifiers (PIDs)—for people (researchers), places (their organizations) and things (their research outputs and other contributions)—are foundational elements in the overall research information infrastructure. They enable these entities to be uniquely identified and connected, to create reliable links between them. In this paper we describe what PIDs are and how they work. We demonstrate how, if widely adopted, the connections they enable will result in improved access to information, opportunities for collaboration, reduced administrative overhead and, ultimately, increased trust in scholarship and research. To ensure they are fit for purpose, we propose that PID metadata should meet FAIR principles, and that the source of information they contain should be clear and transparent. We also recognize existing usage of persistent identifiers, and invite community support for wider adoption of PIDs in future.

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

"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