Researchers’ attitudes and perceptions towards data sharing and data reuse in the field of food science and technology – Melero – 2020 – Learned Publishing – Wiley Online Library

Abstract:  This work analyses the perception and practice of sharing, reusing, and facilitating access to research data in the field of food science and technology. The study involved the coordination of a focus group discussion and an online survey, to understand and evince the behaviour of researchers regarding data management in that field. Both the discussion group and the survey were performed with researchers from several institutes of the Spanish National Research Council. The lack of a data sharing culture, the fear of being scooped, and confusion between the concepts of the working plan and the data management plan were some of the issues that emerged in the focus group. Respondents’ previous experience with sharing their research data has been mainly in the form of appendices to peer?reviewed publications. From the survey (101 responses), the most important motivations for publishing research data were found to be facilitating the reproducibility of the research, increasing the likelihood of citations of the article, and compliance with funding body mandates. Legal constraints, intellectual property, data ownership, data rights, potential commercial exploitation, and misuse of data were the main barriers to publishing data as open data. Citation in publications, certification, compliance with standards, and the reputation of the data providers were the most relevant factors affecting the use of other researchers’ data. Being recent or recently updated, well documented, with quality metadata and ease of access were the most valued attributes of open research data.

 

COPIM Experimental Publishing Workshop – Part 2: Promoting Experimental Publishing  · COPIM

“Following on from our previous post – summarising our discussion of inhibitions towards experimental publishing – this post looks at how we can stimulate experimentation, looking to understand how it can be encouraged within academic publishing and how some of the inhibitions described previously can be addressed. The following is a summary of our discussions.

Underlying our discussions were the following questions:

How can we stimulate the uptake of experimental publishing and the creation of experimental long-form publications, and the reuse of and engagement with OA books?

What projects/platforms/software do we need to be aware of and in touch with?

What strategies should we devise to stimulate experimentation and reuse?….”

To Spur Software Re-use in Research, CANARIE Awards up to $3.4M to Research Teams to Evolve their Platforms for Use by Other Researchers | CANARIE

“CANARIE announced today the selection of 13 successful projects from its latest Research Software funding call. This funding will enable research teams to adapt their existing research platforms for re-use by other research teams, including those working in different disciplines. As a result, new research teams from across Canada will be able to re-use previously funded and developed software to accelerate their discoveries.

The research workflow (data acquisition, storage, computation/processing, visualization, and data management) is common across all research disciplines. By adapting purpose-built software developed for this workflow so that other research teams can also benefit from them, the impact of public investments in research is maximized and time to discoveries can be accelerated:

More research funding is allocated to research, rather than to the development of software that already exists
Efficiencies in software development enable researchers to devote their time and resources to the research itself …”

New dimensions in data management: Understanding sharing and reuse practices for 3-D data | Wittenberg | College & Research Libraries News

“As 3-D digitization becomes more accessible and research institutions expand support for 3-D modeling, researchers are increasingly leveraging 3-D models and methods. For instance, a paleontologist might use a micro CT scanning process to capture images of the inside of a specimen that would otherwise be destroyed by such an analysis. An archaeologist might use photogrammetry to construct digital representations of artifacts that can then be examined in a way that would be difficult or impossible in a museum setting. The emergence of 3-D modeling as a research practice presents several challenges for libraries working to support and facilitate the dissemination and reuse of 3-D data packages. At present, there is significant work to be done in the community to create a culture and infrastructure that facilitates sharing 3-D research.

Understanding data sharing and reuse among researchers is critical to the success of collection, dissemination, and preservation efforts among memory institutions. Existing literature on data sharing, reuse, trust, quality, and review can inform approaches to evaluating how researchers might share or reuse 3-D data. However, 3-D data have characteristics that make them unique—rapidly changing technology, intersections with lucrative commercial sectors like virtual reality gaming, and the expectation that a model will render—or be accessible for user interaction—when shared. This project offers a unique and necessary contribution to the literature in analyzing creation, reuse, and publishing of 3-D through interviews with expert researchers. This provides substantial value to libraries, archives, and museums that work with 3-D by enabling memory institutions to design digital collection and repository systems that meet patron needs and foster innovation….”

Artificial Intelligence for Data Discovery and Reuse (AIDR) Symposium 2020

“AIDR (Artificial Intelligence for Data Discovery and Reuse) aims to find innovative solutions to accelerate the dissemination and reuse of scientific data in the data revolution. The explosion in the volume of scientific data has made it increasingly challenging to find data scattered across various platforms. At the same time, increasing numbers of new data formats, greater data complexity, lack of consistent data standards across disciplines, metadata or links between data and publications makes it even more challenging to evaluate data quality, reproduce results, and reuse data for new discoveries. Last year, supported by the NSF scientific data reuse initiative, the inaugural AIDR 2019 attracted AI/ML researchers, data professionals, and scientists from biomedicine, technology industry, high performance computing, astronomy, seismology, library and information science, archaeology, and more, to share innovative AI tools, algorithms and applications to make data more discoverable and reusable, and to discuss mutual challenges in data sharing and reuse.

This year, we are following up with a one-day, virtual AIDR Symposium, that provides a place for the community to continue having these conversations and work together to build a healthy data ecosystem. The program will feature invited speakers and panel discussions from a variety of disciplines, including a focused session on COVID-19 data. Audience are highly encouraged to join the conversation by submitting a poster, joining the panel discussions and social hours, chatting on Slack, and participating in collaborative note-taking.”

Final Report and Recommendations of the Data Rescue Project at the National Agricultural Library

“The National Agricultural Library (NAL) identified a need for a framework of guidance to support rapid appraisal and processing for scientific researchers’ collections after being offered collections of scientific data and data-rich materials that required immediate appraisal before acquisition. To this end, the NAL partnered with the University of Maryland’s College of Information Studies (iSchool) to support two Data Rescue Digital Curation Fellows to investigate processes for efficiently identifying, appraising, and processing scientific data out of legacy collections, to support data use and reuse….

The data being ‘rescued’ is intended for inclusion in the USDA’s Agricultural Research Service (ARS) open access data repository, Ag Data Commons….”

Research Practices in the wake of COVID-19 | Advancing Discovery | Springer Nature

“The current climate has put a spotlight onto the value and importance of data sharing and curation and  good data management for boosting the reproducibility and reliability of research.  Its value has never been pulled more sharply into focus as you can see the real life impact of data sharing as we navigate this pandemic. After five years of collaboration on an annual survey of researchers, we can see increasing positive attitudes and behaviours when it comes to data sharing, and yet many researchers and those within the research community still face roadblocks – be this because of challenges in working practices, the lack of tools or services supporting them, or the wider misconception around the role, use and appropriate re-use of data – and this is a problem. 

Since 2016 Figshare, Springer Nature and Digital Science have partnered on the State of Open Data report, based on a survey tracking researcher attitudes and behaviours towards open data sharing and research data management.  The most recent survey launched  in May this year, and with the global pandemic we took the opportunity to ask researchers how Covid-19 was impacting their ability to carry out research, and their views on reuse of data and collaboration. We wanted to get a better understanding of how researcher behaviour was being affected.  When the survey was conducted much of the world was under lockdown which has since eased, however, fears of a second wave are growing. We are aware of the time sensitivity of these insights so rather than wait until October we wanted to release a snapshot of the data  to the community as soon as we could, to allow stakeholders the time to analyse the data to help inform policy and actions going forward as we enter a new phase of the pandemic. The data published this week was from surveys dating from 24th May to 18th June, n=3,436. …”