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In response to Webb and Tangney (2022) we call into question the conclusion that data collected on Amazon's Mechanical Turk (MTurk) was "at best—only 2.6% valid" (p. 1). We suggest that Webb and Tangney made certain choices during the study-design and data-collection process that adversely affected the quality of the data collected. As a result, the anecdotal experience of these authors provides weak evidence that MTurk provides low-quality data as implied. In our commentary we highlight best practice recommendations and make suggestions for more effectively collecting and screening online panel data. [ABSTRACT FROM AUTHOR]

Psychology is moving increasingly toward digital sources of data, with Amazon's Mechanical Turk (MTurk) at the forefront of that charge. In 2015, up to an estimated 45% of articles published in the top behavioral and social science journals included at least one study conducted on MTurk. In this article, I summarize my own experience with MTurk and how I deduced that my sample was—at best—only 2.6% valid, by my estimate. I share these results as a warning and call for caution. Recently, I conducted an online study via Amazon's MTurk, eager and excited to collect my own data for the first time as a doctoral student. What resulted has prompted me to write this as a warning: it is indeed too good to be true. This is a summary of how I determined that, at best, I had gathered valid data from 14 human beings—2.6% of my participant sample (N = 529). [ABSTRACT FROM AUTHOR]

Copyright of ABI Technik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arab International Journal of Knowledge Management is the property of Arab Institution of Knowledge Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Investment in large neuroscience initiatives is starting to show results, but questions remain over whether they can solve the most fundamental questions about cognition. [ABSTRACT FROM AUTHOR]

Research data is increasingly recognised as an essential output type in the context of research documentation. This paper aims to examine the possible use cases for showcasing research datasets in research information systems. The analysis indicates that three primary use cases play a key role in the implementation of a dataset module in an institutional or in a regional/national CRIS. The paper describes the use cases and places them in the specific context of the University of Vienna, while also referring to existing case studies of other institutions. [ABSTRACT FROM AUTHOR]

This paper examines how privacy measures, such as anonymisation and aggregation processes for email collections, can affect the perceived usefulness of email visualisations for research, especially in the humanities and social sciences. The work is intended to inform archivists and data managers who are faced with the challenge of accessioning and reviewing increasingly sizeable and complex personal digital collections. The research in this paper provides a focused user study to investigate the usefulness of data visualisation as a mediator between privacy-aware management of data and maximisation of research value of data. The research is carried out with researchers and archivists with vested interest in using, making sense of, and/or archiving the data to derive meaningful results. Participants tend to perceive email visualisations as useful, with an average rating of 4.281 (out of 7) for all the visualisations in the study, with above average ratings for mountain graphs and word trees. The study shows that while participants voice a strong desire for information identifying individuals in email data, they perceive visualisations as almost equally useful for their research and/or work when aggregation is employed in addition to anonymisation. [ABSTRACT FROM AUTHOR]

This article discusses the involvement of Polish medical libraries in the field of research data management (RDM). It provides an overview of RDM’s development and its introduction in medical libraries. On the basis of a survey conducted among the staff of Polish medical libraries, the authors outline the librarians’ level of competence, the extent of services they provide and the organisational context of their work. It is stressed that it is crucial to further develop librarians’ qualifications related to RDM, as well as to increase the awareness of libraries’ role in this area among researchers. The authors present conclusions concerning the formal acknowledgement of librarians’ role in the process of RDM, which contributes to the development of both libraries and research institutions.

Responsibly managing research data has become increasingly important for researchers, especially within the database research community. Despite significant progress in best practices, the state-of-the-art in research data storage is lacking from a legal perspective. We introduce the stakeholders and the dynamic nature of their relationships (such as researchers changing affiliation) and observe that no existing infrastructure for research data storage fully meets their requirements. Therefore, we emphasize the need to design a comprehensive system architecture for research data storage that is aligned with legal considerations from the start, rather than as an afterthought. [ABSTRACT FROM AUTHOR]

This paper presents the results of an empirical research study of Croatian scientists' use and management of research data. This research study was carried out from 28 June 2023 until 31 August 2023 using an online questionnaire consisting of 28 questions. The answers of 584 respondents working in science were filtered out for further analysis. About three-quarters of the respondents used the research data of other scientists successfully. Research data were mostly acquired from colleagues from the same department or institution. Roughly half of the respondents did not ask other scientists directly for their research data. Research data are important to the respondents mostly for raising the quality of research. Repeating someone else's research by using their research data is still a problem. Less than one-third of the respondents provided full access to their research data mostly due to their fear of misuse. The benefits of research data sharing were recognized but few of the respondents received any reward for it. Archiving research data is a significant problem for the respondents as they dominantly use their own computers prone to failure for that activity and do not think about long-term preservation. Finally, the respondents lacked deeper knowledge of research data management. [ABSTRACT FROM AUTHOR]

Artificial intelligence could help speedily summarize research. But it comes with risks. [ABSTRACT FROM AUTHOR]

Poorly performing antibodies have plagued biomedical sciences for decades. Several fresh initiatives hope to change this. [ABSTRACT FROM AUTHOR]

With efforts to promote sustainability on the rise, researchers are making gains — but doing science in a green way isn’t always easy. [ABSTRACT FROM AUTHOR]

Academic libraries operate in the digital world in a multitude of globally acting information infrastructures. The new ways of use and demands associated with digitization entail a comprehensive development of their tasks and services. As infrastructure and innovation partners, libraries play an important role in the National Research Data Infrastructure (NFDI). [ABSTRACT FROM AUTHOR]

Metadata is vital for information storage and retrieval from a database or repository. In the case of Research Data Repositories (RDRs), metadata can be a potent tool for describing and identifying data. Further, producing the metadata is indispensable for fostering data reuse. A filtered view of the registry of research data repositories, re3data.org, depicts no uniform patterns or standards for metadata in the case of RDRs, and the metadata elements and practices differ from RDR to RDR. The present study describes the features of a select number of RDRs and analyzes their metadata practices: Harvard Dataverse, Dryad, Figshare, Zenodo, and the Open Science Framework (OSF). It further examines the total number of metadata elements, common metadata elements, required metadata elements, and item-level metadata. Results indicate that even though Harvard Dataverse has the most metadata elements, Dryad provides rich metadata concerning item level. This study suggests a common metadata framework, richer metadata elements, and more features to make the research data's interoperability possible from one RDR to another. [ABSTRACT FROM AUTHOR]

The benefits of research data sharing abound in the literature. However, some factors define how researchers and clinicians approach the challenges surrounding sharing human movement health research data. To describe the perceptions of human movement researchers and clinicians on the barriers and facilitators to research data sharing in Africa. A qualitative descriptive design with a purposive sampling method was used. In-depth interviews with human movement researchers and clinicians across Africa were conducted online via Microsoft Teams. Sixteen (n = 16) participants took part in this study. This sample size was representative of East, West, Northern, and Southern Africa. Efforts made to engage with participants in Central Africa were unsuccessful. Five themes emerged: 1) the researcher-clinician gap; 2) technological pros and cons in Africa; 3) cost matters; 4) bureaucracy and ethical factors; and 5) the unique African perspective. Mainly, barriers rather than facilitators to data sharing exist among African human movement researchers and clinicians. There needs to be a societal and psychological shift through reorientation to encourage data sharing among African human movement researchers and clinicians. [ABSTRACT FROM AUTHOR]

This paper explores the landscape of research data in the humanities in the European context, delving into their diversity and the challenges of defining and sharing them. It investigates three aspects: the types of data in the humanities, their representation in repositories, and their alignment with the FAIR principles (Findable, Accessible, Interoperable, Reusable). By reviewing datasets in repositories, this research determines the dominant data types, their openness, licensing, and compliance with the FAIR principles. This research provides important insight into the heterogeneous nature of humanities data, their representation in the repository, and their alignment with FAIR principles, highlighting the need for improved accessibility and reusability to improve the overall quality and utility of humanities research data. [ABSTRACT FROM AUTHOR]

Too often, journal assessments of potentially unreliable research are superficial, opaque and prolonged. Changes to the guidance given by the Committee on Publication Ethics could tighten up the process. [ABSTRACT FROM AUTHOR]

Researchers have tried a bunch of strategies to get more negative results into the literature. Nature asks whether they are working. [ABSTRACT FROM AUTHOR]

Copyright of ABI Technik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Researchers need to be able to find, access, and use data to participate in open science. To understand how users search for research data, we analyzed textual queries issued at a large social science data archive, the Inter-university Consortium for Political and Social Research (ICPSR). We collected unique user queries from 988,475 user search sessions over four years (2012-16). Overall, we found that only 30% of site visitors entered search terms into the ICPSR website. We analyzed search strategies within these sessions by extending existing dataset search taxonomies to classify a subset of the 1,554 most popular queries. We identified five categories of commonly-issued queries: keyword-based (e.g., date, place, topic); name (e.g., study, series); identifier (e.g., study, series); author (e.g., institutional, individual); and type (e.g., file, format). While the dominant search strategy used short keywords to explore topics, directed searches for known items using study and series names were also common. We further distinguished exploratory browsing from directed search queries based on their page views, refinements, search depth, duration, and length. Directed queries were longer (i.e., they had more words), while sessions with exploratory queries had more refinements and associated page views. By comparing search interactions at ICPSR to other natural language interactions in similar web search contexts, we conclude that dataset search at ICPSR is underutilized. We envision how alternative search paradigms, such as those enabled by recommender systems, can enhance dataset search. [ABSTRACT FROM AUTHOR]

Copyright of Métodos de Información is the property of Col·legi Oficial de Bibliotecaris i Documentalistes de la Comunitat Valenciana (COBDCV) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista General de Información y Documentación is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

What are the motivations and sought gratifications leading information science researchers to share and to reuse research data? Research data are both datasets and supplementary materials such as interview guides or questionnaires. The theoretical backgrounds of this study are the Lasswell Formula of Communication, the Uses and Gratifications Theory, and the Self-determination Theory, which formed the basis for the construction of an interview guide and the interpretation of the interview transcripts. We performed 11 in-depth interviews with German information scientists, all with experiences with data. The results demonstrate that research data sharing is not a rare practice among information scientists. Due to problems with different information horizons of the sharing and the reusing researchers, the reusing of data sets is much rarer than the reuse of supplementary materials. [ABSTRACT FROM AUTHOR]

The Digitalia MUNI ARTS - a local node of the LINDAT/CLARIAH-CZ research infrastructure at the Faculty of Arts of Masaryk University constitutes a repository in the Islandora system. It is used for long-term preservation of research data together with their research environment in the form of digital platforms. We transfer the digital outputs of humanities scholars research to the repository according to a set plan, which is based on best practice recommendations for project management and digital curation. In this paper, we present how the results of interviews with platform developers and infrastructure stakeholders translate into the curation workflow, and a resulting model for migrating digital platforms to the repository. Reflecting on three types of problems we encountered during the implementation of platforms into the repository - communication problems, problems of external dependence, and management problems - we describe a modification of the migration process. We present six recommendations for repository administrators and curators in an academic setting - holding an introductory meeting with developers, researching significant and relevant theories of knowledge domain, consulting license experts, prioritizing requirements, and preparing handover protocol and progress reports. [ABSTRACT FROM AUTHOR]

Background. Open Science seeks to render research outputs visible, accessible, reusable. The Open Science framework is currently evolving vigorously due, among others reasons, to the UNESCO Open Science Recommendation adopted in November 2021. In this context, it is relevant to better visualize and describe the relationships that hold among the direct protagonists of this changing landscape: research teams and their research outputs, namely: articles, software and data, as their comprehension will certainly contribute to foster better Open Science practices. Method. In this work we review and describe, through the information collected in a large number of bibliographic references, the current changing trends involving some essential, defining, characteristics and behaviors of the main components of the scientific production, namely, research teams and three kinds of research outputs they produce in many scientific areas. This comparative study is based, among others, in our recent work on the evolving concepts of research software, research data in the context of Open Science. Results. In this work we observe and document some key features in this evolving landscape such as the changing and extended roles of research team members; the need to develop a new citing and referencing culture for articles, but specially for research software and data; the rising relevance of open access (to publications, software, data) policies all over the world; the existence of some barriers and difficulties like the regulations concerning academic research close to industry, or other technological applications; the need to develop standards for the “right to be forgotten”; the need to consider the impact of Open Science costs for less favored communities, countries, institutions. . . Conclusions. This calls for the urgent need to observe and depict further this changing Open Science ecosystem, and to propose –as we have partially attempted in this work– new concepts to analyze this context as well as to contribute to ongoing research-on-research and to improve the implementation of Open Science practices, in order to foster better ways towards a sound, inclusive and fairer Open Science landscape. [ABSTRACT FROM AUTHOR]

Objective: Increases in data-intensive research at colleges and universities is driving demand for data services provided by academic libraries. The current work investigates the distribution of library data services, how such services are offered, and the effect of resourcing on the amount of services offered by a library. Methods: We used a web-based inventory of 25 academic libraries at U.S. Research 1 (R1) Carnegie institutions to assess the state of data services at university libraries. We categorized and quantified services, and tested for an effect of library resourcing on the size of library data service portfolios.Results: Support for data management and geospatial services was relatively widespread, with increasing support in areas of data analyses and data visualization. There was significant variation among services in the modality in which they were offered (web, consult, instruction) and library resourcing had a significant effect on the number of data services a library offered.Conclusions: While a core subset of these data services are offered at most academic libraries, more specialized topics are restricted to well-resourced libraries. In light of the influence of resource scarcity on the number of services a library can offer, intra- and inter-campus partnerships will be critical to ensure campus support for data service needs.

Objective: This study was aimed at analyzing and disseminating the fossil wood collection data stored in the thin slide sections of the paleobotany collection of the Department of Paleontology and Stratigraphy of the Institute of Geosciences of a university in Southern Brazil. Thin sheets of petrified wood are described. Research data used in geosciences specifically seek to develop a model for the use of this type of sheet in paleobotany, enabling visualization of its representativeness in studies published over 40 years to obtain the anatomical characteristics of fossil woods and define their systematic affinities as a specific typology of research data in geosciences. Methods: The methodology involved interviewing a paleobotanical specialist and using different techniques applied in metric studies to map scientific production. Thus, a dataset of (20) thin slide sections of petrified fossil wood used in “Stressing environmental conditions in the “petrified forest” from the Mata Sequence in the Triassic context of the Paraná Basin,” a paper published by the Journal of South American Earth Sciences (DOI:10.1016/j.jsames.2023.104415), was used. Depending on the methodology, these thin petrified wood sheets can reveal paleoclimatic signatures based on the anatomical characteristics of the fossil wood. In addition to this case study, which represents a collection of more than (2.000) thousand blades of fossil wood and approximately 40 years of research, the paleobotanical collection of the department is reused in methodology classes. The collection comprises a database created by research physicists that provides information on anatomical features, systematic affinities, paleoclimatic conditions, and paleoenvironmental insights. Potential for reuse: The reuse, registration, storage, identification, and preservation of thin slide sections as a type of research data used in paleobotany aims to improve the methodology associated with the organization of the physical database of the institution. The research data and blades of fossil wood are being digitized, and soon will be available under the CC BY 4.0 license in the ZENODO repository, according to the sample described here in this data paper (DOI Mendeley:10.17632/b8phfcsync.1). Furthermore, the data can be reused in optical and electronic scanning microscopy software.

Researchers need to be able to find, access, and use data to participate in open science. To understand how users search for research data, we analyzed textual queries issued at a large social science data archive, the Inter-university Consortium for Political and Social Research (ICPSR). We collected unique user queries from 988,475 user search sessions over four years (2012-16). Overall, we found that only 30% of site visitors entered search terms into the ICPSR website. We analyzed search strategies within these sessions by extending existing dataset search taxonomies to classify a subset of the 1,554 most popular queries. We identified five categories of commonly-issued queries: keyword-based (e.g., date, place, topic); name (e.g., study, series); identifier (e.g., study, series); author (e.g., institutional, individual); and type (e.g., file, format). While the dominant search strategy used short keywords to explore topics, directed searches for known items using study and series names were also common. We further distinguished exploratory browsing from directed search queries based on their page views, refinements, search depth, duration, and length. Directed queries were longer (i.e., they had more words), while sessions with exploratory queries had more refinements and associated page views. By comparing search interactions at ICPSR to other natural language interactions in similar web search contexts, we conclude that dataset search at ICPSR is underutilized. We envision how alternative search paradigms, such as those enabled by recommender systems, can enhance dataset search.

Virtual platforms have revolutionized distance education, making it accessible worldwide and empowering scientists, academicians, and researchers to access knowledge effortlessly. These platforms provide flexibility, allowing the users to tailor their learning experience to their needs and integrating knowledge into their work. Reproducibility is crucial in cancer research, and researchers integrate data analysis into virtual or electronic learning (e-Learning) platforms to facilitate replication and verification, promoting transparency and reliability. This integration enhances accessibility and enables collaboration among scientists and stakeholders in the fight against cancer. Virtual learning offers written and audio-visual communication benefits facilitated by electronic and web-enabling advancements. In the dynamic virtual realm, researchers transcend limitations, exchange knowledge, and push the boundaries of cancer research. Virtual platforms provide time efficiency and financial freedom, while advanced tools support data analysis and facilitate new insights. These tools unlock hidden patterns and accelerate the pace of discovery. The digital ecosystem generates new ideas, improves research methodology, and enhances research quality. Limitless collaboration and advanced tools propel cancer research, unravelling complex data with precision and innovation. The potential of cyberspace to revolutionize scientific research in the future, therefore, is promising.

Data gaps are a significant lack of data about marginalized groups existing due to unequal power relations (D’Ignazio and Klein, 2020). They both perpetuate and result in a dominance of male, white, hetero, and cis perspectives in how we make sense of and interact with the world. The most prominent data gap is the gender data gap notably described by Criado-Perez (2020). However, not only women, but all marginalized groups are affected by such gaps, as data about them are frequently not collected due to a disregard on behalf of those in power of the need to do so. LGBTIQ+ people, considered a ‘hidden population’ by demographers, are a case in point. The acronym is used to refer to lesbian, gay, bisexual, trans, intersex, and queer people, as well as all people with non-normative sexual or gender identities, including asexual and agender people, who do not consider themselves as falling under one of these labels. A first step towards identifying and closing data gaps is to take stock of data that already exist. In this paper we give an overview of LGBTIQ+ data in European social science archives. We researched all data archives of CESSDA ERIC, the Consortium of European Social Science Data Archives, and found 66 LGBTIQ+ datasets in 9 of the 34 member and associated archives and 1 former member archive. We discuss characteristics, coverages, and findability of the identified datasets and approach the question of potential data gaps by analyzing the keywords assigned to each dataset by the archive.