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A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small‐angle X‐ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS‐tools library is a community‐driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python‐native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS‐tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethylammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry. [ABSTRACT FROM AUTHOR]

This study examines trends in open access article processing charges (APCs) from 2011 to 2021, building on a 2011 study by Solomon and Björk. Two methods are employed, a modified replica and a status update of the 2011 journals. Data are drawn from multiple sources and datasets are available as open data. Most journals do not charge APCs; this has not changed. The global average per‐journal APC increased slightly, from 906 to 958 USD, while the per‐article average increased from 904 to 1,626 USD, indicating that authors choose to publish in more expensive journals. Publisher size, type, impact metrics and subject affect charging tendencies, average APC, and pricing trends. Half the journals from the 2011 sample are no longer listed in DOAJ in 2021, due to ceased publication or publisher de‐listing. Conclusions include a caution about the potential of the APC model to increase costs beyond inflation. The university sector may be the most promising approach to economically sustainable no‐fee OA journals. Universities publish many OA journals, nearly half of OA articles, tend not to charge APCs and when APCs are charged, the prices are very low on average. [ABSTRACT FROM AUTHOR]

Despite large public investments in facilitating the secondary use of data, there is little information about the specific factors that predict data's reuse. Using data download logs from the Inter‐university Consortium for Political and Social Research (ICPSR), this study examines how data properties, curation decisions, and repository funding models relate to data reuse. We find that datasets deposited by institutions, subject to many curatorial tasks, and whose access and preservation is funded externally, are used more often. Our findings confirm that investments in data collection, curation, and preservation are associated with more data reuse. [ABSTRACT FROM AUTHOR]

Scientifically significant sites are the source of, and long‐term repository for, considerable amounts of data—particularly in the natural sciences. However, the unique data practices of the researchers and resource managers at these sites have been relatively understudied. Through case studies of two scientifically significant sites (the hot springs at Yellowstone National Park and the fossil deposits at the La Brea Tar Pits), I developed rich descriptions of site‐based research and data curation, and high‐level data models of information classes needed to support integrative data reuse. Each framework treats the geospatial site and its changing natural characteristics as a distinct class of information; more commonly considered information classes such as observational and sampling data, and project metadata, are defined in relation to the site itself. This work contributes (a) case studies of the values and data needs for researchers and resource managers at scientifically significant sites, (b) an information framework to support integrative reuse at these sites, and (c) a discussion of data practices at scientifically significant sites. [ABSTRACT FROM AUTHOR]

In recent years, different cultural institutions have made efforts to spread culture through the construction of a unique search interface that integrates their digital objects and facilitates data retrieval for lay users. However, integrating cultural data is not a trivial task; therefore, this work performs a systematic literature review on data aggregation workflows, in order to answer five questions: What are the projects? What are the planned steps? Which technologies are used? Are the steps performed manually, automatically, or semi‐automatically? Which perform semantic search? The searches were carried out in three databases: Networked Digital Library of Theses and Dissertations, Scopus and Web of Science. In Q01, 12 projects were selected. In Q02, 9 stages were identified: Harvesting, Ingestion, Mapping, Indexing, Storing, Monitoring, Enriching, Displaying, and Publishing LOD. In Q03, 19 different technologies were found it. In Q04, we identified that most of the solutions are semi‐automatic and, in Q05, that most of them perform a semantic search. The analysis of the workflows allowed us to identify that there is no consensus regarding the stages, their nomenclatures, and technologies, besides presenting superficial discussions. But it allowed to identify the main steps for the implementation of the aggregation of cultural data. [ABSTRACT FROM AUTHOR]

A 5‐year project to study scientific data uses in geography, starting in 1999, evolved into 20 years of research on data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. By emulating the "team science" approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. Building upon Paul N. Edwards's model of "making global data"—collecting signals via consistent methods, technologies, and policies—to "make data global"—comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. We reflect on continuity over generations of students and staff, transitions between grants, transfer of legacy data between software tools, research methods, and the role of professional data managers in the social sciences. [ABSTRACT FROM AUTHOR]

Social media data (SMD) offer researchers new opportunities to leverage those data for their work in broad areas such as public opinion, digital culture, labor trends, and public health. The success of efforts to save SMD for reuse by researchers will depend on aligning data management and archiving practices with evolving norms around the capture, use, sharing, and security of datasets. This paper presents an initial foray into understanding how established practices for managing and preserving data should adapt to demands from researchers who use and reuse SMD, and from people who are subjects in SMD. We examine the data management practices of researchers who use SMD through a survey, and we analyze published articles that used data from Twitter. We discuss how researchers describe their data management practices and how these practices may differ from the management of conventional data types. We explore conceptual, technical, and ethical challenges for data archives based on the similarities and differences between SMD and other types of research data, focusing on the social sciences. Finally, we suggest areas where archives may need to revise policies, practices, and services in order to create secure, persistent, and usable collections of SMD. [ABSTRACT FROM AUTHOR]

Citations are the cornerstone of knowledge propagation and the primary means of assessing the quality of research, as well as directing investments in science. Science is increasingly becoming "data-intensive," where large volumes of data are collected and analyzed to discover complex patterns through simulations and experiments, and most scientific reference works have been replaced by online curated data sets. Yet, given a data set, there is no quantitative, consistent, and established way of knowing how it has been used over time, who contributed to its curation, what results have been yielded, or what value it has. The development of a theory and practice of data citation is fundamental for considering data as first-class research objects with the same relevance and centrality of traditional scientific products. Many works in recent years have discussed data citation from different viewpoints: illustrating why data citation is needed, defining the principles and outlining recommendations for data citation systems, and providing computational methods for addressing specific issues of data citation. The current panorama is many-faceted and an overall view that brings together diverse aspects of this topic is still missing. Therefore, this paper aims to describe the lay of the land for data citation, both from the theoretical (the why and what) and the practical (the how) angle. [ABSTRACT FROM AUTHOR]

Systematic study of data sharing by citizen scientists will make a significant contribution to science because of the growing importance of aggregated data in data-intensive science. This article expands on the data sharing component of a paper presented at the 2013 ASIST conference. A three-phase project is reported. Conducted between 2011 and 2013 within an environmental voluntary group, the Australian Plants Society Victoria ( APSV), the interviews of the first phase are the major data source. Because the project revealed the importance of data sharing with professional scientists, their views are included in the literature review where four themes are explored: lack of shared disciplinary culture, trust, responsibility and controlled access to data, and describing data to enable reuse. The findings, presented under these themes, revealed that, within APSV, sharing among members is mostly generous and uninhibited. Beyond APSV, when online repositories were involved, barriers came very strongly into play. Trust was weaker and barriers also included issues of data quality, data description, and ownership and control. The conclusion is that further investigation of these barriers, including the attitudes of professional scientists to using data contributed by citizen scientists, would indicate how more extensive and useful data sharing could be achieved. [ABSTRACT FROM AUTHOR]

Accurate and detailed data recording is indispensable for documenting archeological projects and for subsequent information exchange. To prevent comprehension and accessibility issues in these cases, data infrastructures can be useful. The establishment of such data infrastructures requires a clear understanding of the business processes and information flows within the archeological domain. This study attempts to provide insights into how information is managed in Flemish archeological processes and how this management process can be enhanced: an exploratory study based on an analysis of the new Flemish Immovable Heritage Decree, informal interviews with Flemish archeological organizations, and the results of an international survey. Three main processes, in which certified archeologists and the Flemish Heritage agency are key actors, were identified. Multiple types of information, the majority of which contain a geographical component, are recorded, acquired, used, and exchanged. Geographical information systems ( GIS) and geodatabases therefore appear to be valuable components of an archeology-specific data infrastructure. This is of interest because GIS are widely adopted in archeology and multiple Flemish archeological organizations are in favor of a government-provided exchange standard or database templates for data recording. Furthermore, free and open source software is preferred to ensure cost efficiency and customizability. [ABSTRACT FROM AUTHOR]

In recent years, sociolinguists have become increasingly focused on and more explicit about ensuring the preservation, and accessibility, of their data. This increased focus on our data has involved new lines of work explicitly on data management and, in turn, has led to important (re)considerations of the nature of sociolinguistic data and the metadata of importance for sociolinguist research. While many of the papers in this special issue focus on issues having to do with specific metadata, in this paper, I consider archiving and sharing data more generally. I attend to three specific problem areas, portability access and security, and discoverability and relevance, providing advice as well as some 'food for thought' discussions for each. [ABSTRACT FROM AUTHOR]