Data Soup Webinar, December 16, 2021: hosted by the Data Curation Network and the Journal of eScience Librarianship

Data Soup is a collaboration between the Journal of eScience Librarianship (JeSLIB) and the Data Curation Network to host a series of community focused webinars/discussions to exchange practices for curating research data of different formats or subject areas among data curators. The lineup of the inaugural webinar includes the following speakers and topics from the recent JeSLIB Special Issue: Data Curation in Practice: Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide Alexandra Cooper, Michael Steeleworthy, Ève Paquette-Bigras, Erin Clary, Erin MacPherson, Louise Gillis, and Jason Brodeur, https://escholarship.umassmed.edu/jeslib/vol10/iss3/2 Active Curation of Large Longitudinal Surveys: A Case Study Inna Kouper, Karen L. Tucker, Kevin Tharp, Mary Ellen van Booven, and Ashley Clark, https://doi.org/10.7191/jeslib.2021.1210 Data Curation through Catalogs: A Repository-Independent Model for Data Discovery Helenmary Sheridan, Anthony J. Dellureficio, Melissa A. Ratajeski, Sara Mannheimer, and Terrie R. Wheeler, https://doi.org/10.7191/jeslib.2021.120

Toward open computational communication science: A practical road map for reusable data and code

Computational communication science (CCS) offers an opportunity to accelerate the scope and pace of discovery in communication research. This article argues that CCS will profit from adopting open science practices by fostering the reusability of data and code. We discuss the goals and challenges related to creating reusable data and code and offer practical guidance to individual researchers to achieve this. More specifically, we argue for integration of the research process into reusable workflows and recognition of tools and data as academic work. The challenges and road map are also critically discussed in terms of the additional burden they place on individual scholars, which culminates in a call to action for the field to support and incentivize the reusability of tools and data

Toward Open and Reproducible Environmental Modeling by Integrating Online Data Repositories, Computational Environments, and Model Application Programming Interfaces

Cyberinfrastructure needs to be advanced to enable open and reproducible environmental modeling research. Recent efforts toward this goal have focused on advancing online repositories for data and model sharing, online computational environments along with containerization technology and notebooks for capturing reproducible computational studies, and Application Programming Interfaces (APIs) for simulation models to foster intuitive programmatic control. The objective of this research is to show how these efforts can be integrated to support reproducible environmental modeling. We present first the high-level concept and general approach for integrating these three components. We then present one possible implementation that integrates HydroShare (an online repository), CUAHSI JupyterHub and CyberGIS-Jupyter for Water (computational environments), and pySUMMA (a model API) to support open and reproducible hydrologic modeling. We apply the example implementation for a hydrologic modeling use case to demonstrate how the approach can advance reproducible environmental modeling through the seamless integration of cyberinfrastructure services

Forschungssoftware in Bibliotheken

Software is increasingly acknowledged as valid research output. Academic libraries adapt to this change to become research software-ready. Software publication and citation are key areas in this endeavor. We present and discuss the current state of the practice of software publication and software citation, and discuss four areas of activity that libraries engage in: (1) technical infrastructure, (2) training and support, (3) software management and curation, (4) policies.Software wird zunehmend als gültiges Forschungsergebnis anerkannt. Wissenschaftliche Bibliotheken passen sich diesem Wandel an, um für Forschungssoftware gerüstet zu sein. Softwarepublikation und -zitierung sind hierbei Schlüsselbereiche. Wir präsentieren und diskutieren hier den aktuellen Praxisstand und heben vier Bereiche hervor, in denen Bibliotheken aktiv werden können, um für Forschungssoftware gerüstet zu sein: (1) technische Infrastruktur, (2) Schulung und Support, (3) Management und Kuratierung von Software, (4) Richtlinien.Peer Reviewe

Report on the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2)

This technical report records and discusses the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2). The report includes a description of the alternative, experimental submission and review process, two workshop keynote presentations, a series of lightning talks, a discussion on sustainability, and five discussions from the topic areas of exploring sustainability; software development experiences; credit & incentives; reproducibility & reuse & sharing; and code testing & code review. For each topic, the report includes a list of tangible actions that were proposed and that would lead to potential change. The workshop recognized that reliance on scientific software is pervasive in all areas of world-leading research today. The workshop participants then proceeded to explore different perspectives on the concept of sustainability. Key enablers and barriers of sustainable scientific software were identified from their experiences. In addition, recommendations with new requirements such as software credit files and software prize frameworks were outlined for improving practices in sustainable software engineering. There was also broad consensus that formal training in software development or engineering was rare among the practitioners. Significant strides need to be made in building a sense of community via training in software and technical practices, on increasing their size and scope, and on better integrating them directly into graduate education programs. Finally, journals can define and publish policies to improve reproducibility, whereas reviewers can insist that authors provide sufficient information and access to data and software to allow them reproduce the results in the paper. Hence a list of criteria is compiled for journals to provide to reviewers so as to make it easier to review software submitted for publication as a “Software Paper.

Research Data Management: A review of UAE academic library experience

Purpose: This paper is a review of the status of Research Data Management (RDM) efforts in UAE public university libraries. Approach: The investigation is through examining available literature about the topic using region-specific articles when available, librarian comments, and the information provided by UAE university library websites. Existing lessons and policy documents are sought, and plans suggested for local solutions, suggesting avenues for progress. Findings: Though not a new concept, findings indicate that local RDM activities are emerging, but knowledge of their importance of exists. Research limitations: This review is limited to public university libraries though the results and experiences could be generally relevant to more research establishments. Practical implications: Taking advantage of the existing awareness to organize tangible RDM efforts can facilitate retrieval and availability of data relevant to the region. Value: An intricate range of activities involved in the organization of RDM services is revealed

Out of cite, out of mind: the current state of practice, policy, and technology for the citation of data

PREFACE The growth in the capacity of the research community to collect and distribute data presents huge opportunities. It is already transforming old methods of scientific research and permitting the creation of new ones. However, the exploitation of these opportunities depends upon more than computing power, storage, and network connectivity. Among the promises of our growing universe of online digital data are the ability to integrate data into new forms of scholarly publishing to allow peer-examination and review of conclusions or analysis of experimental and observational data and the ability for subsequent researchers to make new analyses of the same data, including their combination with other data sets and uses that may have been unanticipated by the original producer or collector. The use of published digital data, like the use of digitally published literature, depends upon the ability to identify, authenticate, locate, access, and interpret them. Data citations provide necessary support for these functions, as well as other functions such as attribution of credit and establishment of provenance. References to data, however, present challenges not encountered in references to literature. For example, how can one specify a particular subset of data in the absence of familiar conventions such as page numbers or chapters? The traditions and good practices for maintaining the scholarly record by proper references to a work are well established and understood in regard to journal articles and other literature, but attributing credit by bibliographic references to data are not yet so broadly implemented