Category: Open Source Software

"A Guide to Potential Liability Pitfalls for People Running a Mastodon Instance"


The absolute safest thing to do, to shield your own personal assets, is register a LLC (limited liability company), get a separate bank account in the name of the LLC, transfer any assets and liabilities (donations you receive / bills you pay) to the LLC, and get insurance in the name of the LLC. This is obviously complete overkill for anyone who’s running a really small server, especially because the annual fees for LLC registration are likely to exceed whatever amount your users chip in, but if you’re running an open-registration server or you exceed 20-30k users, or you have a lot of personal assets, you should think hard about it and talk to a lawyer.

https://cutt.ly/iM2aXNd

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

Open Source "Academic Tracker: Software for Tracking and Reporting Publications Associated with Authors and Grants"


In recent years, United States federal funding agencies, including the National Institutes of Health (NIH) and the National Science Foundation (NSF), have implemented public access policies to make research supported by funding from these federal agencies freely available to the public. Enforcement is primarily through annual and final reports submitted to these funding agencies, where all peer-reviewed publications must be registered through the appropriate mechanism as required by the specific federal funding agency. Unreported and/or incorrectly reported papers can result in delayed acceptance of annual and final reports and even funding delays for current and new research grants. So, it’s important to make sure every peer-reviewed publication is reported properly and in a timely manner. For large collaborative research efforts, the tracking and proper registration of peer-reviewed publications along with generation of accurate annual and final reports can create a large administrative burden. With large collaborative teams, it is easy for these administrative tasks to be overlooked, forgotten, or lost in the shuffle. In order to help with this reporting burden, we have developed the Academic Tracker software package, implemented in the Python 3 programming language and supporting Linux, Windows, and Mac operating systems. Academic Tracker helps with publication tracking and reporting by comprehensively searching major peer-reviewed publication tracking web portals, including PubMed, Crossref, ORCID, and Google Scholar, given a list of authors. Academic Tracker provides highly customizable reporting templates so information about the resulting publications is easily transformed into appropriate formats for tracking and reporting purposes. The source code and extensive documentation is hosted on GitHub (https://moseleybioinformaticslab.github.io/academic_tracker/) and is also available on the Python Package Index (https://pypi.org/project/academic_tracker) for easy installation.

https://doi.org/10.1371/journal.pone.0277834

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"Who Writes Scholarly Code?"


This paper presents original research about the behaviours, histories, demographics, and motivations of scholars who code, specifically how they interact with version control systems locally and on the Web. By understanding patrons through multiple lenses—daily productivity habits, motivations, and scholarly needs—librarians and archivists can tailor services for software management, curation, and long-term reuse, raising the possibility for long-term reproducibility of a multitude of scholarship.

http://www.ijdc.net/article/view/839

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

"Introducing the FAIR Principles for Research Software"


The FAIR for Research Software (FAIR4RS) Working Group has adapted the FAIR Guiding Principles to create the FAIR Principles for Research Software (FAIR4RS Principles). The contents and context of the FAIR4RS Principles are summarised here to provide the basis for discussion of their adoption. Examples of implementation by organisations are provided to share information on how to maximise the value of research outputs, and to encourage others to amplify the importance and impact of this work.

https://doi.org/10.1038/s41597-022-01710-x

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

It’s Déjà VU All over Again: Artificial Intelligence in Libraries

No doubt you have noticed the increasing number of articles that talk about AI and libraries. You might be tempted to think that this is a new idea. You would be wrong. Gaining stream in the mid-1980s, peaking around 1990, and declining significantly by the late 1990s, libraries experimented with the application of expert systems in a number of functional areas, including abstracting, acquisitions, cataloging, collection development, document delivery, indexing, bibliographic search, and reference.

An expert system is: "a computer system emulating the decision-making ability of a human expert." During the period in question, they were typically developed by libraries using expert system shells. Less frequently, an AI programming language, such as Prolog, was used.

Sharon Manel De Silva’s "A Review of Expert Systems in Library and Information Science" (1977) surveys over 400 papers on this topic.

An example of expert system development during this period was the University of Houston Libraries’ Intelligent Reference Information System project, which produced the Index Expert (expert system shell) and the Reference Expert (Prolog) systems. Reference Expert’s open source code was distributed at no charge to over 500 libraries at their request. The project also conducted a survey of ARL libraries’ expert system activity, which was published as a SPEC Kit.

Academic Library as Scholarly Publisher Bibliography, Version 2 | Digital Scholarship | Digital Scholarship Sitemap

"Open Data Products—a Framework for Creating Valuable Analysis Ready Data"

https://doi.org/10.1007/s10109-021-00363-5

Electronic Theses and Dissertations Bibliography, Version 7 | Digital Curation and Digital Preservation Works | Open Access Works | Digital Scholarship | Digital Scholarship Sitemap