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Data and Software Citations

NISO Plus 2023 was a virtual global event which happened around the world on February 14-16, 2023. Building on our track record of engagement and conversation, we brought the same quality of content from 2020-2022 to our 2023 gathering. Dozens of amazing speakers and keynotes from across the globe share their knowledge and expertise on important topics for the information community.
When we read a published scholarly article we rarely, if ever, ask to see the machine actionable version of the text. And yet this hidden version is used to enable much of the downstream services such as automated attribution and credit. When it comes to data and software citations in the reference section, recently the probability of an accurate machine-readable version was very low. For some journals, even zero.

Why you ask? The citation looks just fine in the online version and the downloadable PDF, what could possibly have gone wrong?

Well, there is a plethora of challenges to uncover. First, data and software citations require different validation steps during the production process. Because of this, there machine-readable text is commonly not analyzed correctly, and some text might be altered such that the citation is no longer actionable. How many times of you see that name of the journal in the title of the dataset? Gobs. Further, Crossref requirements are also different for these types of citations causing those citations sent improperly to land on the cutting room floor in many cases.

In this session we will detail the differences in the production process and provide specific guidance to make the necessary corrections. This work has been led by the Journal Task Force for the FORCE11 Software Citation Implementation Working Group.
This presentation was provided by Iain Hrynaszkiewicz of Open Research Solutions during the two-day "NISO Tech Summit: Reflections Upon The Year of Open Science." Day one was held on October 25, 2023.
What constitutes effective project management? Why is it so useful for information professionals to become familiar with and conversant in the processes of project management? This initial overview addresses the benefits and value of project management skills and a context for the rest of the webinar and the discussions that follow. Maureen Adamson will review major approaches from predictive to agile, core concepts, language and terminology as background. We will also review the overall structure of the rest of the webinar, starting with simple projects with clear goals as a foundational understanding, to be followed by more complex projects and situations later in the webinar.
This event will look at bias awareness and the difficulties of appropriately valuing diversity in a work environment. What are the implications for the library in terms of data collection, recruitment practices, and mentoring? How might library leadership encourage applicants from a broad spectrum of cultural backgrounds while avoiding any appearance of double standards? How might technology jobs in the library be made more appealing to a greater range of applicants?
Faced with a highly diverse combination of externally and internally collected data (web visits, gate counter, collection usage, subject analysis, budgets, space use, reference help interactions, etc.), academic libraries have rapidly mastered the value and use of analytics. Whether analyzing prospective subscription packages to determine their value for an institution’s research activities or reviewing usage data drawn from the local digital repository, libraries want to extract meaning from the increasing volume of library data. What does that data look like? How should that data be managed? And in what combinations is that data most enlightening?