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Big Data analysis provides the opportunity to process data and to generate information that culminates in new knowledge, which can leverage innovation and competitive advantage for the business. In this context, Knowledge Management processes can enhance the flow of information generated from data analysis and transform individual knowledge into organizational knowledge. This paper focused on understanding if the published literature discusses librarians’ performance in the corporate environment regarding Knowledge Management in the context of Big Data. Through a literature review, this paper presents some reflections on how Knowledge Management can be accomplished in the context of Big Data. Furthermore, it checks which competencies are assigned to librarians so that they can act in an organizational context to work with Knowledge Management in a Big Data approach; and finally, it tries to find how librarians can address Knowledge Management in the context of Big Data.

Daten spielen in unserer zunehmend digitalisierten Welt eine immer größere Rolle. Dies gilt natürlich auch für die Arbeitsfelder der Sozialen Arbeit und Sozialwirtschaft. Ziel sollte es sein, diese Daten nicht einfach nur zu erheben und zu erfassen, sondern sie systematisch in Entscheidungen einfließen zu lassen. In diesem Beitrag wird das Konzept des dateninformierten Handelns vorgestellt und aufgezeigt, welchen Mehrwert dies für Organisationen der Sozialen Arbeit und Sozialwirtschaft hat. Hierbei wird besonders darauf eingegangen, wie in einem solchen Prozess auch fachliche Daten berücksichtigt werden können, welche ersten Schritte Organisationen gehen können und welche Herausforderungen dabei gelöst werden müssen.

In today’s data-filled society, institutions are abundant with information but lacking in the transformation of information to knowledge and further utilization of knowledge to support actionable change. The focus of the present study was to develop an instrument to gauge institutional maturity with regard to the level in which information is utilized to support decisions, planning, and change. The findings from a field test yielded a conceptual model to assess institutional maturity of information utilization. Additionally, the pilot of the IUMI instrument found high rates of internal reliability and may be used as a catalyst to spark institutional movement towards a culture of evidence-informed practice.

This presentation looks at how quantitative data is being used in social science teaching in UK Higher Education. Discussions on the teaching of research methods have emphasised the role of data as a pedagogical hook; data is important for making research methods engaging and knowable to students. We consider the question of what data lecturers use in their teaching and how and why do they use it. We explored these questions with lecturers in a mixed method study that combined a survey and interviews and found how lecturers identify ‘what works.’ What works is shaped by multiple factors including the work involved in finding and preparing data for teaching as well as wider orientations towards teaching quantitative research and data skills as part of a broader curriculum. The talk concludes with insights into what makes good data for teaching and a discussion of the challenges around introducing programming into the curriculum.

The NavCal program at UC Berkeley does exciting work, assisting incoming nontraditional students in navigating the campus through a supportive, hands-on approach. “Non-traditional” includes low-income, first-generation college attendee, transfer and other students who may have challenges adjusting to a large, complex research university environment. A large majority of NavCal participants go on to gain acceptance into research fellowships and nationally-recognized graduate school pipeline programs. The Library has a positive partnership with NavCal and a strong interest in campus-wide information and data literacy, so it made sense for the library to offer customized data literacy workshops for NavCal students… until an advisor said, “what they really need is to get broader training in getting ready to take on research assistant positions.” From this idea, Ready4Research was born: R4R is a 3-hour workshop to support students in learning about and getting ready to participate in research, as research assistants and researchers themselves, with data and data literacy embedded into the content. Since its initial offering in Summer, 2021, Ready4Research has been offered each semester, to positive reviews and robust attendance. Aiming broadly at social sciences research, topics include: how research happens, what kinds of jobs research assistants do, what kind of data they may encounter, some approaches to analyzing and visualizing data, deciding what kinds of jobs to apply for, how to apply for them, how to develop their own research content to present and publish, tips from NavCal alumni, and more. Attendees say that the exposure to the world of research at Berkeley (Cal) has opened their eyes to new possibilities for their academic careers. The workshop has also been revised for different formats and audiences, and ideas for further dissemination are in the works. This poster will outline the program, its development over time, and future plans for improvement.

Based on the work by three academic data professionals who created the Data on Racialized Populations in Canada guide, the presenters will go into more detail about finding data for First Nations, Inuk and Metis Peoples in Canada. The presentation will explore the historical nature of some Indigenous data sources with examples that will be provided of how the federal government of Canada has collected data on Indigenous peoples, often through a colonial lens. There will be a focus on how terminology necessary for searching may include language that can be problematic and/or offensive to contemporary users. Accordingly, the content will illustrate how the vocabulary used to refer to racial, ethnic, religious and cultural groups is specific to the time period when the data was collected and does not reflect the attitudes and viewpoints of contemporary society. More recent trends of inclusive terminology will also be explored and how this reaffirms Indigenous identity in the data. Finally, an overview of data sovereignty will end the presentation to allow insight into how data is collected, gives ownership and is used by Indigenous communities through relevant resources.

Ageism is a bias that has to do with discriminatory practices and prejudicial attitude towards older people in the society. Ageist submission has always been to foster digital divide. However, technology and ageism is to be considered as having a complimentary effect on each other. Technology can as well be used as a two-edged sword, that is, as a weapon of discrimination or as a tool to foster social justice. Technology in the era of datafication can be of help in educating and eliminating the “ism” in terms of technological design, accessibility and use; which as well demands a paradigm shift from a mindset of bias. This paper looks at the two sides of the sword of technology and ageism and emphasizes on fostering social justice.

Since its launch in 1996, the Social Science Japan Data Archive (SSJDA) has been collecting and storing raw data provided by depositors that are obtained mainly from social surveys. These data are then widely shared for academic purposes, or secondary analysis in particular. Although SSJDA has long been responsible for creating the metadata, a new self-archiving system was developed recently that allows the depositors to register their raw data and create the metadata by themselves. This self-archiving system is expected to improve the efficiency of data archiving and sharing in the long run; however, there are also several challenges to overcome. For example, many depositors, including academic researchers, are unexperienced in creating the metadata in a FAIR manner. Therefore, SSJDA is also planning to provide training programs, such as self-learning materials to the depositors.

Policies communicate expectations to stakeholders, codify legal and administrative procedures, and espouse underlying values. However, often moving from policy to actual practice requires interpretation, the development of new procedures, and has various resource implications. In the United States, the federal government has been expanding policies related to the management and sharing of research data with the NIH Data Management and Sharing policy in effect as of January 2023 and other agencies developing and revising policies in response to the recent “Nelson” OSTP memo on immediate and equitable access to research. At Duke University, the research administration has also been working to implement a new institutionally-based research data policy. As information professionals situated within a library part of our role is to help researchers navigate this changing policy landscape. Likewise, we are stakeholders when considering the development of resources and services to support policy implementation. We may also take on the role of advocates for values we hold, such as the value of openness or equity in the research enterprise. How can we balance these different roles? What are some common challenges or pitfalls? What makes the library’s position in this policy space unique? In this presentation, we will share some reflections from our recent experiences at Duke navigating this complex landscape and engage the audience in a discussion about their experiences.

In Spring 2022, Georgia State University Library's Research Data Services Department launched the GSU Data Ready! Badges data literacy micro-credentialing initiative: https://lib.gsu.edu/data-ready. In this poster session, we will present: (1) the content of our two badges tracks — data literacy foundations and software/coding training [14 separate badges]; (2) the online platforms [Canvas and Badgr] used for automated badge earning and distribution; (3) assessment of program success; and (4) ways in which other institutions might develop similar initiatives. The poster session format will optimize attendee engagement via extended Q&A and demonstration opportunities.

186 Personen haben am 23. Februar 2023 am Community-Workshop „Kartierung der Datenkompetenz-Angebote“ teilgenommen. Sowohl Beteiligte der NFDI-Konsortien als auch Akteur:innen der Forschungsdatenmanagement (FDM)-Landesinitiativen, universitärer Einrichtungen, Hochschulen und Forschungseinrichtungen haben die vierstündige Online-Veranstaltung bereichert. 26 Weiterbildungsangebote haben sich in zweiminütigen Kurzpräsentationen der Community vorgestellt und weitere 53 Angebote sind auf generischen Steckbriefen sichtbar geworden. Die Verortung der vielfältigen Angebote auf der Deutschlandkarte sowie Links zu den Webpräsenzen können im Workshopbericht eingesehen werden. Zusätzlich zu der Übersicht verschiedener Datenkompetenz Weiterbildungsangebote werden im Rahmen des Berichtes die Diskussionen des Workshops zusammengefasst. Dabei wird reflektiert, wo das Kompetenzfeld im Diskurs steht und wie die Weiterentwicklung gemeinsam gestaltet werden kann. Von dem Bedarf nach mehr fachspezifischen und anwendungsorientierten Weiterbildungsangeboten bis hin zu dem Wunsch nach verstetigten personellen Ressourcen und der Harmonisierung der vielfältigen Angebote, wurde eine breite Palette an Bedarfen und notwendigen nächsten Schritten diskutiert. Die Veranstaltung wurde von der engagierten Community zum Austausch genutzt und es zeigte sich ein großer Konsens, gemeinsam aktiv die Datenkompetenzlandschaft gestalten zu wollen.

Open data efforts and initiatives tend to focus on the curation and publishing of accessible data for people to use. Conversations on open data commonly surrounds the technology and methodology used to advance these efforts, while there are not as many topics on the people who will be using these data. This talk proposes that the foundation of successful open data program lies in improving data literacy, especially if the intention of open data is public empowerment. Data literacy is the essential feedback loop to enhance the demand and quality of open data and its use. This talk will review the history of literacy (to read and write) and its relationship with industrialization to draw comparisons to our current data industry, and ultimately identify lessons to help us build better data literacy and open data programs.

Intersect’s mission is to help researchers to be more efficient and effective in their research; reducing the time to move from an idea to a tested solution. As a leading provider of digital skills training for researchers in the Australasian region, Intersect provides an extensive range of technology focused training to researchers and higher degree research (HDR) students across Australia. This training ranges from awareness to advanced levels; is delivered interactively either face-to-face or online; and covers categories such as Research Computing, Programming, Data Science, Data Analytics, Machine Learning (ML) & Artificial Intelligence (AI), Statistics, Data Visualisation, Data Collection, and Data Management. Intersect continually revises, updates, and expands its course catalogue, ensuring researchers always have access to the most relevant and useful research training. Our hands-on, instructor-led, live, interactive training is delivered by over 25 highly experienced instructors and is targeted at enhancing the capabilities of researchers in digital tools and technologies. Our research and training expertise extends across various disciplines including, but not limited to: ICT, Data Science, Linguistics, Engineering, Statistics, Bioinformatics, Health & Medical Sciences, Materials Science, Sports Science, Spatial Analytics, Computational Chemistry, Numerical Modelling, Behavioural Science, and Social and Political Sciences. In 2022, Intersect has trained a total number of 5,664 researchers in 300 courses (229 training days). The average attendance rate was approximately 76% based on the capacity (or registration number) of the courses. From those attendees, 4,419 or approximately 78% attended the courses Intersect scheduled at their local university while 1,245 or about 22% attended Intersect courses through the consortium of Intersect member universities. Intersect members are located in NSW, VIC, SA, and ACT, where the majority of the training program takes place. However, the Intersect training courses are also attended by HDR students and researchers from other states and territories, such as Western Australia (WA), Tasmania (TAS), and Queensland (QLD), as well as in national organisations mainly due to the NCI-Intersect Training Partnership. The NCI-Intersect training partnership includes running a series of training courses aimed at users who may be new to NCI's high-performance computing environment, as well as experienced users looking for a refresher. In 2022, most attendees (2,682) are from New South Wales (NSW) universities, organisations, and government departments constituting about 47% of the total attendees. 1,147 and 1,124 HDR students and researchers from Victoria (VIC) and South Australia (SA), respectively, attended Intersect training courses in 2022 representing 20.7% and 20.4% of the total attendees. The fourth largest cohort was from national organisations with approximately 350 attendees, followed by ACT with 260 attendees. Smaller numbers of attendees were from other states and territories. To evaluate the quality of the training delivery, Intersect asks attendees to complete a course evaluation survey at the end of each course, where a Net-Promoter Score (NPS) is also measured. Intersect’s NPS during this period was +70 based on 2,090 responses (~37% of attendees) which is considered outstanding. Furthermore, the average scores of the primary metrics for measuring the quality of the training delivery exceed 9.1 out of 10, which indicates that feedback from participants is excellent. This report summarises the Research Digital Skills Training Program provided by Intersect Australia across Australia for the calendar year 2022 as well as useful insights on historical trends.

Broadly, the information science field has grown to encompass a more extensive set of data science competencies as the role of data, data literacy, and data visualization has grown. Schwabish explains, "now more than ever, content must be visual if it is to travel far" (2021). Through coding selected years across 20 years of JASIST journal, from the years 2001, 2006, 2011, 2016, and 2021; we were able to not only inventory the proportion of images that are data visualizations but also to identify trends and changes over time in the data visualizations contained in JASIST publications. Findings suggested that overall, the importance and complexity of data visualizations in publications increased over the date range studied. Additionally, as data visualizations were used more often, they were observed to become more complex. Still, once distilled into their simplest forms, a limited variety of data visualizations was used across the dataset. Therefore, there is a clear need for increased data literacy targeted toward complex data visualizations. Furthermore, opportunities exist to improve the types of data visualizations used in academic writing.

Eine große Herausforderung für Wissenschaftler:innen ist der korrekte Umgang mit den rasant anwachsenden Datenmengen. Um Forschungsdaten nachhaltig speichern, bereitstellen, bewerten und nutzen zu können, ist Datenkompetenz essentiell. In NFDI werden wertvolle Datenbestände von Wissenschaft und Forschung für das gesamte deutsche Wissenschaftssystem systematisch erschlossen, vernetzt und nachhaltig sowie qualitativ nutzbar gemacht. Damit soll ein digitaler Wissensspeicher geschaffen werden, der neue Forschungsfragen, Erkenntnisse und Innovation ermöglicht. Das unter dem Dach der Vereins Nationale Forschungsdateninfrastruktur (NFDI) e.V. organisierte Netzwerk besteht (Stand März 2023) aus 26 Fachkonsortien, einem Konsortialverbund für Basisdienste und vier Sektionen, die Bottom-up an diesem Ziel arbeiten. Dabei entstehen zahlreiche Ressourcen, die unterschiedlichen Zielgruppen in diversen Formaten Datenkompetenz vermitteln. Die Angebote und Anforderungen an Datenkompetenz-Weiterbildungsangeboten für Wissenschaftler:innen sind dadurch vielfältig und werden in verteilten Systemen bereitgestellt. Das vom BMBF geförderte Projekt Datenkompetenz in NFDI unterstützt durch die gezielte Vernetzung der verschiedenen Akteure (auch über NFDI hinaus) den ganzheitlichen und nachhaltigen Aufbau von Datenkompetenz für Wissenschaftler:innen. Das Poster veranschaulicht die erste durchgeführte Phase "Basis" im Projekt, mit ihren zugehörigen absolvierten Arbeitspaketen und die methodische Umsetzung. Die Key Messages der ersten Phase werden zusammengefasst und das weitere Vorgehen dargestellt.

Poster für die Konferenz Informationswissenschaft im Wandel. Wissenschaftliche Tagung 2022 an der Heinrich-Heine-Universität Düsseldorf, 06.-07-10.2022. Der Text der akzeptierten Beiträge (Full-Paper, Poster und Panel) wird auch in der HI-Schriftenreihe Informationswissenschaft (Werner Hülsbusch Verlag) veröffentlicht.

Folien zum Workshop „Datenbasiertes Entscheiden durch Evaluationen und Wirkungsorientierung“ im Rahmen der Tagung „Wie gemeinwohlorientierte KI gestalten?“ des Deutschen Caritasverbandes. Slides to the workshop „Datenbasiertes Entscheiden durch Evaluationen und Wirkungsorientierung“ in the context of the conference „Wie gemeinwohlorientierte KI gestalten?“ of the German Caritas.

In the context of fundamental changes in the economy and the labor market, the introduction of educational programs in the field of data analysis and machine learning at all levels of education with the priority of integrating mathematical, natural science and socio-humanitarian knowledge becomes important. An overview and analysis of foreign experience and main discussion topics in the development of educational modules for data science and machine learning for adolescents and adolescents is presented.

The Turing Way is a community-led resource for reproducible, open, collaborative, and inclusive data science. Created by over 300 contributors, The Turing Way uses open source tools to enable people to collaboratively write chapters, build and maintain resources, as well as share their skills and ideas around best practices. Core to this is the version control tool, Github which supports The Turing Way’s collaborative practices. In this workshop, co-facilitators from The Turing Way Community will introduce participants to using GitHub as a tool to support collaborative documentation-writing and knowledge sharing. They will discuss the importance of open community practices in building and maintaining collective resources, and learn about the importance of different roles in open source documentation communities like The Turing Way: including that of maintainers, reviewers, and translators. Participants will gain hands-on experience in working collaboratively during the workshop by contributing to the The Turing Way project. A shared document will be used for collaborative note-taking, capturing feedback and learnings.

Presentation slides for the talk "RDM Compas– An online platform to foster data management skills for data curators in the social sciences" in Session F1 on June 9th, 2022by Tatiana Kvetnayaat IASSIST 2022.

Services to support researchers in managing their research data have been offered at the University Library of Basel since 2017. This presentation introduces what these services are and how they are linked to and integrated into related services offered by the University Library and the entire University. The University of Basel launched a data stewardship programme on 21 September 2021. In the second part of the presentation, the programme coordinators give an insight into the implementation of the programme and share their experiences so far. The presentation was given in German at the workshop "Data Information Literacy" of the association Information Literacy Working Group at Swiss Universities on 23 June 2022. Apart from the title slide, all slides are in English.

Esta presentación forma parte de los recursos educativos abiertos elaborados por miembros del GIR Inforal, en el marco del Proyecto de Innovación y Mejora Docente 2021/2022 de la Universidad de Salamanca denominado Laboratorio de experimentación para trabajar la alfabetización en datos mediante Prácticas Educativas Basadas en Evidencias con estudiantes de Grado (ID2021/017), Este material forma parte de las acciones formativas que se están llevando a cabo en el marco del Proyecto PID2020-116233RB-I00 financiado por el Ministerio de Ciencia e Innovación (España)

Folien für einen Impulsvortrag im Rahmen des Stifterverband DigitalChangeMaker-Accelerator-Projekts „Alte Bibliotheken - Neue Perspektiven“, Lehrgebiet Geschichte Europas, FernUniversität in Hagen, am 15.06.2022

How might quantitative data skills training within data services change in the future? How can we approach things differently? Who should we be reaching and how do they want to learn? This presentation outlines the UK Data Service's approach to quantitative data skills training, including recent changes and thoughts for the future. We discuss our experiences of new training formats and topics, such as upskilling social scientists in computational social science methods, and how the data and feedback we collect from users (and potential) users of our training is shaping our thoughts for the future of our training. We present our vision as we seek to prepare diverse users for the data skills and knowledge they will need to create relevant research now and in the future.

An important pedagogical development in contemporary data literacy education is the use of intensive multi-day “data bootcamps” to teach learners from diverse backgrounds foundational data competencies that they can immediately apply in their work and research. Academic libraries and digital scholarship centers are a part of this trend, experimenting in particular with the bootcamp format as a way to extend traditional short-form library teaching on data-related topics. In the summer of 2021, the Center for Research Data and Digital Scholarship (CRDDS), a formal collaboration between the University Libraries and Research Computing at the University of Colorado-Boulder, held its inaugural Data Bootcamp for graduate students. The Bootcamp was hosted virtually over three days, and attracted over seventy attendees with diverse disciplinary backgrounds and experience levels. The curriculum and lesson plans, which were newly developed for the Bootcamp in collaboration with Bootcamp instructors (most of whom are full-time employees at CRDDS), covered a range of topics across the research lifecycle. These included strategies for data discovery; data analysis and visualization in R and Python; tools for collaboration and reproducible research (such as GitHub, Docker, and institutional repositories); and the critical evaluation of found data and data ethics. After the Bootcamp, participants had the opportunity to certify their knowledge of the material taught in the Bootcamp by earning a micro-credential (i.e. “digital badge”) that was sponsored by the University Libraries, and formally issued by the University’s Office of the Registrar. In this presentation, we describe our experience in conceiving and organizing this Bootcamp, and reflect on its pedagogical and logistical successes and challenges, with a view towards helping other librarians and data professionals organize similar events at their own institutions. Whenever relevant, our discussion is informed by survey data that was collected from Bootcamp participants before, during, and after the event.

In our roles as data specialists and librarians within the Canadian academic community we actively promote data literacy through our library instruction and outreach to courses that have a requirement to locate reputable data sources for analysis. Our collective experience delivering data literacy sessions has led to the development of a shared pedagogical approach to teaching an instructional data session. We used this approach to develop a template for a forthcoming ACRL Cookbook on data literacy. In this presentation, we will introduce our approach to delivering instruction to post-secondary students in the social, health sciences, or related disciplines. Our approach focuses on helping students understand data as an information source by helping them think critically about how and why data are collected and shared. The instructional session focuses on locating, evaluating, and using sources of secondary data as information resources. We encourage students to consider how data are created and used by exploring the following questions – Who collects data? Why do they collect data and why might they choose to share it or not share it? How is data collected, and how do administrative and survey data differ? By working through these questions, we help students to learn why public data may be available on some topics and not others, understand key limitations of official statistics, and think about where information can be found to fill in the gaps. This session not only highlights the value of data literacy as a learning objective but also acknowledges the benefits of early careers practitioners learning from experienced colleagues.

Teaching data literacy - Data competency for subject librarians. Presentation at VIRAK 2022. The presentation was originally developed for a 90min workshop for subject librarians including practical exercises (https://doi.org/10.5281/zenodo.5564181). This is a shortened version sharing the main resources, aiming to inspire to see research data integrated in scholarly information competency. Benefits of reusing research data Data reuse requirements & FAIR principles Discovering datasets: Data from the public sector, data in digital archives & collections, scientific datasets Teaching data competency: Data Management 101

Esta presentación forma parte del curso Cómo elaborar un Plan de Gestión de Datos de investigación, impartido por las autoras, en el marco del Programa de Doctorado Formación en la Sociedad del Conocimiento de la Universidad de Salamanca, Este material se ha elaborado en el marco del Proyecto PID2020-116233RB-I00 financiado por el Ministerio de Ciencia e Innovación (España)

Academic libraries are considered to be a repository for knowledge, teaching and research supporting tools. As research is changing, expanding and transforming, libraries must adapt in their research support methods, and keep widening the availability of ressources and expertise. In recent years, data have become a more visible part of research, thus academic libraries must add data literacy to their research support portfolio and start offering ressources for researchers to learn about data management and its benefits. The EU funded project DaLiCo (Data Literacy in Context) is dedicated to increase the visibility, quality and usage of existing data literacy activities at a university level. The project aims at establishing collaborations between academic partners (departments, library, external partners) to convey data literacy competencies and contribute to the cultural change toward stronger data managing skills and openness. The research data lifecycle (plan-collect-analyse-preserve-share-reuse) provides numerous intervention points where research support agents, librarians can play a large part in the discovery, understanding, and curation of research data. Libraries can (1) provide access to data information (data availability, data sharing, data preservation, etc.), (2) offer services on research data management, and (3) support data science by providing access to training and instructional materials to help improve the knowledge and skill base surrounding data. Connecting to data driven research and related data literacy education, DaLiCo develops a Train the Trainer program to enhance data literacy and skills education among researchers. The primary aim of the program is to build a modular teaching framework which provides methodological and content support for involved stakeholders (researchers, teachers, librarians) for transferring knowledge on data science. This program can also be integrated into the teaching and support toolbox of libraries. Librarians’ expertise in data management and knowledge transfer can serve as the foundation for the training of the next generations of data scientists. The presentation at the BOBCATSSS 2022 will showcase the DaLiCo Train the Trainer program and demonstrate how such program can be included in academic libraries’ research support portfolio. &nbsp

Die Präsentation "Text- und Datamining in den Sozialwissenschaften" wurde im Rahmen einer Coffee Lecture an der Universitätsbibliothek Bern, Bibliothek vonRoll, am 05.04.2022 gehalten. Text and Data Mining (TDM) wird als Forschungsmethode in den Sozialwissenschaften vermehrt eingesetzt. Die Präsentation stellt deren Funktionsweise vor, insbesondere den typischen Ablauf einer TDM-Analyse mittels Machine-Learning-Methoden das Pre-Processing mit Methoden des Natural Language Processing (NLP) bekannte Machine-Learning-Ansätze für das Textmining. Nach der Präsentation einer Beispielstudie aus der Politikwissenschaft werden Vor- und Nachteile von TDM-Ansätzen beleuchtet, und abschliessend Hinweise zu Tools für den Einstieg, zu Tutorials und Literaturhinweise gegeben.

Im Rahmen seiner Öffentlichkeitsarbeit hat das Data Center for the Humanities (DCH) an der Universität zu Köln den Auftrag, Wissenschaftler:innen über Aspekte des Umgangs mit Forschungsdaten und des Forschungsdatenmanagements (FDM) zu informieren. Mit Beginn der Corona-Pandemie 2020 mussten neben Sprechstunde und Lehre in Präsenz auch die als Awareness-Initiative geplanten Kurzvorträge zu einzelnen FDM-Aspekten "Daten & Datteln" ausfallen. Stattdessen wurden die Inhalte in ein digitales Vermittlungsformat transferiert und als kompakte Sammelkarten an die Mitglieder der Philosophischen Fakultät und die interessierte Öffentlichkeit (via Twitter) kommuniziert. Das Poster dokumentiert und reflektiert, wie die Kommunikationsstrategie des DCH an die Pandemiebedingungen angepasst worden ist, um weiterhin sichtbar zu sein und FDM-Aspekte niederschwellig vermitteln zu können, und welche Mehrwerte und Möglichkeiten der Nachnutzung dabei entstanden sind. Ein Beitrag zur 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2022 Kulturen des digitalen Gedächtnisses.

Im Rahmen seiner Öffentlichkeitsarbeit hat das Data Center for the Humanities (DCH) an der Universität zu Köln den Auftrag, Wissenschaftler:innen über Aspekte des Umgangs mit Forschungsdaten und des Forschungsdatenmanagements (FDM) zu informieren. Mit Beginn der Corona-Pandemie 2020 mussten neben Sprechstunde und Lehre in Präsenz auch die als Awareness-Initiative geplanten Kurzvorträge zu einzelnen FDM-Aspekten "Daten & Datteln" ausfallen. Stattdessen wurden die Inhalte in ein digitales Vermittlungsformat transferiert und als kompakte Sammelkarten an die Mitglieder der Philosophischen Fakultät und die interessierte Öffentlichkeit (via Twitter) kommuniziert. Das Poster dokumentiert und reflektiert, wie die Kommunikationsstrategie des DCH an die Pandemiebedingungen angepasst worden ist, um weiterhin sichtbar zu sein und FDM-Aspekte niederschwellig vermitteln zu können, und welche Mehrwerte und Möglichkeiten der Nachnutzung dabei entstanden sind. Ein Beitrag zur 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2022 Kulturen des digitalen Gedächtnisses.

Folien zum Vortrag „Datenbasierte Entscheidungen durch Projektevaluationen“ im Rahmen der 3. Online-Zukunftswerkstatt im Caritas-Projekt „Lernende Systeme in der Beratung“. Slides to the lecture „Datenbasierte Entscheidungen durch Projektevaluationen“ in the context of the 3. Online-Zukunftswerkstatt at the Caritas project „Lernende Systeme in der Beratung“.

Poster GFBio-01fromthe GFBio General Assembly 2021 of the Work Package 1 - PR & Outreach of the GFBio Project summarizing the projects work and outcome between 2013and 2021. The overarching aim of Outreach and User Engagement (WP1) was to raise awareness for research data management among reasearchers and increase data literacy by providing support, training and teaching.

English: Coffee Lecture Slides: Data Literacy - Datenkompetenz als Schlüsselqualifikation im 21. Jahrhundert (Coffee Lecture 24.11.2021) Data literacy is defined as the ability to deal with data in a planned manner and to be able to use and question it consciously in the respective context. Due to the advancing digitization and datafication of society, competencies for handling data are becoming more and more important, not only in science but also in other areas of work and for social participation. It's not just about being able to collect and process data yourself. We are confronted with large amounts of data every day, which, among other things, should help us to assess developments in the world or to make personal or professional decisions. Basic skills in handling and understanding data are therefore important in order to generate knowledge from the available data and to be able to make well-founded decisions. This coffee lecture is dedicated to the question of what it means to be "data literate" and why (research) data management plays an important role in this. Video: Link ------------------------------------------------------ Deutsch: Coffee Lecture Folien: Data Literacy - Datenkompetenz als Schlüsselqualifikation im 21. Jahrhundert (Coffee Lecture 24.11.2021) Data Literacy wird definiert als die Fähigkeit, planvoll mit Daten umzugehen und sie im jeweiligen Kontext bewusst einsetzen und hinterfragen zu können. Durch die fortschreitende Digitalisierung und Datafizierung der Gesellschaft werden Kompetenzen zum Umgang mit Daten immer wichtiger, nicht nur in der Wissenschaft sondern auch in anderen Arbeitsbereichen und für die gesellschaftliche Teilhabe. Dabei geht es nicht nur darum selbst Daten erheben und verarbeiten zu können. Wir werden täglich mit großen Mengen an Daten konfrontiert, die uns unter anderem bei der Einschätzung von Entwicklungen in der Welt oder aber auch beim Treffen von persönlichen oder beruflichen Entscheidungen helfen sollen. Grundlegende Kompetenzen zum Umgang mit und dem Verständnis von Daten sind daher wichtig, um Wissen aus den verfügbaren Daten zu generieren und begründete Entscheidungen treffen zu können. Diese Coffee Lecture widmet sich der Frage, was es bedeutet "datenliterat" zu sein und warum (Forschungs-)Datenmanagement dabei eine wichtige Rolle spielt. Video: Link

English: Coffee Lecture Slides: Data Literacy - Datenkompetenz als Schl��sselqualifikation im 21. Jahrhundert (Coffee Lecture 24.11.2021) Data literacy is defined as the ability to deal with data in a planned manner and to be able to use and question it consciously in the respective context. Due to the advancing digitization and datafication of society, competencies for handling data are becoming more and more important, not only in science but also in other areas of work and for social participation. It's not just about being able to collect and process data yourself. We are confronted with large amounts of data every day, which, among other things, should help us to assess developments in the world or to make personal or professional decisions. Basic skills in handling and understanding data are therefore important in order to generate knowledge from the available data and to be able to make well-founded decisions. This coffee lecture is dedicated to the question of what it means to be "data literate" and why (research) data management plays an important role in this. Video: Link ------------------------------------------------------ Deutsch: Coffee Lecture Folien: Data Literacy - Datenkompetenz als Schl��sselqualifikation im 21. Jahrhundert (Coffee Lecture 24.11.2021) Data Literacy wird definiert als die F��higkeit, planvoll mit Daten umzugehen und sie im jeweiligen Kontext bewusst einsetzen und hinterfragen zu k��nnen. Durch die fortschreitende Digitalisierung und Datafizierung der Gesellschaft werden Kompetenzen zum Umgang mit Daten immer wichtiger, nicht nur in der Wissenschaft sondern auch in anderen Arbeitsbereichen und f��r die gesellschaftliche Teilhabe. Dabei geht es nicht nur darum selbst Daten erheben und verarbeiten zu k��nnen. Wir werden t��glich mit gro��en Mengen an Daten konfrontiert, die uns unter anderem bei der Einsch��tzung von Entwicklungen in der Welt oder aber auch beim Treffen von pers��nlichen oder beruflichen Entscheidungen helfen sollen. Grundlegende Kompetenzen zum Umgang mit und dem Verst��ndnis von Daten sind daher wichtig, um Wissen aus den verf��gbaren Daten zu generieren und begr��ndete Entscheidungen treffen zu k��nnen. Diese Coffee Lecture widmet sich der Frage, was es bedeutet "datenliterat" zu sein und warum (Forschungs-)Datenmanagement dabei eine wichtige Rolle spielt. Video: Link

The increased availability of research data in open access has impacted the scientific research environment, mainly due to the requirement of data deposit by government laws, funding agencies' policies, and scientific publication mandates. In this scenario, the researchers face difficulties managing their data and third parties, especially in data reuse-related matters. Each field of Science has its particularities of data types, volumes, and forms of data production, which is inherent to each scientific discipline. However, the relation of availability versus data management is more complex in the Social Sciences, whose data are heterogeneous and variable. This work seeks to evidence the lack of researcher's information data literacy, which exposes the untapped potential of data reuse already available. Therefore, this research output proposes the requirements for informational data literacy, concerning the minimal necessary skills regarding data reuse in Social Sciences, a model of 16 requirements, and 37 competencies for research data reuse in the Social Sciences. Essential requirements include access, licensing, and data use skills, and core competencies are findability and access to data, recognizing license types, and technical abilities for using available datasets., Complete research: ESTEVÃO, Janete Saldanha Bach. Letramento informacional para reúso de dados nas ciências sociais em ambientes virtuais de pesquisa: proposta de requisitos e competências. 2019. Tese (Doutorado em Tecnologia e Sociedade) - Universidade Tecnológica Federal do Paraná, Curitiba, 2019. http://repositorio.utfpr.edu.br/jspui/handle/1/4675.

Presentation of the projectPeter Handke Notebooks. Digital Edition in the Digital Humanities Ringvorlesung at the University of Vienna (Winter semester 2021/22).

Llevar a cabo investigaciones con datos sobre personas es un privilegio, no un derecho, por lo tanto, todos los que administran datos de investigaci��n, datos abiertos o cualquier tipo de datos proporcionados por personas, incluidos bibliotecarios e investigadores, deben desarrollar conocimientos de datos cr��ticos y ��ticos. Atenas, Havemann & Timmermann, 2021 Panel en Abrelatam21 sobre alfabetizaci��n en datos desde una perspectiva cr��tica y ��tica: el panel se centra en presentar diferentes experiencias, perspectivas y oportunidades en alfabetizaci��n en datos con una mirada cr��tica con un enfoque en la ��tica y en el bien com��n. El video del panel est�� ac�� Abrelatam ConDatos del Futuro: Alfabetizaci��n en datos

Llevar a cabo investigaciones con datos sobre personas es un privilegio, no un derecho, por lo tanto, todos los que administran datos de investigación, datos abiertos o cualquier tipo de datos proporcionados por personas, incluidos bibliotecarios e investigadores, deben desarrollar conocimientos de datos críticos y éticos. Atenas, Havemann & Timmermann, 2021 Panel en Abrelatam21 sobre alfabetización en datos desde una perspectiva crítica y ética: el panel se centraen presentar diferentes experiencias, perspectivas y oportunidades en alfabetización en datos con una mirada crítica con un enfoqueen la ética y en el bien común. El video del panel está acá Abrelatam ConDatos del Futuro: Alfabetización en datos &nbsp

Presentation given at the 'XVIII International Conference on University Libraries: Reading, information, digital, transmedia and research competencies in the training of professionals for future' organized by the Universidad Nacional Autónoma de México (UNAM) on October 26th to 28th, 2021. This presentation was part of the round table 4 'Data Literacy and Open Science for the advancement of learning, knowledge and research' The session was recorded: https://www.facebook.com/bibliotecasUNAM/videos/917528655528027 The presentation tries to reflect on the different approaches that university libraries can contribute to capacity building on data literacy and open science skills based on TU Delft Library experience.

Course structure and learning objectives for the3 ECTS Research Data Management (BRDM) course at the University of Turku and at the Åbo Akademi University, Turku, Finland in Spring of 2019-22.

Course structure and learning objectives for the3 ECTS Research Data Management (BRDM) course at the University of Turku and at the Åbo Akademi University, Turku, Finland in Spring of 2019-22.

Course structure and learning objectives for the3 ECTS Research Data Management (BRDM) course at the University of Turku and at the Åbo Akademi University, Turku, Finland in Spring of 2019-22.

In February 2021, University of California (UC) Libraries co-hosted UC Love Data Week, a series of free events for UC affiliates on a wide range of topics including: data publishing, data repositories, data cleaning, and text mining to name a few. In an interactive workshop entitled, "Ethical Considerations in Data", data librarians from UCLA, UC Berkeley, and UC San Diego hosted an open discussion around data ethics focusing on case studies of participant data privacy, algorithmic bias, and the social justice components of research. The discussion includes an overview of related resources available at various UC campuses, including further reading available through the libraries and groups on UC campus conducting research in these areas.

This chapter is aimed at presenting two-core elements of the world of data, oneat an individual level and the other, at thecollective level. In the first unit, wewill review the concepts and skills needed to enable personal data agency,which can beunderstood as the individual’s ability to understand andchallenge the data collected about him/her. By doing so, he/she willbe able to make informed decisions about his/her data throughunderstanding the legal landscape of data protection and datarights. This will allow individuals to curate and control their (personal) data. Todo this we need to gain knowledge of these datadriven systems, beingable to identify them as well as understanding how they operate. In thesecond unit, we will present thekey elements and principles of indigenousdata sovereignty (ID-SOV). This is a relatively recent concept that can beunderstoodas the right of indigenous peoples to own, control, access and possess datathat derive from their needs andsocial reality. This is grounded on therights to self-determination and governance as affirmed in the UnitedNations Declaration on the Rights of Indigenous Peoples (UNDRIP).

En esta unidad, exploraremos el concepto de justicia de datos y las diferentesinterpretaciones de la idea de justicia de datos. También profundizaremos endiferentes enfoques de la justicia de datos, analizando sus beneficios y dificultades. Luego nos centraremos en el marco de Taylor (2017) para el diseño y la gobernanzade las tecnologías de datos. El marcoes una capacidad (Sen, 2009) y un enfoquebasado en la libertad que examina cómo las tecnologías de datos influyen en el tipode vida que la gente considera valiosa para vivir. Existe una interacción innegable entre las tecnologías basadas en datos y lavida diaria de las personas. Esta interacción es compleja y matizada y tieneimplicaciones tanto positivas como negativas. Los sistemas basados en datos tienenlacapacidad de inspirar a las organizaciones a innovar en la forma en que operan,mientras que los gobiernos pueden usar lainformación para informar políticasdirigidas al bienestar económico. Pero también los sistemas basados en datospuedenservir como una herramienta para discriminar o marginalizar comunidadesvulnerables. La forma en que se gestionan los sistemas es fundamental paraofrecer servicios y beneficios por igual a todos los ciudadanos. La justicia de datoses una respuesta a las implicaciones sociales negativas que estos sistemas tienenen nuestras vidas.

In this unit, we explore the concept of data justice and the different interpretationsof the idea. That is, we consider thedifferent approaches to data justice, lookingat their benefits and pitfalls. We then focus on Taylor’s (2017) framework for datatechnologies’ design and governance. The framework is a capability (Sen, 2009) andfreedom-based approach that examines how data technologies influence the kindof lives that people deem valuable to live. As a complement to the notion of data justice, which is mainly a conceptual one, data feminism, the data ethics canvas,and the seven inequities held in power aregoing to be described as actionableanalytical tools to address issues of data justice when working with research in the classroom. We believe that with this module the mechanisms of negotiability and agency somuch needed to be able to interact in data-driven systems can be improved.

Este capitulo tiene como objetivo presentar dos núcleos de elementos dedatos, uno a nivel individual y otro a nivel colectivo.En la primera unidad,revisaremos el concepto, los principios y las habilidades necesariaspara habilitar la agencia de datospersonales y en la segunda unidad,exploraremos el concepto de soberanía de datos indígenas (SOB-DI). En la primera unidad, revisaremos los conceptos y habilidades necesariospara habilitar la agencia de datos personales,entendida como la capacidadde los individuos para comprender y cuestionar los datos recopilados sobre ellos,para tomardecisiones informadas sobre sus datos al comprender el panorama legalde protección de datos y derechos de datos. Estopermitirá a las personas conservar ycontrolar sus datos (personales). Para hacer esto, necesitamos adquirir conocimientode estos sistemas, poder identificarlos, pero también entender cómo funcionan.En la segunda unidad, presentaremos loselementos y principios clave de la soberanía de datos indígenas (ID-SOV), un concepto relativamente reciente quepuede entenderse como los derechos de los pueblos indígenas a poseer, controlar, acceder y poseer datos que deriven de sus necesidadesy realidad social, fundamentada en los derechos a la autodeterminación y la gobernanza como se afirma en laDeclaración de las Naciones Unidas sobre los Derechos de los Pueblos Indígenas (DNUDPI).

Este capitulo tiene como objetivo presentar dos n��cleos de elementos de datos, uno a nivel individual y otro a nivel colectivo. En la primera unidad, revisaremos el concepto, los principios y las habilidades necesarias para habilitar la agencia de datos personales y en la segunda unidad, exploraremos el concepto de soberan��a de datos ind��genas (SOB-DI). En la primera unidad, revisaremos los conceptos y habilidades necesarios para habilitar la agencia de datos personales, entendida como la capacidad de los individuos para comprender y cuestionar los datos recopilados sobre ellos, para tomar decisiones informadas sobre sus datos al comprender el panorama legal de protecci��n de datos y derechos de datos. Esto permitir�� a las personas conservar y controlar sus datos (personales). Para hacer esto, necesitamos adquirir conocimiento de estos sistemas, poder identificarlos, pero tambi��n entender c��mo funcionan. En la segunda unidad, presentaremos los elementos y principios clave de la soberan��a de datos ind��genas (ID-SOV), un concepto relativamente reciente que puede entenderse como los derechos de los pueblos ind��genas a poseer, controlar, acceder y poseer datos que deriven de sus necesidades y realidad social, fundamentada en los derechos a la autodeterminaci��n y la gobernanza como se afirma en la Declaraci��n de las Naciones Unidas sobre los Derechos de los Pueblos Ind��genas (DNUDPI).