We live in a data-driven world, much of it processed and served up by increasingly complex algorithms, and evaluating its quality requires its own skillset. As a component of information literacy, it's crucial that students learn how to think critically about statistics, data, and related visualizations. Here, Bauder and her fellow contributors show how librarians are helping students to access, interpret, critically assess, manage, handle, and ethically use data. Offering readers a roadmap for effectively teaching data literacy at the undergraduate level, this volume explores such topics as the potential for large-scale library/faculty partnerships to incorporate data literacy instruction across the undergraduate curriculum; how the principles of the ACRL Framework for Information Literacy for Higher Education can help to situate data literacy within a broader information literacy context; a report on the expectations of classroom faculty concerning their students’ data literacy skills; various ways that librarians can partner with faculty; case studies of two initiatives spearheaded by Purdue University Libraries and University of Houston Libraries that support faculty as they integrate more work with data into their courses; Barnard College’s Empirical Reasoning Center, which provides workshops and walk-in consultations to more than a thousand students annually; how a one-shot session using the PolicyMap data mapping tool can be used to teach students from many different disciplines; diving into quantitative data to determine the truth or falsity of potential “fake news” claims; and a for-credit, librarian-taught course on information dissemination and the ethical use of information.

Given the increasing attention to managing, publishing, and preserving research datasets as scholarly assets, what competencies in working with research data will graduate students in STEM disciplines need to be successful in their fields? And what role can librarians play in helping students attain these competencies? In addressing these questions, this book articulates a new area of opportunity for librarians and other information professionals, developing educational programs that introduce graduate students to the knowledge and skills needed to work with research data. The term "data information literacy" has been adopted with the deliberate intent of tying two emerging roles for librarians together. By viewing information literacy and data services as complementary rather than separate activities, the contributors seek to leverage the progress made and the lessons learned in each service area. The intent of the publication is to help librarians cultivate strategies and approaches for developing data information literacy programs of their own using the work done in the multiyear, IMLS-supported Data Information Literacy (DIL) project as real-world case studies. The initial chapters introduce the concepts and ideas behind data information literacy, such as the twelve data competencies. The middle chapters describe five case studies in data information literacy conducted at different institutions (Cornell, Purdue, Minnesota, Oregon), each focused on a different disciplinary area in science and engineering. They detail the approaches taken, how the programs were implemented, and the assessment metrics used to evaluate their impact. The later chapters include the "DIL Toolkit," a distillation of the lessons learned, which is presented as a handbook for librarians interested in developing their own DIL programs. The book concludes with recommendations for future directions and growth of data information literacy. More information about the DIL project can be found on the project's website: datainfolit.org.

An insider’s guide to data librarianship packed full of practical examples and advice for any library and information professional learning to deal with data. Interest in data has been growing in recent years. Support for this peculiar class of digital information – its use, preservation and curation, and how to support researchers’ production and consumption of it in ever greater volumes to create new knowledge, is needed more than ever. Many librarians and information professionals are finding their working life is pulling them toward data support or research data management but lack the skills required. The Data Librarian’s Handbook, written by two data librarians with over 30 years’ combined experience, unpicks the everyday role of the data librarian and offers practical guidance on how to collect, curate and crunch data for economic, social and scientific purposes. With contemporary case studies from a range of institutions and disciplines, tips for best practice, study aids and links to key resources, this book is a must-read for all new entrants to the field, library and information students and working professionals. Key topics covered include: • the evolution of data libraries and data archives • handling data compared to other forms of information • managing and curating data to ensure effective use and longevity • how to incorporate data literacy into mainstream library instruction and information literacy training • how to develop an effective institutional research data management (RDM) policy and infrastructure • how to support and review a data management plan (DMP) for a project, a key requirement for most research funders • approaches for developing, managing and promoting data repositories • handling and sharing confidential or sensitive data • supporting open scholarship and open science, ensuring data are discoverable, accessible, intelligible and assessable. This title is for the practising data librarian, possibly new in their post with little experience of providing data support. It is also for managers and policy-makers, public service librarians, research data management coordinators and data support staff. It will also appeal to students and lecturers in iSchools and other library and information degree programmes where academic research support is taught.

Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

This inspiring book will enable academic librarians to develop excellent research and instructional services and create a library culture that encompasses exploration, learning and collaboration. Higher education and academic libraries are in a period of rapid evolution. Technology, pedagogical shifts, and programmatic changes in education mean that libraries must continually evaluate and adjust their services to meet new needs. Research and learning across institutions is becoming more team-based, crossing disciplines and dependent on increasingly sophisticated and varied data. To provide valuable services in this shifting, diverse environment, libraries must think about new ways to support research on their campuses, including collaborating across library and departmental boundaries. This book is intended to enrich and expand your vision of research support in academic libraries by: Inspiring you to think creatively about new services. Sparking ideas of potential collaborations within and outside the library, increasing awareness of functional areas that are potential key partners. Providing specific examples of new services, as well as the decision-making and implementation process. Encouraging you to take a broad view of research support rather than thinking of research and instruction services, metadata creation and data services etc as separate initiatives. Dynamic Research Support in Academic Libraries provides illustrative examples of emerging models of research support and is contributed to by library practitioners from across the world. The book is divided into three sections: Part I: Training and Infrastructure, which describes the role of staff development and library spaces in research support Part II: Data Services and Data Literacy, which sets out why the rise of research data services in universities is critical to supporting the current provision of student skills that will help develop them as data-literate citizens. Part III: Research as a Conversation, which discusses academic library initiatives to support the dissemination, discovery and critical analysis of research. This is an essential guide for librarians and information professionals involved in supporting research and scholarly communication, as well as library administrators and students studying library and information science.

This book constitutes the refereed proceedings of the European Conference on Information Literacy, ECIL 2013, held in Istanbul Turkey, in October 2013. The 73 revised full papers presented together with two keynotes, 9 invited papers and four doctoral papers were carefully reviewed and selected from 236 submissions. The papers are organized in topical sections on overview and research; policies and strategies; theoretical framework; related concepts; citizenship and digital divide; disadvantaged groups; information literacy for the workplace and daily life; information literacy in Europe; different approaches to information literacy; teaching and learning information literacy; information literacy instruction; assessment of information literacy; information literacy and K-12; information literacy and higher education; information literacy skills of LIS students; librarians, libraries and ethics.

"With the appearance of big data, open data, and particularly research data curation on many libraries' radar screens, data service has become a critically important topic for academic libraries. Drawing on the expertise of a diverse community of practitioners, this collection of case studies, original research, survey chapters, and theoretical explorations presents a wide-ranging look at the field of academic data librarianship. By covering the data lifecycle from collection development to preservation, examining the challenges of working with different forms of data, and exploring service models suited to a variety of library types, this volume provides a toolbox of strategies that will allow librarians and administrators to respond creatively and effectively to the data deluge. Edited by Kristi Thompson and Lynda Kellam, Databrarianship: The Academic Data Librarian in Theory and Practice provides advice and insight on data services for all types of academic libraries and will be of interest to library educators"--Publisher's website.

Novice and early career researchers often have difficulty with understanding how theory, data analysis and interpretation of findings “hang together” in a well-designed and theorized qualitative research investigation and with learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Data Analysis, Interpretation, and Theory in Literacy Studies Research demonstrates how to design, conduct and analyze a well put together qualitative research project. Using their own successful studies, chapter authors spell out a problem area, research question, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

Creating Data Literate Students provides high school librarians and educators with foundational domain knowledge to teach a new subset of information literacy skills -- data and statistical literacy, including: statistics and data comprehension; data as argument; and data visualization. Data -- both raw and displayed in visualizations -- can clarify or confuse, confirm or deny, persuade or deter. Students often learn that numbers are objective, though data in the real world is rarely so. In fact, visualized data -- even from authoritative sources -- can sometimes be anything but objective. Librarians and classroom educators need to be as fluent with quantitative data as they are with text in order to support high schoolers as they engage with data in formal and informal settings. We asked contributors to this volume -- experts in high school curriculum, information literacy and/or data literacy -- to explore the intersections between data and curriculum and identify high-impact strategies for demystifying data for educators and students alike.

Armed with this guide's strategies and concrete examples, subject librarians, data services librarians, and scholarly communication librarians will be inspired to roll up their sleeves and get involved with teaching research data management competencies to students and faculty. The usefulness of research data management skills bridges numerous activities, from data-driven scholarship and open research by faculty to documentation for grant reporting. And undergrads need a solid foundation in data management for future academic success. This collection gathers practitioners from a broad range of academic libraries to describe their services and instruction around research data. You will learn about such topics as integrating research data management into information literacy instruction; threshold concepts for novice learners of data management; four key competencies that are entry points for library-faculty collaboration in data instruction; an 8-step plan for outreach to faculty and grad students in engineering and the sciences; using RStudio to teach data management, data visualization, and research reproducibility; expanding data management instruction with adaptable modules for remote learning; designing a data management workshop series; developing a research guide on data types, open data repositories, and data storage; creating a data management plan assignment for STEM undergraduates; and data management training to ensure compliance with grant requirements.