RQM is a research methods course that focuses on modernizing the post-data collection portion of the scientific workflow. The course takes an approach that produces both conventional research products and trains students to make their work more efficient and reproducible. This handbook provides a framework for professors who would like to teach a 14-week class on reproducible quantitative methods, presuming an understanding of open workflows for publication, some intermediate R or (other command-line based data analysis software) skills, and basic GitHub operations and use.

The Research Data Curation Bibliography includes over 750 selected English-language articles, books, and technical reports that are useful in understanding the curation of digital research data in academic and other research institutions.

MANTRA is a free, online non-assessed course with guidelines to help you understand and reflect on how to manage the digital data you collect throughout your research. It has been crafted for the use of post-graduate students, early career researchers, and also information professionals. It is freely available on the web for anyone to explore on their own.

Through a series of interactive online units you will learn about terminology, key concepts, and best practice in research data management.

There are eight online units in this course and one set of offline (downloadable) data handling tutorials that will help you:

1. Understand the nature of research data in a variety of disciplinary settings
2. Create a data management plan and apply it from the start to the finish of your research project
3. Name, organise, and version your data files effectively
4. Gain familiarity with different kinds of data formats and know how and when to transform your data
5. Document your data well for yourself and others, learn about metadata standards and cite data properly
6. Know how to store and transport your data safely and securely (backup and encryption)
7. Understand legal and ethical requirements for managing data about human subjects; manage intellectual property rights
8. Understand the benefits of sharing, preserving and licensing data for re-use
9. Improve your data handling skills in one of four software environments: R, SPSS, NVivo, or ArcGIS

Each unit takes up to one hour, plus time for further reading and carrying out the data handling exercises. In the units you will find explanations, descriptions, examples, exercises, and video clips in which academics, PhD students and others talk about the challenges of managing research data. The data handling tutorials assume some experience with each software environment and provide exercises in PDF along with open datasets to download and work through using your own installed software.

MANTRA modules and data handling exercises are available for download via Zenodo: https://doi.org/10.5281/zenodo.1035218

The Research Data Management Academy (RDMLA) is a global, free online professional development program for librarians, information professionals, or other professionals who work in a research-intensive environment. The curriculum focuses on the knowledge and skills needed to collaborate with researchers and other stakeholders on data management. RDMLA features a unique partnership between a library and information science academic program, academic health sciences and research libraries, and industry publisher. All of the content is hosted on Canvas Network, freely available, and open for reuse under a CC-BY-NC-SA license.

This webliography is intended for librarians seeking to enhance their own knowledge and assist peers in improving their data management awareness. The webliography is organized by content type, first with more foundational materials such as established data management curricula and then with current awareness and community materials such as social media.

This module dwells on a number of methods (including old and new) available for research evaluation. The module comprises the following four units:
Unit 1. Introduction to Research Evaluation Metrics and Related Indicators.
Unit 2. Innovations in Measuring Science and Scholarship: Analytical Tools and Indicators in Evaluation Scholarship Communications.
Unit 3. Article and Author Level Measurements, and
Unit 4. Online Citation and Reference Management Tools.
Brief overviews of the units are presented below.
Unit 1 encompassed and discussed citation analysis, use of citation-based indicators for research evaluation, common bibliometric indicators, classical bibliometric laws, author level indicators using authors' public profiles, article level metrics using altmetric tools. It is to be noted that author level indicators and article level metrics are new tools for research evaluation. Author level indicators encompasses h index, citations count, i10 index, g index, articles with citation, average citations per article, Eigenfactor score, impact points, and RG score. Article level metrics or altmetrics are based on Twitter, Facebook, Mendeley, CiteULike, and Delicious which have been discussed. All technical terms used in the Unit have been defined.
Unit 2 deals with analytical tools and indicators used in evaluating scholarly communications. The tools covered are The Web of Science, Scopus, Indian Citation Index (ICI), CiteSeerX, Google Scholar and Google Scholar Citations. Among these all the tools except Indian Citation Index (ICI) are international in scope. ICI is not very much known outside India. It is a powerful tool as far Indian scholarly literature is concerned. As Indian journals publish a sizable amount of foreign literature, the tool will be useful for foreign countries as well. The analytical products with journal performance metrics Journal Citation Reports (JCR®) has also been described. In the chapter titled New Platforms for Evaluating Scholarly Communications three websites i.e. SCImago Journal & Country Rank (SJR) [ScimagoJR.com], eigenFACTOR.org, JournalMetrics.com and one software called Publish or Perish (POP) Software have been discussed.
Article and author level measurements have been discussed in Unit 3. Author and researcher identifiers are absolutely essential for searching databases in the WWW because a name like D Singh can harbour a number of names such as Dan Singh, Dhan Singh, Dhyan Singh, Darbara Singh, Daulat Singh, Durlabh Singh and more. The ResearcherID.com, launched by Thomson Reuters, is a web-based global registry of authors and researchers that individualises each and every name. Open Researcher and Contributor ID (ORCID) is also a registry that uniquely identifies an author or researcher. Both have been discussed in this Unit. Article Level Metrics (Altmetrics) has been treated in this Unit with the discussion as to how altmetrics can be measured with Altmetric.com and ImpactStory.org. Altmetrics for Online Journals has also been touched. There are a number of academic social networks of which ResearchGate.net, Academia.edu, GetCited.org, etc. have been discussed. Regional journal networks with bibliometric indicators are also in existence. Two networks of this type such as SciELO – Scientific Electronic Library Online, and Redalyc have been dealt with.
The last unit (Unit 4) is on online citation and reference management tools. The tools discussed are Mendeley, CiteULike, Zotero, Google Scholar Library, and EndNote Basic. The features of all the management tools have been discussed with figures, tables, and text boxes.
This is Module Four of the UNESCO's Open Access Curriculum for Researchers.
Full-Text is available at http://unesdoc.unesco.org/images/0023/002322/232210E.pdf

These research metric source cards provide the citation for a scholarly work and the research metrics of that work, which can include: the Altmetric Attention Score, the scholarly citation counts from different data sources, and field-weighted citation indicators; in addition, abstracts and important context to some of the metrics is also included, e.g., citation statements, titles of select online mentions, such as news and blog article titles, Wikipedia pages, patent citations, and the context behind those online mentions. There are four printable source cards (front and back) followed by activity questions for each source card. These cards help students engage in and interrogate the meaning behind bibliometrics and altmetrics of specific scholarly works as well as evaluate the credibility, authority, and reliability of the scholarly work itself.

This version of this teaching module was published in Teaching Issues and Experiments in Ecology:

Jim McNeil and Megan A. Jones. April 2018, posting date. Data Management using National Ecological Observatory Network’s (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis. Teaching Issues and Experiments in Ecology, Vol. 13: Practice #9 [online]. http://tiee.esa.org/vol/v13/issues/data_sets/mcneil/abstract.html

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Undergraduate STEM students are graduating into professions that require them to manage and work with data at many points of a data management life cycle. Within ecology, students are presented not only with many opportunities to collect data themselves, but increasingly to access and use public data collected by others. This activity introduces the basic concept of data management from the field through to data analysis. The accompanying presentation materials mention the importance of considering long-term data storage and data analysis using public data.

This data set is a subset of small mammal trapping data from the National Ecological Observatory Network (NEON). The accompanying lesson introduces students to proper data management practices including how data moves from collection to analysis. Students perform basic spreadsheet tasks to complete a Lincoln-Peterson mark-recapture calculation to estimate population size for a species of small mammal. Pairs of students will work on different sections of the datasets allowing for comparison between seasons or, if instructors download additional data, between sites and years. Data from six months at NEON’s Smithsonian Conservation Biology Institute (SCBI) field site are included in the materials download. Data from other years or locations can be downloaded directly from the NEON data portal to tailor the activity to a specific location or ecological topic.

In this activity, students will:

- discuss data management practices with the faculty. Presentation slides are provided to guide this discussion.
- view field collection data sheets to understand how organized data sheets can be constructed.
- design a spreadsheet data table for transcription of field collected data using good data management practices.
- view NEON small mammal trapping data to a) see a standardized spreadsheet data table and b) see what data are collected during NEON small mammal trapping.
- use Microsoft Excel or Google Sheets to conduct a simple Lincoln-Peterson Mark-Recapture analysis to estimate plot level species population abundance.

Please note that this lesson was developed while the NEON project was still in construction. There may be future changes to the format of collected and downloaded data. If using data directly from the NEON Data Portal instead of using the data sets accompanying this lesson, we recommend testing out the data each year prior to implementing this lesson in the classroom.

This module was originally taught starting with a field component where students accompanied NEON technicians during the small mammal trapping. As this is not a possibility for most courses, the initial part of the lesson has been modified to include optional videos that instructors can use to show how small mammal trapping is conducted. Instructors are also encouraged to bring small mammal traps and small mammal specimens into the classroom where available.

The Data Sets

The National Ecological Observatory Network is a program sponsored by the National Science Foundation and operated under cooperative agreement by Battelle Memorial Institute. This material is based in part upon work supported by the National Science Foundation through the NEON Program.

The following datasets are posted for educational purposes only. Data for research purposes should be obtained directly from the National Ecological Observatory Network (www.neonscience.org).

Data Citation: National Ecological Observatory Network. 2017. Data Product: NEON.DP1.10072.001. Provisional data downloaded from http://data.neonscience.org. Battelle, Boulder, CO, USA

Notes
Version 2.1: Includes correct Lincoln-Peterson Index formula in PPT, faculty, and student notes.

Version 2.0: This version of the teaching module was published in Teaching Issues and Experiments in Ecology. McNeil and Jones 2018. This version reflects updates based on comments from reviewers.

Version 1.0: This version of the teaching module was prepared as part of the 2017 DIG FMN. It was submitted for publication as part of the DIG Special Issue of TIEE.

Cite this work
Researchers should cite this work as follows:

Jim McNeil, Megan A. Jones (2018). Data Management using National Ecological Observatory Network's (NEON) Small Mammal Data with Accompanying Lesson on Mark Recapture Analysis. NEON - National Ecological Observatory Network, (Version 2.1). QUBES Educational Resources. doi:10.25334/Q4M121

The laboratory notebook is the cornerstone of any laboratory course. Students develop critical thinking, documentation, and communication skills while mastering scientific concepts. Furthermore, the use of electronic lab notebooks (ELNs) for documentation has become the standard for data management in industry and academic labs.

Replacing paper with an interactive research notebook provides students with authentic data management skills. It also offers a medium for easily incorporating quantitative reasoning into the curriculum to address real. Instructors using digital notebooks in their courses reported a significant increase in student engagement and assessment scores.

In this workshop, we will explore the current ELNs landscape and best practices for moving from paper to digital.

Cite this work
Researchers should cite this work as follows:

Stringer, N. (2019). Electronic Lab Notebooks: Options for Building Data Management and Quantitative Reasoning Skills. Evolution of Data in the Classroom: From Data to Data Science (SW 2019), QUBES Educational Resources. doi:10.25334/B1NP-B249

Description
This lesson introduces students to working with metadata, which can be broadly thought of as the data ABOUT existing data. Data isn’t complete without metadata, and this lesson will help students understand both how to work with metadata and how to create their own.

Data used: NEON aquatic macroinvertebrate datasets from multiple stations. It could be adapted to use any data sets or taxonomic groups though.

Activities: The lesson involves three major activities. 1) Querying and downloading datasets and corresponding products from NEON. 2) Reading and answering comprehension questions about metadata files that correspond with data files 3) Combining two datasets based off understanding the metadata in exercise 2 (e.g. understanding which columns indicate sampling dates and in which formats will allow them to appropriately combine multiple data sets).

Programs: No specific programming skills or language is required for this lesson. This lesson is designed to be done entirely in common office/student software programs (e.g. Microsoft Word and Microsoft Office) and could be done using online programs (e.g. my university has student licenses for Google Spreadsheets and Google Docs).

Learning objectives:

1 – Students will be able to define ‘metadata’ and understand how metadata is critical for reproducible research.

2 – Students will be able to correctly answer comprehension questions about a metadata file.

3 – Students will be able to apply their understanding of the metadata file to create a new data file from two data sets.

4 – Students will understand the importance of creating and understanding metadata to go along with datasets.

Timing: This lesson was designed to take place in two – 75 minute class periods that are in a workshop format. This lesson could easily be part of a longer lab, homework, or a remote / online / asynchronous assignment.

Notes
This version is current as of Spring 2019 and was classroom taught. I encourage folks to adapt, modify, and make new versions.

Cite this work
Researchers should cite this work as follows:

Whitney, K. S. (2019). Introduction to Data Management and Metadata using NEON aquatic macroinvertebrate data. NEON Faculty Mentoring Network, QUBES Educational Resources. doi:10.25334/SJX1-F373

This document is an evidence-based guide that outlines the practical and policy supports needed to enable K-12 school librarians to take on leadership roles around OER, and to support OER curation efforts by librarians and all educators.

This guide is based on a study led by ISKME (iskme.org) in collaboration with Florida State University's School of Information. The study is titled “Exploring OER Curation and the Role of School Librarians". ISKME designs guides and toolkits that help educators navigate and implement new teaching and learning practices. Grounded in research, our evidence-based guides and toolkits help articulate what actually works in real education settings—and are tailored to the unique professional learning needs of our clients and their stakeholders.

The study was made possible in part by the Institute of Museum and Library Services (www.imls.gov), under grant number LG-86-17-0035-17. The findings and recommendations expressed in this document do not necessarily represent those of the Institute of Museum and Library Services.

This course is no longer taught at the U-M School of Information. These materials are from an older iteration of the course.

This course introduces students to the ideas and practices surrounding teaching, learning and research at a world class research university like the University of Michigan, and the emerging role in these practices of Open Educational Resources, including open content such as opencourseware, open access initiatives, open publishing of research and learning materials as found in open journals, databases and e-prints, open textbooks, related open software efforts such as open learning systems, and emerging open teaching experiments. The course will ground the students in how teaching, learning and research is done at the university level, and then survey relevant OER efforts, looking at their history, development, potential futures, and the underlying motivations for their progressive adoption by various members of the community of scholars. more...

This course uses an open textbook Open Educational Resources at the University of Michigan. The articles in the open textbook (wikibook) were written by the School of Information Graduate students in the class.

This guidebook was created by ISKME, in partnership with the Science Education Resource Center (SERC) at Carleton College. The document provides a practical reference for curators and authors of STEM OER, and contains 23 accessibility criteria, or elements, to reference as they curate, design and adapt materials to be accessible for STEM learners.

The primary audience of this resource is STEM postsecondary faculty, instructional designers, and others responsible for course design and pedagogy who seek to:

- Expand their knowledge about accessibility and ways to integrate it into their STEM curriculum and instruction
- Design openly licensed STEM courses and course materials that support both access and use by learners
- Curate existing STEM content that expands upon traditional textbooks and courseware to address variability in learning
- Identify and add meaningful keywords, or tags, to the STEM OER they create, so that their OER can be more easily discovered across platforms

Professional learning teams on campus are also encouraged to use this framework as part of training to facilitate integration of accessibility concepts into STEM course design and pedagogy.

The framework and guide development was supported by a mini-grant program facilitated by Bates College and the SCORE-UBE Network (Sustainability Challenges for Open Resources to promote an Equitable Undergraduate Biology Education), with funding from The William and Flora Hewlett Foundation. The framework and guide were developed by ISKME and SERC with input from 21 STEM faculty members from across the United States, and in collaboration with the project’s Working Group of accessibility experts: Andrew Hasley and Hayley Orndorf, both with BioQUEST’s UDL Initiative and the Quantitative Undergraduate Biology Education and Synthesis (QUBES) Project; Hannah Davidson, Plymouth State University; and Cynthia Curry, National Center on Accessible Educational Materials (AEM)/CAST.

The Declaration on Research Assessment (DORA) recognizes the need to improve the ways in which the outputs of scholarly research are evaluated. The declaration was developed in 2012 during the Annual Meeting of the American Society for Cell Biology in San Francisco. It has become a worldwide initiative covering all scholarly disciplines and all key stakeholders including funders, publishers, professional societies, institutions, and researchers. The DORA initiative encourages all individuals and organizations who are interested in developing and promoting best practice in the assessment of scholarly research to sign DORA.

Other resources are available on their website, such as case studies of universities and national consortia that demonstrate key elements of institutional change to improve academic career success.

This lesson on the nature and cost of scholarly publishing could be taught by
itself, or as part of a series on scholarly communication, or as a small part of a larger lesson on
information privilege.

In ScholCom 202X, you'll take on the role of a new scholarly communication librarian at a small public university somewhere in the US in the "distant future" of the year 202X.

You'll be given a number of scenarios derived from activities and questions a real scholarly communication librarian might expect to receive. These scenarios fall into four general areas: copyright; publishing; institutional repositories; and open access.

The game has two versions, an interactive fiction format written in Ink (located in the "Ink source" and "playable" folders) and a static PDF version (in "printables").

In the interactive fiction version, after reading each scenario you'll be given a chance to consult your "augment," a smartphone-like device which contains a very brief annotated list of some relevant sources and a calendar that tracks how busy you are. In the PDF/print version, these sources are listed below the scenario text, and are open access whenever possible.

After you've read the scenario text and consulted these sources (or not), put yourself in the place of the librarian in the game and think about how you would respond. Would you try to help just the person you're currently talking to, or would you rather build resources and develop strategies that could make the question easier to answer the next time it comes up, and potentially even reach and educate people who don't know the questions to ask in the first place?

As you think through each scenario, ask yourself how you would balance the desire to do a good job against the threat of overwork. You're welcome to write out what you would do, or just think about it. The PDF versions of the scenarios can also be used to role play in a classroom setting, with one student taking on the role of the librarian and another the role of the person who needs their help.

Playable version at https://people.wou.edu/~bakersc/ScholCom202X/index.html. Additional background available at https://lisoer.wordpress.ncsu.edu/2021/05/18/new-to-the-scn-scholcom-202x-an-interactive-fiction-game/.

Researchers, scholars and scientists main business is scholarly communication. We communicate about our work to others, as we push the boundaries of what we know and the society knows. We question established notions and truths about science. We share our findings with others, and in a way that is popularly known as scholarly communication which emerged with the publication of first journal in 1665. However, the term gained popularity only in the 1970s, as access to peer reviewed and scholarly communication became difficult. This module has four units covering introduction to scholarly communication, peer reviewed journals, electronica journals and databases and the Serials Crisis. At the end of this module, the learner is expected to be able to:
- Explain philosophy, mission, and objectives of scholarly communication
- Describe the process of scholarly communication
- Identify different channels of scholarly communication
- Discuss the dysfunctioning of the scholarly communication
In Unit 1, Introduction to scholarly communication, we have discussed different aspects of scholarly communication – particularly its genesis, importance and ethics of academic publishing, and different communication channels available in academic publishing. Some of these channels are commonly described as primary sources as they provide first-hand testimony or direct evidence concerning a topic under investigation. Historically, scientific journals were initiated by learned societies and other scholarly communities for reporting results of concluded research works or scientific discoveries. Now many forprofit publishers have started publishing research journals.
Unit 2, Communicating with Peer Review Journals, covers two important academic publishing channels, namely peer reviewed journals, conferences and their proceedings. This Unit also highlights different methods and procedures of peer reviewing for publishing primary literature emanated from research studies. The peer reviewing is essential for validating quality of research findings conveyed by researchers, which are subject to fulfilment of ethical standards and appropriate research design, sampling and other methodological issues.
In Unit 3, Electronic journals and databases, we have discussed the emergence of electronic journals in academic and research environment due to wide proliferation of information and communication technologies (ICT) in research communications and academic publishing. Scientific communities and scientific communications from the global South are getting substantive attentions through adaptation of electronic journals and electronic academic databases in the process of research communications.
In Unit 4, the Serials Crisis, we discuss the cost of peer reviewed publications and the problems faced by researchers in developing countries. The focus of this unit is on highlighting the problems and discusses possible solutions including the emergence of open access as one of the solutions. Open access journal publishing helps in mitigating some of the problems associated with serials crisis.
This is Module One of the UNESCO's Open Access Curriculum for Researchers.
Full-Text is available at http://unesdoc.unesco.org/images/0023/002319/231938e.pdf

Jumping into research on a specific subject may feel overwhelming when faced with the vast amount of information that has been published on the subject. In this lesson, students will discover how research is like a conversation that takes place between scholars in a field and will investigate ways they can become part of the conversation over time.

The School of Data aims to make your learning experience as tailored as possible through independent learning modules. Learning modules are all stand-alone and can be taken in any order. To make your learning experience easier, we curated modules into a series of courses - with a focus on data basics as well as specific skills. When you identified the course you're interested in click on "Show Modules" to see all modules you might want to take.

This is the last Module of the course on Open Access for researchers. So far you have studied about Open Access, its history, advantages, initiatives, copyrights and licensing, evaluation matrix for research – all in the context of scholarly communication. In this Module with just two units, we would like to help you share your work in Open Access though repositories and journals. At the end of this module, you are expected to be able to:
- Understand the publication process involved in dissemination of scholarly works;
- Choose appropriate Open Access journals and repositories for sharing research results;
- Use social media to promote personal research work and build reputation.
In Unit 1, we discuss the research publication process at five stages – planning stage, preparing stage, pre-publication stage, publication stage and postpublication stage. We emphasize the importance of social media in sharing and making your work visible to the target groups.
In Unit 2, we focus on sharing your research through OA repositories and Journals. First we discussed the different types of repositories to select and highlighted the steps that you may consider including deposit in your own institutional repositories or in global open repositories. We then discuss the sources of finding and deciding on OA journals. This unit also provides guidance on choosing the right OA journals, as the quality of OA journals is often questioned.
This is Module Five of the UNESCO's Open Access Curriculum for Researchers.
Full-Text is available at http://unesdoc.unesco.org/images/0023/002322/232211E.pdf