A first person story is presented to the students to hook their interest in the disease. Using a jigsaw approach, students will learn about the fundamentals of Pompe disease and share information during a whole class discussion.

The Pompe Predicament was developed as a part of Biomedical Explorations: Bench to Bedside which was supported by the National Center for Research Resources and the Division of Program Coordination, Planning, and Strategic Initiatives of the National Institutes of Health through Grant Number R25RR023294. Additional support provided by the University of Florida (UF) and the UF Center for Precollegiate Education and Training.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

The Portage Network offers a range of training materials – everything from one-page guides to online training modules and videos – that span the research data life cycle.

With the assistance of the Portage National Training Expert Group, the Portage Network of Experts continues to develop new bilingual training aids and online modules to support a community of practice for research data management in Canada.

These materials are intended for researchers, library data specialists, research data managers, and discipline and functional experts across the research data landscape. All training resources created by Portage are licensed under CC BY-NC 4.0 and are free to share and adapt for your own needs.

If you have questions about developing RDM training at your institution or would like assistance with creating in-person or online training resources or opportunities, please contact RDM-GDR@alliancecan.ca.

Relatório técnico conclusivo, no qual - por meio de indicadores deduzidos obtidos na realização de estudo prévio de avaliação, durante pesquisa de doutorado, e vinculado à melhoria contínua de seus resultados - é apresentado programa de ações que dá suporte à gestão integrada de resíduos sólidos e com vistas à melhoria da cooperação intersetorial e engajamento das partes interessadas envolvidas. A iniciativa provém do Programa Regional de Pós-Graduação em Desenvolvimento e Meio Ambiente (Rede PRODEMA), proposta interdisciplinar, interinstitucional e intrarregional, da qual participam nove instituições de ensino superior, que trabalham para propor resolução de problemas locais e regionais. Se aplicado, pode gerar mudanças efetivas na área ambiental, social, econômica, cultural e jurídica, colaborando com governos locais municipais e sua relação com os cidadãos. Vale destacar ainda que este produto atende a seis objetivos de desenvolvimento sustentável, da ONU, especificamente o ODS 1 – Erradicação da pobreza, ODS 3 – Saúde e bem-estar, ODS 6 – Água potável e saneamento, ODS 10 – Redução das desigualdades, ODS 12 – Consumo e produção responsáveis e o ODS 17 – Parcerias e meios de implementação.

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Despite being often feared, spiders are mysterious and intriguing, offering a useful foundation for the effective teaching and learning of scientific concepts and processes. In order to provide an entryway for teachers and students—as well as scientists themselves—into the biology of spiders, we compiled a list of 99 record breaking achievements by spiders (the “Spider World Records”).

We chose a world-record style format, as this is known to be an effective way to intrigue readers of all ages. We highlighted, for example, the largest and smallest spiders, the largest prey eaten, the fastest runners, the highest fliers, the species with the longest sperm, the most venomous species, and many more. We hope that our compilation will inspire science educators to embrace the biology of spiders as a resource that engages students in science learning.

By making these achievements accessible to non-arachnologists and arachnologists alike, we suggest that they could be used: (i) by educators to draw in students for science education, (ii) to highlight gaps in current organismal knowledge, and (iii) to suggest novel avenues for future research efforts. Our contribution is not meant to be comprehensive, but aims to raise public awareness on spiders, while also providing an initial database of their record breaking achievements.

An Eco ed resource based on the rainforest explorers of the 19th C. They went to the forest to record and classify the plants, animals and people. The site has lessons for Eco events like Earth Day as well as 10,000 rare images and the explorers' journals. Within the 700 pages of text, all locations, plant and animal names are linked to their images. Exploring even one page of the text will raise Eco awareness. There is an extensive index for reports and projects. This is a family project that was approved by the British govt. for Curriculum OnLine, by the National Wildlife Federation and the Da Vinci Science Center.

Comments about Remember the Rainforest:
Rob Fox, education director Da Vinci Science Center : “ Fantastic !”

Ken Higgins, regional director and founder of Green Schools Alliance :
“I did open the link, and it is very impressive. I passed it along to our lower school and middle school science teachers, and have posted it with my sustainability educators group in New York.”

This course was developed and taught by Ben Marwick, Professor of Archaeology at University of Washington. It is a requirement for the UW Master of Science in Data Science, introduces students to the principles and tools for computational reproducibility in data science using R. Topics covered include acquiring, cleaning and manipulating data in a reproducible workflow using the tidyverse. Students will use literate programming tools, and explore best practices for organizing data analyses. Students will learn to write documents using R markdown, compile R markdown documents using knitr and related tools, and publish reproducible documents to various common formats. Students will learn strategies and tools for packaging research compendia, dependency management, and containerising projects to provide computational isolation.

ABSTRACT: The online computer science classroom is growing, but there is little research on how to teach inclusive design online. As a result, online CS students are graduating without learning how to avoid bias in their software designs. Through the lens of the Inclusive Design Pedagogical Content Knowledge (PCK), this thesis analyzes a set of curricular activities that were embedded into online post-baccalaureate computer science courses. The contributions of this work include: (1) a set of takeaways outlining what I learned from student responses to the activities and (2) the second iteration of the Inclusive Design PCKs that can be applied in both the online and in-person classrooms.

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.

The Research Data Curation and Management Bibliography includes over 800 selected English-language articles and books that are useful in understanding the curation of digital research data in academic and other research institutions. It covers topics such as research data creation, acquisition, metadata, provenance, repositories, management, policies, support services, funding agency requirements, open access, peer review, publication, citation, sharing, reuse, and preservation. Most sources have been published from January 2009 through December 2019; however, a limited number of earlier key sources are also included. The bibliography has links to included works. Abstracts are included in this bibliography if a work is under certain Creative Commons Attribution licenses. It is available as a 250-page PDF or a website.

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.

CITATION: Gender-Inclusiveness Personas vs. Stereotyping: Can We Have it Both Ways? Charles Hill, Maren Haag, Alannah Oleson, Chris Mendez, Nicola Marsden, Anita Sarma, Margaret Burnett, ACM Conference on Human Factors in Computing Systems (CHI'17), May 2017, pp. 6658-6671. ABSTRACT: Personas often aim to improve product designers' ability to "see through the eyes of" target users through the empathy personas can inspire - but personas are also known to promote stereotyping. This tension can be particularly problematic when personas (who, of course as "people" have genders) are used to promote gender inclusiveness - because reinforcing stereotypical perceptions can run counter to gender inclusiveness. In this paper we explicitly investigate this tension through a new approach to personas: one that includes multiple photos (of males and females) for a single persona. We compared this approach to an identical persona with only one photo using a controlled laboratory study and an eye-tracking study. Our goal was to answer the following question: is it possible for personas to encourage product designers to engage with personas while at the same avoiding promoting gender stereotyping? Our results are encouraging about the use of personas with multiple pictures as a way to expand participants' consideration of multiple genders without reducing their engagement with the persona. VIDEO: https://www.youtube.com/watch?v=6f1aJhWGfLM

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

Here web link lists all the documents related to the Open Educational Resources (OER).

For decades, the media have given enormous attention to sensational claims that vague lights in the sky are actually extra-terrestrial spacecraft. Recently, there has been a flurry of misleading publicity about UFOs on military photographs. A sober examination of these claims reveals that there is a lot LESS to them than first meets the eye: when there is enough evidence, UFO claims can be explained by terrestrial or celestial phenomena (including lights from human craft and re-entering space junk). This up-to-date guide provides key resources available free on the Web, to help scientists, educators, students, and journalists learn about the skeptical perspective (and the background stories) behind these claims.