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Data

This collection contains materials regarding open data, research data management, and other aligned open science practices.

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AI skills for engineers: Data creation and collection
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CC BY-NC-SA
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A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

Subject:
Applied Science
Engineering
Material Type:
Full Course
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Jie Yang
Ujwal Gadiraju
Date Added:
06/30/2023
Analyzing Institutional Publishing Output: A Short Course
Unrestricted Use
CC BY
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This short course provides training materials about how to create a set of publication data, gather additional information about the data through an API (Application Programming Interface), clean the data, and analyze the data in various ways. Developing these skills will assist academic librarians who are:

Negotiating a renewal of a journal package or an open access publishing agreement,
Interested in which journals the institution's authors published in or which repositories the institution’s authors shared their works in,
Looking to identify publications that could be added to your repository,
Searching for authors who do or do not publish OA for designing outreach programs, or
Tracking how open access choices have changed over time.
After completing the lessons, the user will be able to gain an understanding of an institution’s publishing output, such as number of publications per year, open access status of the publications, major funders of the research, estimates of how much funding might be spent towards article processing charges (APCs), and more. The user will also be better prepared to think critically about institutional publishing data to make sustainable and values-driven scholarly communications decisions.

The course is presented in two sections. Section 1 describes how to build a dataset. Section 2 describes a free, open source tool for working with data. Examples of how to do analyses both in OpenRefine and Microsoft Excel are provided.

This short course was created for the Scholarly Communication Notebook. The file "Analyzing Institutional Publishing Output-A Short Course.docx" serves as a table of contents for the materials.

Subject:
Applied Science
Information Science
Material Type:
Unit of Study
Author:
Ana Enriquez
Allison Langham-Putrow
Date Added:
03/23/2022
Analyzing and Making Mathematical and Historical Claims from (Linear) Data Representations
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A statistics lesson on describing and making claims from data representations, specifically linearly increasing data. Applies ideas of rate-of-change to develop writing a linear equation to fit the data, using the equation to interpolate and extrapolate additional information, and integrating the mathematical interpretation appropriately into a social sciences argument.

Subject:
Mathematics
Material Type:
Lesson Plan
Date Added:
03/31/2015
Archiving for the Future: Simple Steps for Archiving Language Documentation Collections
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CC BY-SA
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Archiving for the Future is a free training course designed to teach language documenters, activists, and researchers how to organize, arrange, and archive language documentation, revitalization, and maintenance materials and metadata in a digital repository or language archive. Then entire course can be completed in approximately 3-5 hours.

This course was developed by the staff of the Archive of the Indigenous Languages of Latin America at the University of Texas at Austin in consultation with representatives of various DELAMAN (https://www.delaman.org/) archives and other digital data repositories in the United States, the United Kingdom, the European Union, Australia, and Cameroon.

The course material is based upon work supported by the National Science Foundation under Grant No. BCS-1653380 (September 1, 2016 to August 31, 2020). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Subject:
Anthropology
Applied Science
Arts and Humanities
Ethnic Studies
Information Science
Languages
Linguistics
Social Science
Material Type:
Full Course
Interactive
Author:
Alicia Niwagaba
Elena Pojman
Ryan Sullivant
Susan Smythe Kung
Date Added:
11/05/2020
Australian Research Data Commons (ARDC) Resources
Unrestricted Use
CC BY
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ARDC curate a collection of resources for researchers, librarians and eResearch professionals. The topics covered by resources and guides range from ethics and sensitive data to managing data; from research data policy and licensing to training and teaching research data management skills.

Subject:
Applied Science
Information Science
Material Type:
Module
Primary Source
Author:
Australian Research Data Commons
Date Added:
06/24/2022
Backups, Archives & Data Preservation
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Public Domain
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There are several important elements to digital preservation, including data protection, backup and archiving. In this lesson, these concepts are introduced and best practices are highlighted with case study examples of how things can go wrong. Exploring the logistical, technical and policy implications of data preservation, participants will be able to identify their preservation needs and be ready to implement good data preservation practices by the end of the module.

Subject:
Applied Science
Education
Higher Education
Information Science
Material Type:
Lesson
Provider:
DataONE
Author:
DataONE Community Engagement & Outreach Working Group
Date Added:
11/21/2020
Best Practices in Data Collection and Management Workshop
Unrestricted Use
Public Domain
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Ever need to help a researcher share and archive their research data? Would you know how to advise them on managing their data so it can be easily shared and re-used? This workshop will cover best practices for collecting and organizing research data related to the goal of data preservation and sharing. We will focus on best practices and tips for collecting data, including file naming, documentation/metadata, quality control, and versioning, as well as access and control/security, backup and storage, and licensing. We will discuss the library’s role in data management, and the opportunities and challenges around supporting data sharing efforts. Through case studies we will explore a typical research data scenario and propose solutions and services by the library and institutional partners. Finally, we discuss methods to stay up to date with data management related topics.

Subject:
Applied Science
Computer Science
Information Science
Material Type:
Lesson
Primary Source
Author:
Andrea Denton
Sherry Lake
Date Added:
05/16/2022
CESSDA Consortium - Data Management Expert Guide
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CC BY-SA
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Data Management Expert Guide
This guide is designed by European experts to help social science researchers make their research data Findable, Accessible, Interoperable and Reusable (FAIR).

You will be guided by different European experts who are - on a daily basis - busy ensuring long-term access to valuable social science datasets, available for discovery and reuse at one of the CESSDA social science data archives.

You can download the full DMEG for your personal study offline (DOI: 10.5281/zenodo.3820473). PDFs for every single chapter are also available for being printed as handouts for training.

Subject:
Applied Science
Information Science
Social Science
Material Type:
Primary Source
Reading
Unit of Study
Author:
CESSDA
Date Added:
05/07/2022
C++ Programming
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CC BY
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The student will learn the mechanics of editing and compiling a simple program written in C++ beginning with a discussion of the essential elements of C++ programming: variables, loops, expressions, functions, and string class. Next, the student will cover the basics of object-oriented programming: classes, inheritance, templates, exceptions, and file manipulation. The student will then review function and class templates and the classes that perform output and input of characters to/from files. This course will also cover the topics of namespaces, exception handling, and preprocessor directives. In the last part of the course, the student will learn some slightly more sophisticated programming techniques that deal with data structures such as linked lists and binary trees. Upon successful completion of this course, students will be able to: Compile and execute code written in C++ language; Work with the elementary data types and conditional and iteration structures; Define and use functions, pointers, arrays, struct, unions, and enumerations; Write C++ using principles of object-oriented programming; Write templates and manipulate the files; Code and use namespaces, exceptions, and preprocessor instructions; Write a code that represents linked lists and binary trees; Translate simple word problems into C++ language. (Computer Science 107)

Subject:
Applied Science
Computer Science
Material Type:
Full Course
Provider:
The Saylor Foundation
Date Added:
11/16/2011
CREATES
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CC BY-NC-SA
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CREATES is a set of 6 steps that help learners read and critically analyze scientific papers. The CREATES method, pioneered by Dr. Sally Hoskins, has a demonstrated positive impact on undergraduate students' self-confidence in scientific reading, as well as in their general perceptions of and beliefs about science and scientific thinking (Hoskins, et. al, 2017).

The new CREATES site, created in collaboration with Jordan Moberg Parker, UCLA's Director of Undergraduate Laboratory Curriculum and Assessment in Microbiology, Immunology, and Molecular Genetics, uses interactive media, step-by-step directions, and detailed annotation of authentic examples to guide students through the process.

Subject:
Applied Science
Life Science
Physical Science
Material Type:
Full Course
Interactive
Author:
Doug Worsham
Kian Ravaei
Xinyi(Alex) Yan
Dr. Jordan Moberg Parker
Date Added:
07/20/2020
The Carpentries
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CC BY
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Data Carpentry, Software Carpentry, and Library Carpentry are branches under The Carpentries known as a learning program to develop and teach workshops on the fundamental data and coding skills needed to conduct research. Participants can request to host a workshop at their institution or organization, attend a workshop, and/or involve by becoming a certified instructor, contributing in developing the content, or just simply support the programs. All lessons in either Carpentry branch can be used to teach introduction courses in data science/library information sciences.

Subject:
Applied Science
Computer Science
Information Science
Material Type:
Full Course
Primary Source
Author:
The Carpentries
Date Added:
12/18/2021
The Changing Geographic Distribution of Malaria with Global Climate Warming
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CC BY
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This activity engages students in the analysis of climate data to first find areas in the southern United States that are now close to having conditions in which the malaria parasite and its mosquito hosts thrive and then attempt to forecast when areas might become climatically suitable.

Subject:
Applied Science
Career and Technical Education
Environmental Science
Environmental Studies
Physical Science
Material Type:
Activity/Lab
Provider:
CLEAN: Climate Literacy and Energy Awareness Network
Provider Set:
CLEAN: Climate Literacy and Energy Awareness Network
Author:
Carleton College
Kendra Murray
Mary Savina
SERC Teaching Quantitative Skills in the Geosciences Collection
Date Added:
06/19/2012
Companion Resource (Pathfinder) for Create Accurately and Interactive Dashboards with Tableau
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     This is a pathfinder designed for users who are new to Tableau Desktop and Tableau Public.  The purpose of this pathfinder is to be a companion resource to the February 25, 2023 presentation Create Accurately and Interactive Dashboards with Tableau.  The Tableau Student Ambassador presenters of the workshop were Taiwo Adegite, Junior Analyst; and Zena Patton, Corporate Learning Professional, and Librarian.  To learn more about the Tableau Community Leader Ambassador program, go to the following link  https://www.tableau.com/community/community-leaders/ambassadors      This companion resource is an artifact of a global, collaborative effort between Taiwo Adegite (Nigeria), Junior Analyst; and Zena Patton (United States of America), Corporate Learning Professional, and Librarian.Last update April 15, 2023.  This update includes resources from Flip the Tableau! Learning Experience.   

Subject:
Information Science
Management
Material Type:
Diagram/Illustration
Lecture Notes
Reading
Student Guide
Author:
Zena Patton
Taiwo Adegite
Date Added:
02/17/2023
Computation and Visualization in the Earth Sciences
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CC BY-NC-SA
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In EARTH 801, you will develop skills in a programming language designed for visual arts and visualization while exploring Earth science topics. Specifically, you'll learn and practice digital graphics capabilities in order to render Earth science concepts that are otherwise difficult to visualize due to complicated space and time scales. Here, you will interact with large, open, freely-available data sets by collecting, plotting, and analyzing them using a variety of computational methods. You'll be ready to teach secondary school students a range of Next Generation Science Standard skills involving data collecting, manipulation, analysis, and plotting. You'll also read and discuss current research regarding the teaching, learning, and evaluation of visualization skills, as well as multiple external representations of science concepts.

Subject:
Applied Science
Computer Science
Environmental Science
Information Science
Material Type:
Full Course
Provider:
Penn State College of Earth and Mineral Sciences
Author:
Eliza Richardson
Date Added:
10/07/2019
Creating and Analyzing a Binary Map Using FRED® Maps
Read the Fine Print
Educational Use
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This lesson demonstrates how easy it is to create a binary FRED map. Students search for state-level data on average weekly earnings and visualize them in FRED. The goals are for students to customize a map, observe patterns in mapped data, and note differences across geographical areas.

Subject:
Economics
Social Science
Material Type:
Activity/Lab
Provider:
Federal Reserve Bank of St. Louis
Provider Set:
Economic Lowdown Lessons
Author:
Diego Mendez-Carbajo
Mark Bayles
Date Added:
02/23/2023
DATUM for Health: Research data management training for health studies
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Abstract
Training materials. The DATUM for Health training programme covers both generic and discipline-specific issues, focusing on the management of qualitative, unstructured data, and is suitable for students at any stage of their PhD. It aims to provide students with the knowledge to manage their research data at every stage in the data lifecycle, from creation to final storage or destruction. They learn how to use their data more effectively and efficiently, how to store and destroy it securely, and how to make it available to a wider audience to increase its use, value and impact.

Subject:
Applied Science
Computer Science
Information Science
Material Type:
Activity/Lab
Module
Primary Source
Author:
Julie Mcleod
Date Added:
05/06/2022
Data Analysis and Workflows
Unrestricted Use
Public Domain
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Understanding the types, processes, and frameworks of workflows and analyses is helpful for researchers seeking to understand more about research, how it was created, and what it may be used for. This lesson uses a subset of data analysis types to introduce reproducibility, iterative analysis, documentation, provenance and different types of processes. Described in more detail are the benefits of documenting and establishing informal (conceptual) and formal (executable) workflows.

Subject:
Applied Science
Education
Higher Education
Information Science
Material Type:
Lesson
Provider:
DataONE
Author:
DataONE Community Engagement & Outreach Working Group
Date Added:
11/21/2020
Data Citation
Unrestricted Use
Public Domain
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Data citation is a key practice that supports the recognition of data creation as a primary research output rather than as a mere byproduct of research. Providing reliable access to research data should be a routine practice, similar to the practice of linking researchers to bibliographic references. After completing this lesson, participants should be able to define data citation and describe its benefits; to identify the roles of various actors in supporting data citation; to recognize common metadata elements and persistent data locators and describe the process for obtaining one, and to summarize best practices for supporting data citation.

Subject:
Applied Science
Education
Higher Education
Information Science
Material Type:
Lesson
Provider:
DataONE
Author:
DataONE Community Engagement & Outreach Working Group
Date Added:
11/21/2020