All Learning Resources
Data citation and you: Where things stand today
Open data and the USGS Science Data Catalog
Data Rescue: Packaging, Curation, Ingest, and Discovery
Data Conservancy was introduced to Data Rescue Boulder through our long-time partner Ruth Duerr of Ronin Institute. Through our conversations, we recognized that Data Rescue Boulder has a need to process large number of rescued data sets and store them in more permanent homes. We also recognized that Data Conservancy along with Open Science Framework have the software infrastructure to support such activities and bring a selective subset of the rescued data into our own institution repository. We chose the subset of data based on a selection from one of the Johns Hopkins University faculty members.
This video shows one of the pathways through which data could be brought into a Fedora-backed institutional repository using our tools and platforms
Data Conservancy screen cast demonstrating integration between the Data Conservancy Packaging Tool, the Fedora repository, and the Open Science Framework. Resources referenced throughout the screen cast are linked below.
DC Package Tool GUI
DC Package Ingest
- Package Ingest release page
- Fedora API Extension Architecture Home, GitHub, and Docker-based demo
- API-X funding provided by IMLS grant #LG-70-16-0076-16
Fedora OSF Storage Provider
(under development as of April 2017)
Open Principles in Education - Building Bridges, Empowering Communities
This presentation shared experiences from “Geo for All” initiative on the importance of having open principles in education for empowering communities worldwide . Central to “Geo for All” mission is the belief that knowledge is a public good and Open Principles in Education will provide great opportunities for everyone. By combining the potential of free and open software, open data, open standards, open access to research publications, open education resources in Geospatial education and research will enable the creation of sustainable innovation ecosystem . This is key for widening education opportunities, accelerating new discoveries and helping solving global cross disciplinary societal challenges from Climate change mitigation to sustainable cities. Service for the benefit and betterment of humanity is a key fundamental principle of “Geo for All” and we want to contribute and focus our efforts for the United Nations Sustainable Development Goals. We aim to create openness in Geo Education for developing creative and open minds in students which is critical for building open innovation and contributes to building up Open Knowledge for the benefit of the whole society and for our future generations. The bigger aim is to advance STEM education across the world and bring together schools, teachers and students across the world in joint projects and help building international understanding and global peace.
Unidata Data Management Resource Center
In this online resource center, Unidata provides information about evolving data management requirements, techniques, and tools. They walk through common requirements of funding agencies to make it easier for researchers to fulfill them. In addition, they explain how to use some common tools to build a scientific data managment workflow that makes the life of an investigator easier, and enhances access to their work. The resource center provides information about: 1) Agency Requirements, 2) Best Practices, 3) Tools for Managing Data, 4) Data Management Plan Resources, 5) Data Archives, and 6) Scenarios and Use Case.
USGS Data Management Training Modules – the Value of Data Management
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. In this module, you will learn how to: 1. Describe the various roles and responsibilities of data management. 2. Explain how data management relates to everyday work and the greater good. 3. Motivate (with examples) why data management is valuable. These basic lessons will provide the foundation for understanding why good data management is worth pursuing.
USGS Data Management Training Modules – Planning for Data Management
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. In this module, we will provide an overview of data management plans. First, we will define and describe Data Management Plans, or DMPs. We will then explain the benefits of creating a DMP. Finally, we will provide instructions on how to prepare a DMP, including covering key components common to most DMPs.
USGS Data Management Training Modules – Best Practices for Preparing Science Data to Share
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. In this module, you’ll learn:
The importance of maintaining well-managed science data
Nine fundamental practices scientists should implement when preparing data to share
Associated best practices for each data management habit
USGS Data Management Training Modules – Science Data Lifecycle
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. By the end of this module, you should be able to answer the following questions… What is a science data lifecycle? Why is a science data lifecycle important and useful? What are the elements of the USGS science data lifecycle, and how are they connected? What are the difference roles and responsibilities? Where do you go if you need more information?
USGS Data Management Training Modules – Planning for Data Management Part II
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. By the end of this course you should know the difference between data management plans and project plans; you should know how to use the DMPTool to create a data management plan; and you should understand the basic information that should go into a data management plan.
USGS Data Management Training Modules—Metadata for Research Data
This is one of six interactive modules created to help researchers, data stewards, managers and the public gain an understanding of the value of data management in science and provide best practices to perform good data management within their organization. This module covers metadata for research data. The USGS Data Management Training modules were funded by the USGS Community for Data Integration and the USGS Office of Organizational and Employee Development's Technology Enabled Learning Program in collaboration with Bureau of Land Management, California Digital Library, and Oak Ridge National Laboratory. Special thanks to Jeffrey Morisette, Dept. of the Interior North Central Climate Science Center; Janice Gordon, USGS Core Science Analytics, Synthesis, and Libraries; National Indian Programs Training Center; and Keith Kirk, USGS Office of Science Quality Information.
DataONE Data Management Module 06: Data Protection and Backups
This module covers the difference between data protection, backup, archiving and preservation, best practices for backing up and preserving data.
DataONE Data Management Module 08: Data Citation
This module defines data citation, explains benefits of data citation, and provides examples and best practices for data citation.
DataONE Data Management Module 09: Analysis and Workflows
This module covers types of data analyses, introduction to reproducibility, provenance, and workflows, informal (conceptual) and formal (executable) workflows.
DataONE Data Management Module 04: Data Entry and Manipulation
This module covers best practices for data entry, data entry and data manipulation tools. It covers best practices for creating organized spreadsheets and data files, use of descriptive file names, and software options for data manipulation.
DataONE Data Management Module 10: Legal and Policy Issues
Legal and policy issues, copyright and licenses, data restrictions and ethical considerations.
Planning for Software Reproducibility and Reuse
Many research projects depend on the development of scripts or other software to collect data, perform analyses or simulations, and visualize results. Working in a way that makes it easier for your future self and others to understand and re-use your code means that more time can be dedicated to the research itself, rather than troubleshooting hard-to-understand code, resulting in more effective research. In addition, by following some simple best practices around code sharing, the visibility and impact of your research can be increased. In this introductory session, you will:
- learn about best practices for writing, documenting (Documentation), and organizing code (Organization & Automation),
- understand the benefits of using version control (Version Control & Quality Assurance),
- learn about how code can be linked to research results and why (Context & Credit),
- understand why it is important to make your code publishable and citable and how to do so (Context & Credit),
- learn about intellectual property issues (Licensing),
- learn about how and why your software can be preserved over time (Archiving).
Preparing Your Data Management Plan
Grant proposals for a growing number of funders require data management plans, including the National Science Foundation. Developing a competitive data management plan requires understanding and effectively addressing the many aspects of research data management that funders and reviewers emphasize (e.g., plans for research data security, sharing, and documentation). Join Data Management Services for a training session on preparing data management plans. During this one-hour workshop, we will cover the research data questions one should answer in creating an effective, competitive plan. Participants will have an opportunity to ask data management and planning questions specific to their research.
ISRIC Spring School
The ISRIC Spring School aims to introduce participants to world soils, soil databases, software for soil data analysis and visualisation, digital soil mapping and soil-web services through two 5-day courses run in parallel. Target audiences for the Spring School include soil and environmental scientists involved in (digital) soil mapping and soil information production at regional, national and continental scales; soil experts and professionals in natural resources management and planning; and soil science students at MSc and PhD level. Examples courses include "World Soils and their Assessment (WSA) and Hands-on Global Soil Information Facilities (GSIF). Data management topics are included within the course topics.
ISRIC - World Soil Information Educational Videos
YouTube Channel of videos on various topics related to world soils data creation and management. Example categories of videos include Digital Soil Mapping; Screencast: How to use ISRIC's Soil Data Hub; Sustainable Soil Managment; and Global Soil Information Facilities.