All Learning Resources

  • 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.

  • Template Research Data Management workshop for STEM researchers

    These materials are designed as a template for an introductory Research Data Management workshop for STEM postgraduate students and Early Career Researchers. The workshop is interactive and is designed to be run for 2-3 hours depending on which sections of the workshop are delivered. As it is a template workshop there is a lot of material to cover all disciplines, it is unlikely that all sections would be of interest to any one group of researchers. The sections are:
    Backup and file sharing
    How to organise your data well
    Data Tools
    Personal and sensitive data
    Data sharing
    Data Management Plans

    The workshop works best when adapted for a particular discipline and with a maximum of 30 participants. This workshop was developed for the Data Champions programme at the University of Cambridge and is an adaptation of workshops which are run on a regular basis for PhD students and Postdoctoral researchers. If you would like any more information please email and we would be happy to answer any questions that you have.

  • 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

    Fedora OSF Storage Provider

    (under development as of April 2017)

  • LEARN Toolkit of Best Practice for Research Data Management

    The LEARN Project's Toolkit of Best Practice for Research Data Management expands on the issues outlines in the LERU Roadmap for Research Data (2013).  It is freely downloadable, and is a deliverable for the Eruopean Commission.  It includes:

    • 23 Best-Practice Case Studies from institutions around the world, drawn from issues in the original LERU Roadmap;
    • 8 Main Sections, on topics such as Policy and Leadership, Open Data, Advocacy and Costs;
    • One Model RDM Policy, produced by the University of Vienna and accompanied by guidance and an overview of 20 RDMpolicies across Europe;
    • An Executive Briefing in six languages, aimed at senior institutional decision makers.

    The Executive Briefing of the LEARN Toolkit is available in English, Spanish, German, Portuguese, French and Italian translations.

  • 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).
  • 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 – 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.

  • 23 (research data) Things

    23 (research data) Things is self-directed, online learning for anybody who wants to know more about research data. Each of the 23 Things offers a variety of learning opportunities with activities at three levels of complexity: ‘Getting started’, ‘Learn more’ and ‘Challenge me’. All resources used in the program are online and free to use.

  • Structuring and Documenting a USGS Public Data Release

    This tutorial is designed to help scientists think about the best way to structure and document their USGS public data releases. The ultimate goal is to present data in a logical and organized manner that enables users to quickly understand the data. The first part of the tutorial describes the general considerations for structuring and documenting a data release, regardless of the platform being used to distribute the data. The second part of the tutorial describes how these general consideration can be implemented in ScienceBase. The tutorial is designed for USGS researchers, data managers, and collaborators, but some of the content may be useful for non-USGS researchers who need some tips for structuring and documenting their data for public distribution.

  • New England Collaborative Data Management Curriculum

    NECDMC is an instructional tool for teaching data management best practices to undergraduates, graduate students, and researchers in the health sciences, sciences, and engineering disciplines. Each of the curriculum’s seven online instructional modules aligns with the National Science Foundation’s data management plan recommendations and addresses universal data management challenges. Included in the curriculum is a collection of actual research cases that provides a discipline specific context to the content of the instructional modules. These cases come from a range of research settings such as clinical research, biomedical labs, an engineering project, and a qualitative behavioral health study. Additional research cases will be added to the collection on an ongoing basis. Each of the modules can be taught as a stand-alone class or as part of a series of classes. Instructors are welcome to customize the content of the instructional modules to meet the learning needs of their students and the policies and resources at their institutions.

  • 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.

  • Data Management Planning Part 1: overview and a USGS program experience

    Emily Fort of the USGS presents an introduction to data management planning and a USGS program experience.

  • Data Management Planning Part 2: theory and practice in research data management

    Steve Tessler and Stan Smith present an example of a data management planning strategy for USGS science centers.

  • Introduction to the ISO 19115-2 Metadata Standard - DISL Data Management Metadata Training Webinar Series - Part 2

    Begins with a brief overview of how the components of the ISO 19115-2 metadata standard are organized, followed by an example completed metadata record. Overview of how to use NOAA NCEI's ISO workbooks and EDM Wiki as resources for writing ISO metadata. The video is 34 minutes. 

  • Introduction to Data Documentation - DISL Data Management Metadata Training Webinar Series - Part 1

    Introduction to data documentation (metadata) for science datasets. Includes basic concepts about metadata and a few words about data accessibility. Video is about 23 minutes.

  • LP DAAC Data Recipes

    A collection of tutorials that describe how to use Earth science data from NASA's Land Processes Distributed Active Archive Center (LP DAAC) using easily available tools and commonly used formats for Earth science data.  These tutorials are available to assist those wishing to learn or teach how to obtain and view these data. 

  • 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.

  • Digital Preservation Workshop Module 2: Selection

    Module 2 of The Digital Preservation Network's Digital Preservation Workflow Curriculum introduces the concept of selection for digital preservation and how understanding an organization’s collections landscape can help with planning, selection, and prioritization of digital content for preservation. Lectures will discuss planning, and offer criteria and introduce tools to track and document collections and evaluate their readiness to prioritize submission to a digital preservation service. Participants will consider factors such as legal status, “done-ness” (when is an asset ready to be preserved?), and roles and responsibilities for decision making. They will be asked to look at how the sources of content (whether from digitization or borndigital) affect decision making, and will apply what they have learned through discussions and a case study on evaluation. 

    For background information about this module including learning objectives, goals, resources and lessons, also see:

  • Digital Preservation Workshop Module 3: Preparing for Submission

    Module 3 of The Digital Preservation Network's Digital Preservation Workflow Workshop Curriculum focuses on preparing content for submission to a long-term storage service, whether in-house or external to the organization. It will emphasize requisite tasks such as understanding and conforming to submission requirements, local file management prior to submission, and tracking asset status. This module will explore common challenges encountered during this stage in the workflow, such as determining how and when to capture metadata, deciding what is “good enough” to submit, dealing with different content sources (e.g., born-digital vs. digitized), and work through ways of resolving these. A case study will be used to provide participants with experience creating a plan for this stage. A hands-on exercise creating a preservation package according to the specifications of a long-term storage service will expose participants to common tools and approaches for compliance with requirements. It will conclude with a discussion of how the processes reviewed during this module can be implemented in a program that will support all organizational content regardless of type, source, or owner.

    For background information about this module including learning objectives, goals, resources and lessons, also see:

  • Digital Preservation Workshop Module 1: Programmatic Digital Preservation

    Module 1 of The Digital Preservation Network's Digital Preservation Curriculum provides an overview of the workshop contents and approach. It begins with a discussion of the goal of the workshop — providing participants with the capacity to ensure valuable content is stored in a managed environment over the long-term, and enact digital preservation programs at their organizations — and provides an opportunity for participants to discuss what this might look like within different organizational contexts. Participants will look at the factors involved in operationalizing a digital preservation program, and the pathway that content travels along as it nears a long-term storage environment. This module introduces the problem-solving and decision-making framework that will run throughout all subsequent modules.

    For background information about this module including learning objectives, goals, resources and lessons, also see: