All Learning Resources

  • GES DISC Data Cookbook

    A collection of tutorials, called "data recipes" that describe how to use Earth science data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) using easily available tools and commonly used formats for Earth science data such as NetCDF, ASCII, HDF-5, and shapefile.  These tutorials are available to assist those wishing to learn or teach how to obtain and view these data. 

  • Reverb Data Access Cookbook

    A collection of tutorials, called "data recipes" that describe how to access Earth science data from the Earth Observing Clearing House (ECHO) such as MODIS, NRT, ASTER and MERIS data.  These tutorials are available to assist those wishing to learn or teach how to access and order these data.  Links are provided to User Support if the data desired are not available from this collection.

  • ASDC Data Recipes

    A collection of tutorials, called "data recipes" that describe how to obtain and use Earth science data from the Atmospheric Science Data Center, a NASA DAAC (Distributed Active Archive Center) at the NASA Langley Research Center 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. 

  • ASF Data Recipes

    A collection of tutorials, called "data recipes" that describe how to obtain and use Earth science data from the Alaska Satellite Facility, a NASA DAAC (Distributed Active Archive Center) 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. 

  • 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. 

  • NSIDC DAAC Data Recipes

    A collection of tutorials, called "data recipes" that describe how to use Earth science data from NASA's National Snow and Ice Data Center (NSIDC) 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. 

  • 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.

  • 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.

  • 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:
    Introduction
    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 info@data.cam.ac.uk and we would be happy to answer any questions that you have.

  • 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 European 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).
  • 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.

  • 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.

  • 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. 

  • 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 Workflow Curriculum Development

    The purpose of this workshop curriculum is to provide attendees with: A. An understanding of the goals, processes, and responsibilities involved in the creation of a digital preservation program B. Problem-solving and decision-making skills to enable ongoing, collaborative digital preservation throughout technological, organizational, and content changes.

    This workshop will equip participants with a set of skills and knowledge that will enable them to enact programmatic digital preservation within their organization. It is focused on equipping organizations with the capability to implement and manage a digital preservation program. The workshop modules present the requirements of a digital preservation ecosystem from two parallel viewpoints: 1) governance and program management, including the creation of a unified strategy and the need for cross-organizational coordination, balancing the competing priorities of innovation and maintenance, and 2) asset management, including the selection and submission of content to a managed preservation environment, and ongoing post-submission responsibilities.

    Downloadable workshop modules are available in the Best Practices section of the following page:   http://dpn.org/members .  Module topics include:
    1.  Enabling Programmatic Digital Preservation
    2.  Selection
    3.  Preparing for Submission
    4.  Submission and Ingest
    5.  Post-Submission
    6.  Sustainability
     

  • 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:  http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum....

  • 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: 
    http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum...

  • 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:  http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum....

  • Digital Preservation Workshop Module 4: Submission and Ingest

    Module 4 of the Digital Preservation Network's Digital Preservation Workflow Curriculum introduces the concept of transferring submission packages to preservation environments. It underscores the importance of logging transfer, upload, and verification events during ingest for the establishment (or continuation) of an audit trail that will track digital assets throughout their life in the preservation environment. Lecture will provide an overview of best practices for submission and the capture of information produced by the related events. Participants will gain experience with tools that support package transfer and will upload submission packages into a local environment and a cloud or preservation service. 

    For background information about this module including learning objectives, goals, resources and lessons, also see:  http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum 
     

  • Digital Preservation Workshop Module 5: Post Submission

    Module 5 of The Digital Preservation Network's Digital Preservation Workflow Curriculum examines the relationship of the content holders to the preservation service on an ongoing basis following the submission of content. Regardless of whether the preservation environment is internal to the organization, an external service providing organization, or a collaborative consortium, ongoing preservation is a shared responsibility. This module will lay out the various roles, responsibilities, and tasks, and the service framework that will support the establishment of a sustainable preservation program.

    For background information about this module including learning objectives, goals, resources and lessons, also see:  http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum. 

  • Digital Preservation Workshop Module 6: Sustainability

    Module 6 of The Digital Preservation Network's Digital Preservation Workflow Curriculum introduces some of the standards and best practices for digital preservation program assessment, tools and activities for performing assessments, and developing a business case for digital preservation. Finally, the module provides practical next steps for applying knowledge gained through the workshop. 

    For background information about this module including learning objectives, goals, resources and lessons, also see:  http://dpn.org/dpn-admin/resources/digitalpreservationworkshopcurriculum. 

  • The Geoscience Paper of the Future: OntoSoft Training

    This presentation was developed to train scientists on best practices for digital scholarship, reproducibility, and data and software sharing.  It was developed as part of the NSF EarthCube Initiative and funded under the OntoSoft project.  More details about the project can be found at http://www.ontosoft.org/gpf.

    A powerpoint version of the slides is available upon request from ontosoft@gmail.com.

    These OntoSoft GPF training materials were developed and edited by Yolanda Gil (USC), with contributions from the OntoSoft team including Chris Duffy (PSU), Chris Mattmann (JPL), Scott Pechkam (CU), Ji-Hyun Oh (USC), Varun Ratnakar (USC), Erin Robinson (ESIP).  They were significantly improved through input from GPF pioneers Cedric David (JPL), Ibrahim Demir (UI), Bakinam Essawy (UV), Robinson W. Fulweiler (BU), Jon Goodall (UV), Leif Karlstrom (UO), Kyo Lee (JPL), Heath Mills (UH), Suzanne Pierce (UT), Allen Pope (CU), Mimi Tzeng (DISL), Karan Venayagamoorthy (CSU), Sandra Villamizar (UC), and Xuan Yu (UD).  Others contributed with feedback on best practices, including Ruth Duerr (NSIDC), James Howison (UT), Matt Jones (UCSB), Lisa Kempler (Matworks), Kerstin Lehnert (LDEO), Matt Meyernick (NCAR), and Greg Wilson (Software Carpentry).  These materials were also improved thanks to the many scientists and colleagues that have taken the training and asked hard questions about GPFs.

  • Data Collection Part 1: How to avoid a spreadsheet mess - Lessons learned from an ecologist

    Most scientists have experienced the disappointment of opening an old data file and not fully understanding the contents. During data collection, we frequently optimize ease and efficiency of data entry, producing files that are not well formatted or described for longer term uses, perhaps assuming in the moment that the details of our experiments and observations would be impossible to forget. We can make the best of our sometimes embarrassing data management errors by using them as ‘teachable moments’, opening our dusty file drawers to explore the most common errors, and some quick fixes to improve day-to-day approaches to data.
     

  • Data Collection Part 2: Relational databases - Getting the foundation right

  • Data Sharing and Management within a Large-Scale, Heterogeneous Sensor Network using the CUAHSI Hydrologic Information System

    Hydrology researchers are collecting data using in situ sensors at high frequencies, for extended durations, and with spatial distributions that require infrastructure for data storage, management, and sharing. Managing streaming sensor data is challenging, especially in large networks with large numbers of sites and sensors.  The availability and utility of these data in addressing scientific questions related to water availability, water quality, and natural disasters relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into usable data products.  It also depends on the ability of researchers to share and access the data in useable formats.  In this presentation I will describe tools that have been developed for research groups and sites conducting long term monitoring using in situ sensors.  Functionality includes the ability to track equipment, deployments, calibrations, and other events related to monitoring site maintenance and to link this information to the observational data that they are collecting, which is imperative in ensuring the quality of sensor-based data products. I will present these tools in the context of a data management and publication workflow case study for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) network of aquatic and terrestrial sensors.  iUTAH researchers have developed and deployed an ecohydrologic observatory to monitor Gradients Along Mountain to Urban Transitions (GAMUT). The GAMUT Network measures aspects of water inputs, outputs, and quality along a mountain-to-urban gradient in three watersheds that share common water sources (winter-derived precipitation) but differ in the human and biophysical nature of land-use transitions. GAMUT includes sensors at aquatic and terrestrial sites for real-time monitoring of common meteorological variables, snow accumulation and melt, soil moisture, surface water flow, and surface water quality. I will present the overall workflow we have developed, our use of existing software tools from the CUAHSI Hydrologic Information System, and new software tools that we have deployed for both managing the sensor infrastructure and for storing, managing, and sharing the sensor data.

  • Metadata: Standards, tools and recommended techniques

  • Monitoring Resources: web tools promoting documentation, data discovery and collaboration

    The presentation focuses on USGS/​Pacific Northwest Aquatic Monitoring Partnership's (PNAMP) Monitoring Resources toolset.

  • How high performance computing is changing the game for scientists, and how to get involved

  • Best practices for preparing data to share and preserve

    Scientists spend considerable time conducting field studies and experiments, analyzing the data collected, and writing research papers, but an often overlooked activity is effectively managing the resulting data. The goal of this webinar is to provide guidance on fundamental data management practices that investigators should perform during the course of data collection to improve the usability of their data sets.  Topics covered will include data structure, quality control, and data documentation. In addition, I will briefly discuss data curation practices that are done by archives to ensure that data can be discovered and used in the future. By following the practices, data will be less prone to error, more efficiently structured for analysis, and more readily understandable for any future questions that they might help address.

  • Data citation and you: Where things stand today

  • Open data and the USGS Science Data Catalog