Confluence Retirement

In an effort to consolidate USGS hosted Wikis, myUSGS’ Confluence service is scheduled for retirement on January 27th, 2023. The official USGS Wiki and collaboration space is now SharePoint. Please migrate existing spaces and content to the SharePoint platform and remove it from Confluence at your earliest convenience. If you need any additional information or have any concerns about this change, please contact Thank you for your prompt attention to this matter.

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Amanda Liford is a science data manager at in the Science Data Management Branch within the USGS Science Analytics and Synthesis program. She is a co-facilitator of the CDI since 2019.


  1. CDI will be hosting a final Carpentries training covering Python, Shell, and Git on October 26-27. More information available here:
  2. The CDI FY2022 Request for Proposals is now open!
    1. The themes are 1) enabling data connection, data readiness, and data comprehension in support of USGS and Administration research and development priorities such as climate change, renewable energy, and the “Conserving and Restoring America the Beautiful” report, and 2) advancing equity in data, including approaching data collection with the goal of unbiased representation, and considering the audience for data delivery and reducing barriers to broad access and understanding, especially for underserved communities.
    2. Schedule:
      1. Wednesday, September 15, 1PM ET: RFP Information Session
      2. Friday, October 15, 5PM ET: Submission Deadline for Statements of Interest
      3. Wednesday, October 20, 1-2:30PM ET: SOI Lightning Presentation
  3. Zack Bowen shared more about the Landscape Science Strategy report, available here
  4. Sky Bristol delved into his R2E20 Model and the impetus and thinking behind it, notes below.


Welcome and Opening Announcements

  1. The Future of Work
    1. Leslie presented audience responses on predictions on the future of work, like less travel and more video conferencing, decentralized organization of functional groups that collaborate across domains and places, and virtual-first collaboration and professional development approaches.
  2. Intro to Python, Shell, and Git, Oct 26-27
    1. We will be hosting our final Carpentries training on October 26-27.
    2. The course will cover:
      1. Data analysis and visualization in Python
      2. Working with core data structures
      3. Using conditionals and loops
      4. Writing custom functions
      5. Creating customized plots
      6. More information:
  3. FY2022 CDI Request for Proposals
    1. The FY22 RFP is now open!
      1. The purpose of the CDI FRP is to build USGS capabilities in data integration and management
      2. The CDI RFP increases communication across boundaries and creates opportunities to work with people outside of your normal program
    2. Two-phase RFP
      1. Phase 1: statement of interest
        1. Short, 1 page description
        2. Lightning presentation
        3. Commenting and voting by CDI members
        4. Top ranked SOIs are invited to submit a full proposal
      2. Phase 2: invited full proposal
        1. Proposal narrative
        2. Review panel
        3. Final review by executive leaders
    3. 2022 Themes
      1. Enabling data connection, data readiness, and data comprehension in support of USGS and Administration research and development priorities such as climate change, renewable energy, and the “Conserving and Restoring America the Beautiful” report.
      2. Advancing equity in data
        1. Equity in data includes
          1. Approaching data collection with the goal of unbiased representation
          2. Considering the audience for data delivery and reducing barriers to broad access and understanding, especially for underserved communities
    4. CDI RFP Schedule
      1. Wed, Sept 15, 1PM ET: RFP Information Session
      2. Fri, Oct 15, 5PM ET: Submission Deadline for SOI
      3. Wed, Oct 20, 1-2:30PM ET: SOI Lightning Presentations
  4. Get started
    1. View RFP Guidance on CDI SharePoint
    2. Discuss ideas on Microsoft Teams channel
    3. Send questions to the Teams channel or to


  1. eDNA
    1. 5th Annual eDNA Technical Exchange workshop, Oct 19-21
    2. NOAA ‘omics seminar series: 3rd Wed of the month at 12ET
    3. Feb 1-4; National Workshop on Marine eDNA
  2. Tech Stack
    1. September 9, TerrainR – generating 3D Landscape Visualizations Using R and Unity
  3. DevOps
    1. Next event: October 5, ESRI ArcGIS Enterprise Kubernetes Platform – Deploying on CHS
  4. Inland/Coastal Bathymetry Collaboration Area
    1. Next event: September 23, 10:30AM CT, Monthly Bathymetry Research Coordination Meeting
  5. DataViz
    1. Next event: September 16th, 1PMET, Beyond Bars and Box Plots – Chart alternatives with ggplot2
  6. Imagery
    1. Next event: October 21, 2PM ET, Imagery Data Management Workflows
    2. Cian Dawson: Check out the beta interactive hydrograph announcement I mentioned in today’s call, using webcams that are part of the Storm Summary Timelapse network
  7. Usability
    1. Next event: October 6 and 20, 3PM ET, User Centered Design Process – Evaluation: presentation and demo
  8. Data Management
    1. Next event: September 13, 2PM ET, Data Reports & other Companion Publications: How data and publishing work together

USGS Landscape Science Strategy - Zack Bowen, USGS

  1. Landscape Science Strategy 2020-2030:
  2. Defining terms
    1. Landscape science – aiming to look at ecosystems and interacting components; use this understanding to help people make policy and management decisions (the what)
    2. Coproduction – working closely with research partners, managers, and stakeholders to make decisions together (the how)
    3. Actionable science – things that people can take and put into use with management actions or policy decisions (the outcome)
  3. Why do we need this strategy?
    1. DOI priorities of clean energy, tribal nations, equity and environmental justice demand an integrated approach with our science efforts
    2. We have a complex landscape of resources.
  4. Goals and Actions
    1. Goal A: deliver science and insights that are used in landscape management
    2. Goal B: understand and communicate how landscapes have changed and will change
    3. Goal C: engage in science that transcends disciplinary bounds
    4. Action 1: build approaches that support our partners
    5. See slides for more.
  5. Example products
    1. Greater Sage Grouse science and tech
      1. Project goal: compile recently published GRSG science, summarize key information relevant to managers for each article, produce a synthesis for managers
      2. Need: inform decisions and potential updates to RMPs within the greater sage grouse range
      3. Products: 2 USGS open-file reports, online searchable tool
  6. Alignment – USGS Science Strategy
    1. Data Acquisition and Management
    2. Modeling and Prediction
    3. Delivery of Actionable Intelligence
      1. A lot of overlap in the Landscape Science Strategy
    4. Science to support strong decision-making in the BLM: quality data, relevant science, standard analysis, best practices
      1. Also overlaps with USGS Science Strategy and Landscape Science Strategy
  7. Conserving and Restoring America the Beautiful contains DOI priorities that directs us to produce data and products to implement the initiative to conserve 30% of U.S. lands and water
  8. Invitation
    1. Identify shared management information needs for data, science, and tools to support decisions
    2. Expand on existing projects and relationships across DOI
    3. Develop an implementation plan

Is there a gap between research and operations in the USGS, and how do we fill it?  - Sky Bristol, USGS

  1. Wanted to explore the notion that USGS is behind other contemporaries in terms of data capabilities (in comparison to GeoScience Australia, etc.)
    1. Just focusing on the ‘portal’ idea that GeoScience Australia has implemented for some of their data: there are two parts to the portals. Portal includes catalog of all their products, can create a persona to bring back specific data/products. In USGS, we have different catalogs for publications, data, models, etc.
    2. GeoScience Australia also have nimble, responsive tools that can produce visualizations.
  2. Spoke to people in USGS to try to get to the core of what the problems might be
    1. Hero Development Environments – one hero that takes on a database, capability, etc., maintains it. Some things remain sustainable, while others are “one Oracle patch away from disaster”. We have older technologies performing critical jobs, but these have not moved forward technologically.
  3. Research to Operations conundrum
    1. See slides for Research Lifecycle at University of Central FL lifecycle, ITIL Service Lifecycle, and Engineering life cycles
    2. See slide for Sky’s R2E20 Model
  4. Principles-based Architecture
    1. Set priorities based on the mission now with mission-next in mind
    2. Traceability, transparency, and buildability (ability to have everything that we put out to be able to be built upon)
    3. Loose coupling, shared services, and data linkability – idea that everything should be coupled with some other parts
    4. Have a very good reason to rebuild something already built
    5. New investments pay down technical debt
    6. Work within constraints of operational core competence
    7. Always be prepared to fail and throw stuff away; if not now, pretty soon
  5. Testing principles in action
    1. GeoArchive
      1. Trying to move from a big collection of documents to actual data that we can work with
      2. Toward a solution of reference management and collaborative annotation
      3. Ended up going towards use of a reference management framework in Zotero to manage these resources
  6. LIMS and NMIC Commodity Stats
    1. Toward a solution for automated data transformation and distribution through schema documentation
    2. Both projects have pointed towards a need for more nimble, linkable, and versioned documentation of methods and protocols

Data Standards information - Amanda Liford, USGS

  1. The Data Management website team recently revamped the Data Standards pageData Standards (
  2. Data standards are important for being able to integrate data into other datasets or systems.
  3. The site has sections on who produces and ratifies data standards, who is responsible for following data standards, why we need data standards, and includes examples of dataset-level standards, parameter-level standards, and data encoding and interface standards.
  4. The DM website also recently put together an A-Z Index to make topic browsing easier: A-Z Index (
  5. Reach out to with suggestions for the Data Standards page or questions.