Thursday, October 22, 2-3:30pm Eastern

1-minute lightning presentations of all of the submitted Statements of Interest to help you get started with community commenting and voting. 

Keep track of your notes: CDI-FY21-StatementsofInterestList.xlsx

Slides: CDI_FY21_RFP_Lightning_Presentation-sm.pdf

Streaming recording: (recommended if you have access to Dept of Int Microsoft) MS Stream link

Recording Part 1 Last Name A-H: 201022-cdi-rfp-lightning-part1.mp4

Recording Part 2 Last Name K-Z: 201022-cdi-rfp-lightning-part2.mp4

 

Order of presentations

Order of 1-minute presentations (alphabetical by last name)


Josh AckermanIntegrating avian and spatial environmental data to assist scenario planning in South San Francisco Bay restoration
Itiya AneeceProcessing a new generation of hyperspectral data on the Cloud using Pangeo
Cara ApplesteinTools for incorporating expert knowledge into predictions of sagebrush steppe post-fire treatment success
Theodore BarnhartFire and Water - Integrating Precipitation and Fire Data into StreamStats 
Adam BenthemA framework for the integration of energy life cycle data to support environmental health assessments, identify science gaps, and EarthMAP
John B. BradfordOperationalizing ecological drought forecasts for drylands of the Western US using high performance computing 
Sandra BrosnahanAn Imagery “ID” System ... Building an “Imagery Dashboard” for rapid and efficient publication of USGS data.
Matthew CashmanFrom reactive- to condition-based maintenance: Anomaly predictions and automated review for USGS time-series data
Katherine ChaseICE! Ice Jam Hazard Mobile-enabled Website
Katharine DahmIntegrated Science Outreach Application for Local Stakeholders
Kara DoranMaking USGS/NOAA Total Water Level and Coastal Change Forecast data accessible through user-friendly interfaces
John Fulton#MinutesMatter: Real-time data collection and transmission in wildfire burn scars
Daniel Grear
(Katie LeVan)
Synthesizing mosquito dynamics and coastal storm hazards for public health resilience
Thomas GushueModernizing sensor data workflows to leverage Internet of Things (IoT) and cloud-based technologies
Travis HarrisonR Package for Corps Water Management System Data
Todd HawbakerLandsat-derived fire history metrics to provide critical information for prioritizing prescribed fire across the Southeast
Liv HerdmanIntegrating data to Explore Interactions, Controls, and Heterogeneity in Harmful Algal Blooms (HABS)
Margaret HunterStandardizing, aggregating and disseminating USGS wildlife genetic data for improved management and advancement of community best practices

few-minute BREAK
Sue KempGIS Clipping and Summarization Tool for Points, Lines, Polygons, and Rasters
Ellis MargolisburnrData: The North American tree-ring fire history database in R
Beth A MiddletonData synthesis to support water sharing and understanding of carbon resilience in tidal mixed baldcypress/hardwood swamps
Kurtis NelsonBuilding opportunities for data collaboration and integration across USGS’s wildland fire science
Birgit PetersonImproving forest structure mapping and regeneration prediction with multi-scale lidar observations
David S. PlliodMonitoring Design Module for the Land Treatment Exploration Tool
Janet Prevey
(Catherine Jarnevich)
Site Prioritization Tool for Invasive Species: Integrating Diverse Spatial Data to Improve Decision Making 
Annie PutmanAssimilating complex biogeochemical dust measurements supports community standardization, collaboration, and environmental health research
Sasha ReedJoining diverse data to improve fire forecasts for the western U.S.: Incorporating hot drought" and intra-annual precipitation variability "
Francis RengersAdvancing Post-Fire Debris Flow Hazard Science with a Field Deployable Mapping Tool
Tara RootAnalysis and Prediction Tool for Coastal Resilience
Douglas ShinnemanThe Wildfire Trends Tool: a data visualization and analysis tool to facilitate land management needs and scientific inquiry 
Camille L. StaggA modeling framework to forecast land cover change impacts on coastal wetland carbon in Louisiana
Jens StevensPredicting successful post-fire reforestation: scaling from data to application

Sean Vitousek
(Jon Warrick)

Integrating Satellite-Derived Shoreline Data and Predictive Models
to Enhance Coastal Change Forecasts 
Alisa WadeIntegrating interdisciplinary data to assess past and future impacts of increasing fire on infrastructure critical to resource management
John C. WarnerCoupled Ocean-Atmosphere-Wave-SedimentTransport (COAWST) Modeling System 2021 Training Workshop
Phillipe WernetteCoast Train: Massive Library of Labeled Coastal Images to Train Machine Learning for Coastal Hazards and Resources



Information for Presenters

Instructions for presenters: Send a simple image (.png or .jpg work great) with minimal text that is close to 1:1 aspect ratio (square) to gs_cdi@usgs.gov by COB on Wednesday, Oct 21 - we will insert this image onto a slide that has your Title and Lead PI name on it. 

Our reason for these requirements is that we want you to focus on your words and timing, not the slide!

A pre-recorded 1 minute .mp3 or .m4a (audio only) file is an option. You can record a file on your phone or computer and send it to us (BY COB ON WED OCT 21) to have it played during the session. Another team member may present if the Lead PI is unavailable (let us know if you haven't already).


Example of how much can be spoken in 1 minute, if speaking relatively quickly:

What exactly is the Community for Data Integration? Maybe you know from our monthly meetings that we bring you information and tools to help you work with your data. But how, and why? CDI’s goal is to increase the USGS knowledge base for data integration and the associated science results. Did you know that the proposals process is only one way that we achieve this purpose? We also have monthly virtual meetings, collaboration areas, training and learning activities, and an in-person workshop every two years. Our topics must be determined by our members in order to stay relevant and true to our grassroots values. CDI is run out of the Science Analytics and Synthesis Program in Core Science Systems, but is open to anyone who wants to participate in our community of practice. The USGS leadership that sponsors CDI are Kevin Gallagher, Associate Director of Core Science Systems, and Tim Quinn, Chief of the Office of Enterprise Information. As facilitators, I, Leslie Hsu, along with Amanda Liford and Grace Donovan, are here to listen to your opinions on how to make CDI work for you.

What order will we present in?
For simplicity, we will proceed in alphabetical order by last name (see table below) 

How will the one minute rule be enforced?
For each speaker:
(1) I'll ask if you are on the line to confirm that we can hear you.
(2) I will read the title and your name to introduce you and save you a few seconds.
(3) We'll start the timer 
(4) We will advance slides after a minute has passed!

(If you have a recording, we will play that.)

Can I use a pointer?
No, we will be advancing the slides for you and will have control, hopefully you can draw attention with your words.

Do I need to be present?
No, not necessarily. A pre-recorded 1 minute .mp3 or .m4a (audio only) file is an option. You can record a file on your phone or computer and send it to us (BY COB ON WED OCT 21) to have it played during the session. Another team member may present if the Lead PI is unavailable.

Will I get a chance to answer questions?
After everyone has given their 1 minute presentation, we will facilitate any questions that come in from listeners. You can either use your audio, or type something into the Teams chat to answer. If you aren't there, we'll post those questions on your statement of interest page on the wiki.

What happens after the lightning presentation session?

1) On Tuesday, October 20, all CDI members will receive a link to the FY21 Statements of Interest wiki page, where there will be a large blue button for “View and Comment on the Statements of Interest.”

2) The button will take you to a Forum page where you are able to sort, view, and comment on different statements. We encourage you to comment on other people’s statements just like the rest of the community.

3) We will add you as a “watcher” to your respective page so that you should get an email notification if someone leaves a comment.
It usually takes a few days to get the comments rolling. Responses to comments are encouraged, it will help to communicate the value of your proposal.

A note on CDI Community Voting

We wanted to send you some more context to our community voting process, it was written a of couple years ago but is still relevant. As our community grows, it becomes a little harder to get that grassroots feel, but we will continue to facilitate it as we can!

Excerpted from: https://my.usgs.gov/confluence/pages/viewpage.action?pageId=557488221

Dear CDI Lead-PIs and registrants,

Since some of you may be new to CDI’s Community Voting process, I thought I would send a bit of an explanation since we often get questions about what is allowed/condoned, etc.

CDI has had community voting since FY2014 in an effort to engage the entire membership so that we make sure to take into account our grassroots efforts, needs, and knowledge before moving forward with funding projects. In FY2013, the proposals were evaluated only by a panel. Prior to FY2013, proposals were developed at in-person CDI meetings and participants would use sticky notes and discussions to lend their feedback. Now CDI has a Bureau-wide RFP and many members who do not attend the annual in-person meetings, so the online community voting phase is a way to preserve that aspect of proposal development and evaluation.

We sometimes get comments that the community voting system can be “gamed” by especially active PIs who solicit votes. To this, we have several responses:

  1. Community voting is just the first phase of the evaluations, there is a panel evaluation as well in Phase 2, that evaluates the Full proposals.

  2. We look at other metrics in Phase 1 like ratio of number of voters:number of votes, IP address participation that is overly skewed, etc. to see if there are any anomalies. (note: we have a new system this year, but we will look at other metrics like anomalous voting for single projects only instead of taking advantage of the full ranking capability)

  3. The community voting indicates the community voice, but there is also the chance for CDI executive sponsors and CDI coordinators to point out SOIs that meet the criteria and add them to Phase 2, this has happened in past years.

  4. We do encourage PIs to spread the word about their proposal to colleagues that would be interested in the project and support the effort, and lend their voice to CDI.

  5. We do not support the solicitation of votes from “anyone off the street” who does not have any personal interest in the actual project or viewing the other submissions. Although, in our experience, this has not helped a project without merit to get funded, due to the other items listed above.

Since this topic comes up every year year, we decided that sending this explanation to all participating PIs was a place to start, and we will continue to do this in following years before the start of voting!