The Community for Data Integration (CDI) meetings are held the 2nd Wednesday of each month from 11:00 a.m. to 12:30 p.m. Eastern Time.
Meeting recordings are available to CDI Members approximately 24 hours after the completion of the meeting. Please log in to view the recording. If you would like to become a member of CDI, email email@example.com.
During the call, you can ask and up-vote questions at slido.com, event code Y188.
11:00a Introduction and Welcome CDI_20190410_OpeningSlides.pdf
11:10a Collaboration Area Announcements [PDF]
11:20a FY18 CDI Funded Project: An Interactive Web-based Tool for Anticipating Long-term Drought Risk - Caitlin Andrews, USGS
11:35a FY18 CDI Funded Project: Knowledge Extraction Algorithms (KEA): Turning Literature Into Data - Matthew Neilson, USGS
11:50a FY18 CDI Funded Project: Mapping land-use, hazard vulnerability and habitat suitability using deep neural networks - Jon Warrick, USGS
Developing an interactive, web-based tool for anticipating long-term drought risk
We developed an interactive web application that allows land managers to simulate and explore historical and future soil moisture and climate for their specific sites. Here we will talk about the process of developing and deploying the application, as well as how to utilize the app and its outcomes.
Caitlin Andrews is a landscape ecologist who works for the Terrestrial Dryland Ecology branch of the Southwest Biological Science Center. Her work focuses on using models and tools to study the effect of climate and drought on western ecosystems.
Knowledge Extraction Algorithms: Turning Literature Into Data
Identifying, extracting, and mobilizing information from current and historical literature is a time-consuming part of organizing and collating synthetic data productions. This project explores the use of algorithm-based methods to identify and extract occurrence information from the GeoDeepDive (GDD) literature database to support upkeep of the Nonindigenous Aquatic Species (NAS) data.
Matthew Neilson, Fishery Biologist and co-lead for the Nonindigenous Aquatic Species Database program, a national repository for biogeographic information on non-native aquatic taxa (both alien and native transplants) nationwide.
Mapping land-use, hazard vulnerability and habitat suitability using deep neural networks
During 2018, we developed multi-day workshops to provide training in the background and implementation of machine learning and deep neural networks. Here we will provide a summary of the workshops, including the tools provided, lessons learned, and success stories.
Jonathan Warrick, Research Geologist, USGS Coastal/Marine Hazards and Resources Program and PI of the USGS Remote Sensing Coastal Change Project. A former USGS Mendenhall from 2002 to 2004, Jon studies coastal watersheds and coastal change using a broad set of tools and analyses.
Presentation: Slides are available to CDI Members. Please log in to download the slides. If you would like to become a member of CDI, email firstname.lastname@example.org.
A Participant Report is available to CDI Members. Please log in to download the report. If you would like to become a member of CDI, email email@example.com.