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Tuesday, January 7
 

11:00am EST

Analytic Centers for Air Quality
The Analytic Center Framework (ACF) is a concept to support scientific investigations with a harmonized collection of data from a wide range of sources and vantage points, tools and computational resources. Four recent NASA AIST competitive awards are focused on either ACFs or components which could feed into AQ ACF's. Previous projects have developed tools and improved the accessibility and usability of data for Air Quality analysis, and have tried to address issues related to inconsistent metadata, uncertainty quantification, interoperability among tools and computing resources and visualization to aid scientific investigation or applications. The format for this meeting will be a series of brief presentati.ons by invited speakers followed by a discussion. This generally follows the panel model How to Prepare for this Session: A link to a set of pre-read materials will be provided.

View Recording: https://youtu.be/fy4eoOfSbpo.

Takeaways
  • Is there enough interest to start an Air Quality cluster? Yes!
  • Technologists and scientists should both be involved in the cluster to ensure usability through stakeholder engagement


Speakers
ML

Mike Little

ESTO, NASA
Computational Technology to support scientific investigations


Tuesday January 7, 2020 11:00am - 12:30pm EST
Glen Echo
  Glen Echo, Working Session

2:00pm EST

ESIP Geoscience Community Ontology Engineering Workshop (GCOEW)
"Brains! Brains! Give us your brains!""
- Friendly neighbourhood machine minds
The collective knowledge in the ESIP community is immense and invaluable. During this session, we'd like to make sure that this knowledge drives the semantic technology (ontologies) being developed to move data with machine-readable knowledge in Earth and planetary science.
What we'll do:

In the first half hour of this session, we'll a) sketch out how and why we build ontologies and b) show you how to request that your knowledge gets added to ontologies (with nanocrediting).
We'll then have a 30-minute crowdsourcing jam session, during which participants can share their geoscience knowledge on the SWEET issue tracker. With a simple post, you can shape how the semantic layer will behave, making sure it does your field justice! Request content and share knowledge here: https://github.com/ESIPFed/sweet/issues
In the last, 30 minutes we'll take one request and demonstrate how we go about ""ontologising"" it in ENVO and how we link that to SWEET to create interoperable ontologies across the Earth and life sciences.

Come join us and help us shape the future of Geo-semantics!

Stuff you'll need:
A GitHub account available at https://github.com/
An ORCID (for nanocrediting your contributions) available at https://orcid.org How to Prepare for this Session:

Presentations:

View Recording:
https://youtu.be/tr0coi5ZQvM

Takeaways
  • Working toward a future (5-10 year goal) of making an open Earth & Space Science Foundry (from SWEET) similar to the OBO (Open Biological and Biomedical Ontology) Foundry. “Humans write queries”. Class definitions need to be machine-readable for interoperability, but must remain human-readable for authoring queries, ontology reuse, etc.
  • Please feel free to add phenomena of interest to the SWEET https://github.com/ESIPFed/sweet/issues/ or ENVO https://github.com/EnvironmentOntology/envo/issues/ issue trackers. 
  • At AGU they added a convention for changes to ontologies. Class level annotation convention. Can get now get textual defs from DBpedia for SWEET terms. See https://github.com/ESIPFed/sweet/wiki/SWEET-Class-Annotation-Convention


Speakers
avatar for Lewis J. McGibbney

Lewis J. McGibbney

Chair, ESIP Semantic Technologies Committee, NASA, JPL
My name is Lewis John McGibbney, I am currently a Data Scientist at the NASA Jet Propulsion Laboratory in Pasadena, California where I work in Computer Science and Data Intensive Applications. I enjoy floating up and down the tide of technologies @ The Apache Software Foundation having... Read More →


Tuesday January 7, 2020 2:00pm - 3:30pm EST
Glen Echo
  Glen Echo, Working Session
 
Wednesday, January 8
 

2:00pm EST

Participatory design and evaluation of a 3D-Printed Automatic Weather Station to explore hardware, software and data needs for community-driven decision making
The development of low-cost, 3D-printed weather stations aims to revolutionize the way communities collect long-term data about local weather phenomenon, as well as develop climate resilience strategies to adapt to the impacts of increasingly uncertain climate trends. This session will engage teachers and scientists in the evaluation and participatory design of the IoTwx 3D-printed weather station that is designed to be constructed and extended by students in middle and high school. We aim to explore the full spectrum of the station from construction (from pre-printed parts), to data collection and development of learning activities, to analysis of scientific phenomenon within the data. The stations also represent a unique opportunity to develop community-based strategies to extend the capabilities of the platform, and in the session we are encouraging full discussion of data collection and sensing technologies of specific relevance to communities adopting the stations.

In this working session, we will work directly with teachers on evaluation and development using a participatory design approach to stimulate and encourage relationships between ESIP Education Committee members and teachers.

Preparing for this Session: TBD

Presentations:

View Recording: https://youtu.be/AfvWhZBkQd8

Takeaways
  • Very valuable for the schools and community. It is an opportunity to include multiple departments within the school system (engineering, computer science, maths, earth science, etc.)
  • Need to understand the constraints that school systems may present: security, wifi, processing power, cloud access, only required for part of the year



Speakers
avatar for Shelley Olds

Shelley Olds

Science Education Specialist, UNAVCO
Data visualization tools, Earth science education, human dimensions of natural hazards, disaster risk reduction (DRR), resilience building.
avatar for Becky Reid

Becky Reid

Science Educator, Learners Without Walls
I discovered ESIP in the summer of 2009 when I was teaching science in Santa Barbara and attended the Summer meeting there. Ever since then, I have been volunteering with the ESIP Education Committee in various capacities, serving as Chair in 2013, 2019, and now, 2020! I currently... Read More →


Wednesday January 8, 2020 2:00pm - 3:30pm EST
Brookside A
  Brookside A, Working Session

2:00pm EST

AI for Augmenting Geospatial Information Discovery
Thanks to the rapid developments of hardware and computer science, we have seen a lot of exciting breakthroughs in self driving, voice recognition, street view recognition, cancer detection, check deposit, etc. Sooner or later the fire of AI will burn in Earth science field. Scientists need high-level automation to discover in-time accurate geospatial information from big amount of Earth observations, but few of the existing algorithms can ideally solve the sophisticated problems within automation. However, nowadays the transition from manual to automatic is actually undergoing gradually, a bit by a bit. Many early-bird researchers have started to transplant the AI theory and algorithms from computer science to GIScience, and a number of promising results have been achieved. In this session, we will invite speakers to talk about their experiences of using AI in geospatial information (GI) discovery. We will discuss all aspects of "AI for GI" such as the algorithms, technical frameworks, used tools & libraries, and model evaluation in various individual use case scenarios. How to Prepare for this Session: https://esip.figshare.com/articles/Geoweaver_for_Better_Deep_Learning_A_Review_of_Cyberinfrastructure/9037091
https://esip.figshare.com/articles/Some_Basics_of_Deep_Learning_in_Agriculture/7631615

Presentations:
https://doi.org/10.6084/m9.figshare.11626299.v1

View Recording: https://youtu.be/W0q8WiMw9Hs

Takeaways
  • There is a significant uptake of machine learning/artificial intelligence for earth science applications in the recent decade;
  • The challenge of machine learning applications for earth science domain includes:
    • the quality and availability of training data sets;
    • Requires a team with diverse skill background to implement the application
    • Need better understanding of the underlying mechanism of ML/AI models
  • There are many promising applications/ developments on streamlining the process and application of machine learning applications for different sectors of the society (weather monitoring, emergency responses, social good)



Speakers
avatar for Yuhan (Douglas) Rao

Yuhan (Douglas) Rao

Postdoctoral Research Scholar, CISESS/NCICS/NCSU
avatar for Aimee Barciauskas

Aimee Barciauskas

Data engineer, Development Seed
avatar for Annie Burgess

Annie Burgess

ESIP Lab Director, ESIP
avatar for Rahul Ramachandran

Rahul Ramachandran

Project Manager, Sr. Research Scientist, NASA
avatar for Ziheng Sun

Ziheng Sun

Research Assistant Professor, George Mason University
My research interests are mainly on geospatial cyberinfrastructure and agricultural remote sensing.


Wednesday January 8, 2020 2:00pm - 3:30pm EST
Salon A-C
  Salon A-C, Breakout

2:00pm EST

Advancing Data Integration approaches of the structured data web
Political, economic, social or scientific decision making is often based on integrated data from multiple sources across potentially many disciplines. To be useful, data need to be easy to discover and integrate.
This session will feature presentations highlighting recent breakthroughs and lessons learned from experimentation and implementation of open knowledge graph, linked data concepts and Discrete Global Grid Systems. Practicality and adoptability will be the emphasis - focusing on incremental opportunities that enable transformational capabilities using existing technologies. Best practices from the W3C Spatial Data on the Web Working Group, OGC Environmental Linked Features Interoperability Experiment, ESIP Science on Schema.org; implementation examples from Geoscience Australia, Ocean Leadership Consortium, USGS and other organisations will featured across the entire session.
This session will highlight how existing technologies and best practices can be combined to address important and common use cases that have been difficult if not impossible until recent developments. A follow up session will be used to seed future collaborative development through co-development, github issue creation, and open documentation generation.

How to Prepare for this Session: Review: https://opengeospatial.github.io/ELFIE/, https://github.com/ESIPFed/science-on-schema.org, https://www.w3.org/TR/sdw-bp/, and http://locationindex.org/.

Notes, links, and attendee contact info here.

View Recording: https://youtu.be/-raMt2Y1CdM

Session Agenda:
1.  2.00- 2.10,  Sylvain Grellet, Abdelfettah Feliachi, BRGM, France
'Linked data' the glue within interoperable information systems
“Our Environmental Information Systems are exposing environmental features, their monitoring systems and the observation they generate in an interoperable way (technical and semantic) for years. In Europe, there is even a legal obligation to such practices via the INSPIRE directive. However, the practice inducing data providers to set up services in a "Discovery > View > Download data" pattern hides data behind the services. This hinders data discovery and reuse. Linked Data on the Web Best Practices put this stack upside down and data is now back in the first line. This completely revamp the design and capacities of our Information Systems. We'll highlight the new data frontiers opened by such practices taking examples on the French National Groundwater Information Network”
View Slides: https://doi.org/10.6084/m9.figshare.11550570.v1

2.  2.10 - 2.20,  Adam Leadbetter, Rob Thomas, Marine Institute, Ireland
Using RDF Data Cubes for data visualization: an Irish pilot study for publishing environmental data to the semantic web
The Irish Wave and Weather Buoy Networks return metocean data at 5-60 minute intervals from 9 locations in the seas around Ireland. Outside of the Earth Sciences an example use case for these data is in supporting Blue Economy development and growth (e.g. renewable energy device development). The Marine Institute, as the operator of the buoy platforms, in partnership with the EU H2020 funded Open Government Intelligence project has published daily summary data from these buoys using the RDF DataCube model[1]. These daily statistics are available as Linked Data via a SPARQL endpoint making these data semantically interoperable and machine readable. This API underpins a pilot dashboard for data exploration and visualization. The dashboard presents the user with the ability to explore the data and derive plots for the historic summary data, while interactively subsetting from the full resolution data behind the statistics. Publishing environmental data with these technologies makes accessing environmental data available to developers outside those with Earth Science involvement and effectively lowers the entry bar for usage to those familiar with Linked Data technologies.
View Slides: https://doi.org/10.6084/m9.figshare.11550570.v1

3. 2.20 - 2.30,  Boyan Brodaric, Eric Boisvert, Geological Survey of Canada, Canada; David Blodgett, USGS, USA
Toward a Linked Water Data Infrastructure for North America
We will describe progress on a pilot project using Linked Data approaches to connect a wide variety of water-related information within Canada and the US, as well as across the shared border
View Slides: https://doi.org/10.6084/m9.figshare.11541984.v1

4.  2.30 - 2.40,  Dalia Varanka, E. Lynn Usery, USGS, USA
The Map as Knowledge Base; Integrating Linked Open Topographic Data from The National Map of the U.S. Geological Survey
This presentation describes the objectives, models, and approaches for a prototype system for cross-thematic topographic data integration based on semantic technology. The system framework offers a new perspectives on conceptual, logical, and physical system integration in contrast to widely used geographic information systems (GIS).
View Slides: https://doi.org/10.6084/m9.figshare.11541615.v1

5.  2.40 – 2.50,  Alistair Ritchie, Landcare, New Zealand
ELFIE at Landcare Research, New Zealand
Landcare Research, a New Zealand Government research institute, creates, manages and publishes a large set of observational and modelling data describing New Zealand’s land, soil, terrestrial biodiversity and invasive species. We are planning to use the findings of the ELFIE initiatives to guide the preparation of a default view of the data to help discovery (by Google), use (by web developers) and integration (into the large environmental data commons managed by other agencies). This integration will not only link data about the environment together, but will also expose more advanced data services. Initial work is focused on soil observation data, and the related scientific vocabularies, but we anticipate near universal application across our data holdings.
View Slides: https://doi.org/10.6084/m9.figshare.11550369.v1

6.  2.50 - 3.00,  Irina Bastrakova, Geoscience Australia, Australia
Location Index Project (Loc-I) – integration of data on people, business & the environment
Location Index (Loc-I) is a framework that provides a consistent way to seamlessly integrate data on people, business, and the environment.
Location Index aims to extend the characteristics of the foundation spatial data of taking geospatial data (multiple geographies) which is essential to support public safety and wellbeing, or critical for a national or government decision making that contributes significantly to economic, social and environmental sustainability and linking it with observational data. Through providing the infrastructure to suppo

Speakers
avatar for Jonathan Yu

Jonathan Yu

Research data scientist/architect, CSIRO
Jonathan is a data scientist/architect with the Environmental Informatics group in CSIRO. He has expertise in information and web architectures, data integration (particularly Linked Data), data analytics and visualisation. Dr Yu is currently the technical lead for the Loc-I project... Read More →
avatar for Dalia Varanka

Dalia Varanka

Research Physical Scientist, U.S. Geological Survey
Principle Investigator and Project Lead, The Map as Knowledge Base
AR

Alastair Richie

Landcare Research NZ
AL

Adam Leadbetter

Marine Institute
RT

Rob Thomas

Marine Institute
BB

Boyan Brodaric

Natural Resources Canada
EB

Eric Boisvert

Natural Resources Canada
avatar for Irina  Bastrakova

Irina Bastrakova

Director, Spatial Data Architecture, Geoscience Australia
I have been actively involved with international and national geoinformatics communities for more than 19 years. I am the Chair of the Australian and New Zealand Metadata Working Group. My particular interest is in developing and practical application of geoscientific and geospatial... Read More →
avatar for David Blodgett

David Blodgett

U.S. Geological Survey


Wednesday January 8, 2020 2:00pm - 3:30pm EST
White Flint

4:00pm EST

Emerging EnviroSensing Topics: Long-range, Low-power, Non-contact, Open-source Sensor Networks
Led by the ESIP EnviroSensing Cluster, this session is open to scientists, information managers, and technologists interested in the general topic of environmental sensing for science and management.

Rapid advances and decreasing costs in technology, as applied to environmental sensing systems, are promoting a shift from sparsely-distributed, single-mission observations toward employing affordable, high-fidelity, ecosystem monitoring networks driven by a need to forecast outcomes across timescales. In this session we will hear talks on new approaches to standing up long-range, low-power monitoring networks; the value(s) added by non-contact sensing (local-remote to satellite based sensing); as well as innovative sensor developments, including open-source approaches, that promote connectivity. The session will conclude with a 20-minute topical discussion open to all in attendance. How to Prepare for this Session:

List of speakers and presentation titles for this session:
  • Jacqueline Le Moigne: NASA
    Future Earth Science Measurements Using New Observing Strategies
  • David Coyle: USGS
    USGS NGWOS LPWAN Experiment: Leveraging LoRaWAN Sensor Platform Technologies
  • James Gallagher: OPeNDAP
    Sensors in Snowy Alpine Environments: Sensor Networks with LoRa, Progress Report
    View Slides: https://doi.org/10.6084/m9.figshare.11555784.v1 
  • Daniel Fuka: Va Tech
    Making Drones Interesting Again
    View Slides: https://doi.org/10.6084/m9.figshare.11663718.v1
  • Joseph Bell: USGS
    Deep-dive discussion after presentations. A topic of interest is documenting test efforts and the publication of peer-reviewed Test Reports

View Recording: https://youtu.be/dXTLqt-5Ai8

Takeaways
  • As monitoring expands across agencies and from point measures on the surface of the earth to monitoring using networks of satellites in space (internet of space) there is a growing need to increase communication among agencies and instrumentation alike
  • Inexpensive monitoring equipment is becoming readily available with large gains being made in the areas of function, reliability, and resolution/accuracy.
    • Market disruption
    • Edge -Computing (is this the current form of SDI-12-style monitoring?) local processing and storage, transmission of small/tiny data payloads
  • There appears to be a need across disciplines and agencies for a peer-reviewed test reports
    • Not resource intensive to publish
    • Available to all users (FAIR)
    • Provides details on test plan and provides test data whenever applicable.


Speakers
avatar for Joseph Bell

Joseph Bell

Hydrologist, USGS


Wednesday January 8, 2020 4:00pm - 5:30pm EST
Forest Glen
  Forest Glen, Breakout
 
Thursday, January 9
 

10:15am EST

Mapping Data & Operational Readiness Levels (ORLs) to Community Lifelines
Approach: The Disaster Lifecycle Cluster has seen great success in its efforts to put Federated arms around “trusted data for decision makers” as a way to accelerate situational awareness and decision-making. By identifying trust levels for data. This session will build upon the Summer meeting and align perfectly with the overall ESIP theme of: Data to Action: Increasing the Use and Value of Earth Science Data and Information.

The ESIP Disaster Lifecycle Cluster has evolved into one of the most operationally active clusters in the Federation with a thirst for applying datasets to decision-making environments while building trust levels that manifest themselves as ORLs. Duke Energy, All Hazards Consortium’s Sensitive Information Sharing environment (SISE), DHS and FEMA are all increasing their interest in ORLs with their sights set on implementing them in the near future. Data is available everywhere and more of it is on the way. Trusted data is available some places and can help decision makers such as utilities make 30-second decisions that can save lives, property and get the lights back on sooner, saving millions of dollars.

This session will provide the venue to discuss emerging projects from NASA’s Applied Sciences Division (A.37), Initiatives at JPL and Federal Agency data portal access that can accelerate decision making today and in the future. We will also discuss drone data and European satellite data that is available for access and use when disasters threaten. Come and join us, the data you have may just save a life.

Agenda:
  1. Greg McShane, DHS CISA - The Critical Nature of the Public-Private Trusted Information Sharing Paradigm (10 min) Presented by Tom Moran, All Hazards Consortium Executive Director
  2. Dave Jones, StormCenter/GeoCollaborate - The status of ORLs, where we are, ESIP Announcement at GEO in Australia, AHC SISE, Next Steps (10 min)
  3. Maggi Glassco, NASA Disasters Program, JPL - New Applied Sciences Disasters Projects, Possible Lifeline Support Information Sources in the Future (10 min)
  4. Bob Chen/Bob Downs, Columbia Univ./SEDAC/CIESIN - Specific Global and Local Population Data for Community Lifeline Decision Making (10 min)
  5. Discussion/Q&A Period (40 min)

Presentations

View Recording: https://youtu.be/gJ93R6SlMkM

Key Takeaways for this Session: 
  1. Through the All Hazards Consortium, a new research institute will begin to help bring candidate research products into operations. An imagery committee, consisting of private and research members under SISE, will identify and evaluate use-case driven candidate imagery data within the ORL context using Geo-Collaborate.
  2. NASA grant opportunities within the disasters program requires co-funding by end user partners to guide usage needs and adoption (using ARL success criteria). This should increase adoption of NASA funded ASP project data and/or services. The cluster would like to work with NASA ASP as a testbed for funded projects to connect to additional user communities.
  3. We discussed the need / value of population data (current and predictions on affected populations) for preparedness activities and emergency response. We would like to leverage additional data services from SEDAC to test with operational decision makers. 


Speakers
avatar for Dave Jones

Dave Jones

StormCenter Communications, StormCenter Communications
Real-time data access, sharing and collaboration across multiple platforms. Collaborative Common Operating Pictures, Decision Making, Situational Awareness, connecting disparate mapping systems to share data, cross-product data sharing and collaboration. SBIR Phase III status with... Read More →
avatar for Karen Moe

Karen Moe

NASA Goddard Emeritus
ESIP Disasters Lifecycle cluster co-chair with Dave Jones/StormCenter IncManaging an air quality monitoring project for my town just outside of Washington DC and looking for free software!! Enjoying citizen science roles in environmental monitoring and sustainable practices in my... Read More →


Thursday January 9, 2020 10:15am - 11:45am EST
Salon A-C
  Salon A-C, Breakout