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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

2:00pm EST

COPDESS: Facilitating a Fair Publishing Workflow Ecosystem
COPDESS, the Coalition for Publishing Data in the Earth and Space Sciences (https://copdess.org/), was established in October 2014 as a platform for Earth and Space Science publishers and data repositories to jointly define, implement, and promote common policies and procedures for the publication and citation of data and other research results (e.g., samples, software, etc.) across Earth Science journals. In late 2018, COPDESS became a cluster of ESIP to give the initiative the needed sustainability to support a long-term FAIR publishing workflow ecosystem and be a springboard to pursue future enhancements of it.

In 2017, with funding from the Arnold Foundation, the ‘Enabling FAIR Data Project’ (https://copdess.org/enabling-fair-data-project/) moved mountains towards implementing the policies and standards that connect researchers, publishers, and data repositories in their desire to accelerate scientific discovery through open and FAIR data. Implementation of the new FAIR policies has advanced rapidly across Earth, Space, and Environmental journals, but supporting infrastructure, guidelines, and training for researchers, publishers, and data repositories has yet to catch up. The primary challenges are:
  • Repositories struggle to keep up with the demands of researchers, who want to be able to instantly deposit data and obtain a DOI, without considering the data quality/data ingest requirements and review procedures of individual repositories - producing a situation where data publication is inconsistent in quality and content.
  • Many publishers who have signed the Commitment Statement for FAIR Data (https://copdess.org/enabling-fair-data-project/commitment-statement-in-the-earth-space-and-environmental-sciences/) agree with it at a high, conceptual level. However, many journal editors and reviewers lack clarity on how to validate that datasets, which underpin scholarly publications, conform with the Commitment Statement.
  • Researchers experience confusion, and in some cases barriers to publication of their papers whilst they try and meet the requirements of the commitment statement. Clarity of requirements, timelines, and criteria for selecting repositories are needed to minimize the barriers to the joint publication of papers and associated data.

Funders have a role to play, in that they need to allow for time and resources required to curate data and ensure compliance, particularly WRT to the assignment of valid DOIs. Funders can also begin to reward those researchers who do take the effort to properly manage and make their data available, in a similar way to how they reward scholarly publications and citation of those publications.

The goal of this session is to start a conversation on developing an integrated publishing workflow ecosystem the seamlessly integrates researchers, repositories, publishers and funders. Perspectives from all viewpoints will be presented.

Notes document: https://docs.google.com/document/d/12M0F6mcUZSn2GdBN-Id__smXhYxbLzKDrAViPAgnH6w/edit?usp=sharing

Presentations:

View Recording: https://youtu.be/x6a1QRNbifQ

Takeaways
  • COPDESS has moved to ESIP as a cluster to ensure the sustainability of the project to address the publishing & citation of research data



Speakers
avatar for Karl Benedict

Karl Benedict

Director of Research Data Services & Information Technology, University of New Mexico
Since 1986 I have had parallel careers in Information Technology, Data Management and Analysis, and Archaeology. Since 1993 when I arrived at UNM I have worked as a Graduate Student in Anthropology, Research Scientist, Research Faculty, Applied Research Center Director, and currently... Read More →
avatar for Kerstin Lehnert

Kerstin Lehnert

President, IGSN e.V.
Kerstin Lehnert is Senior Research Scientist at the Lamont-Doherty Earth Observatory of Columbia University and Director of EarthChem, the System for Earth Sample Registration, and the Astromaterials Data System. Kerstin holds a Ph.D in Petrology from the University of Freiburg in... Read More →
avatar for Lesley Wyborn

Lesley Wyborn

Adjunct Fellow, Australian National University


Tuesday January 7, 2020 2:00pm - 3:30pm EST
Salon A-C
  Salon A-C, Breakout

4:00pm EST

Bringing Science Data Uncertainty Down to Earth - Sub-orbital, In Situ, and Beyond
In the Fall of 2019, the Information Quality Cluster (IQC) published a white paper entitled “Understanding the Various Perspectives of Earth Science Observational Data Uncertainty”. The intention of this paper is to provide a diversely sampled exposition of both prolific and unique policies and practices, applicable in an international context of diverse policies and working groups, made toward quantifying, characterizing, communicating and making use of uncertainty information throughout the diverse, cross-disciplinary Earth science data landscape; to these ends, the IQC addressed uncertainty information from the following four perspectives: Mathematical, Programmatic, User, and Observational. These perspectives affect policies and practices in a diverse international context, which in turn influence how uncertainty is quantified, characterized, communicated and utilized. The IQC is now in a scoping exercise to produce a follow-on paper that is intended to provide a set of recommendations and best practices regarding uncertainty information. It is our hope that we can consider and examine additional areas of opportunity with regard to the cross-domain and cross-disciplinary aspects of Earth science data. For instance, the existing white paper covers uncertainty information from the perspective of satellite-based remote sensing well, but does not adequately address the in situ or airborne (i.e., sub-orbital) perspective. This session intends to explore such opportunities to expand the scope of the IQC’s awareness of what is being done with regard to uncertainty information, while also providing participants and observers with an opportunity to weigh in on how best to move forward with the follow-on paper. How to Prepare for this Session:Agenda:
  1. "IQC Uncertainty White Paper Status Summary and Next Steps" - Presented by: David Moroni (15 minutes)
  2. "Uncertainty quantification for in situ ocean data: The S-MODE sub-orbital campaign" - Presented by: Fred Bingham (15 minutes)
  3. "Uncertainty Quantification for Spatio-Temporal Mapping of Argo Float Data" - Presented by Mikael Kuusela (20 minutes)
  4. Panel Discussion (35 minutes)
  5. Closing Comments (5 minutes)
Notes Page: https://docs.google.com/document/d/1vfYBK_DLTAt535kMZusTPVCBAjDqptvT0AA5D6oWrEc/edit?usp=sharing

Presentations:
https://doi.org/10.6084/m9.figshare.11553681.v1

View Recording: https://youtu.be/vC2O8FRgvck

Takeaways

Speakers
avatar for David Moroni

David Moroni

Data Stewardship and User Services Team Lead, Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center
I am a Senior Science Data Systems Engineer at the Jet Propulsion Laboratory and Data Stewardship and User Services Team Lead for the PO.DAAC Project, which provides users with data stewardship services including discovery, access, sub-setting, visualization, extraction, documentation... Read More →
avatar for Ge Peng

Ge Peng

Research Scholar, CISESS/NCEI
Dataset-centric scientific data stewardship, data quality management
FB

Fred Bingham

University of North Carolina at Wilmington
MK

Mikael Kuusela

Carnegie Mellon University


Tuesday January 7, 2020 4:00pm - 5:30pm EST
Forest Glen
 
Wednesday, January 8
 

2:00pm EST

Citizen Science Data and Information Quality
The ESIP Information Quality Cluster (IQC) has formally defined information quality as a combination of the following four aspects of quality, spanning the full life cycle of data products: scientific quality, product quality, stewardship quality, and service quality. Focus of the IQC has been quality of Earth science data captured by scientists/experts. For example, the whitepaper “Understanding the Various Perspectives of Earth Science Observational Data Uncertainty”, published by IQC in the fall of 2019, mainly addresses uncertainty information from the perspective of satellite-based remote sensing. With the advance of mobile computing technologies, including smart phones, Citizen Science (CS) data have been increasingly becoming more and more important sources for Earth science research. CS data have their own unique challenges regarding data quality, compared with data captured through traditional scientific approaches. The purpose of this session is to broaden the scope of IQC efforts, present the community with the state-of-the-art of research on CS data quality, and foster a collaborative interchange of technical information intended to help advance the assessment, improvement, capturing, conveying, and use of quality information associated with CS data. This session will summarize the scope of what we mean by CS data (including examples of platforms/sensors commonly used in collecting CS data) and include presentations from both past and current CS projects focusing on the topics such as challenges with CS data quality; strategies to assess, ensure, and improve CS data quality; approaches to capturing CS data quality information and conveying it to users; and use of CS data quality information for scientific discovery. 

Agenda (Click titles to view presentations)
  1. Introduction - Yaxing Wei - 5 mins
  2. Citizen Science Data Quality: The GLOBE Program – Helen M. Amos (NASA GSFC) – 18 (15+3) mins.
  3. Can we trust the power of the crowd? A look at citizen science data quality from NOAA case studies - Laura Oremland (NOAA) – 18 (15+3) mins.
  4. Turning Citizen Science into Community Science - Stephen C. Diggs (Scripps Institution of Oceanography / UCSD) and Andrea Thomer (University of Michigan)  – 18 (15+3) mins.
  5. Earth Challenge 2020: Understanding and Designing for Data Quality at Scale - Anne Bowser (Wilson Center) – 18 (15+3) mins.
  6. Discussion and Key Takeaways – All – 13 mins.

    View Recording: https://youtu.be/xaTLP4wqwe8

    Takeaways

Notes Page:
https://docs.google.com/document/d/1lRp19SF9U727ureKjY38PHOF3EGUgE-BixYDs2KlmII/edit?usp=sharing

Presentation Abstracts

  • Citizen Science Data Quality: The GLOBE Program - Helen M. Amos (NASA GSFC)
The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international program that provides a way for students and the public to contribute Earth system observations. Currently 122 countries, more than 40,000 schools, and 200,000 citizen scientists are participating in GLOBE. Since 1995, participants have contributed 195 million observations. Modes of data collection and data entry have evolved with technology over the lifetime of the program, including the launch of the GLOBE Observer mobile app in 2016 to broaden access and public participation in data collection. GLOBE must meet the data needs of a diverse range of stakeholders, from elementary school classrooms to scientists across the globe, including NASA scientists. Operational quality assurance measures include participant training, adherence to standardized data collection protocols, range and logic checks, and an approval process for photos submitted with an observation. In this presentation, we will discuss the current state of operational data QA/QC, as well as additional QA/QC processes recently explored and future directions. 
  • Can we trust the power of the crowd? A look at citizen science data quality from NOAA case studies - Laura Oremland (NOAA)
NOAA has a rich history in citizen science dating back hundreds of years.  Today NOAA’s citizen science covers a wide range of topics such as weather, oceans, and fisheries with volunteers contributing over 500,000 hours annually to these projects. The data are used to enhance NOAA’s science and monitoring programs.   But how do we know we can trust these volunteer-based efforts to provide data that reflect the high standards of NOAA’s scientific enterprise? This talk will provide an overview of NOAA’s citizen science, describe the data quality assurance and quality control processes applied to different programs, and summarize common themes and recommendations for collecting high quality citizen science data. 
  • Earth Challenge 2020: Understanding and Designing for Data Quality at Scale - Anne Bowser (Wilson Center)
April 22nd, 2020 marks the 50th anniversary of Earth day.  In recognition of this milestone Earth Day Network, the Woodrow Wilson International Center for Scholars, and the U.S. Department of State are launching Earth Challenge 2020 as the world’s largest coordinated citizen science campaign.  For 2020, the project focuses on six priority areas: air quality, water quality, insect populations, plastics pollution, food security, and climate change.  For each of these six areas, one work stream will focus on collaborating with existing citizen science projects to increase the amount of open and findable, accessible, interoperable, and reusable (FAIR) data.  A second work stream will focus on designing tools to support both existing and new citizen science activities, including a mobile application for data collection; an open, API-enabled data integration platform; data visualization tools; and, a metadata repository and data journal.
A primary value of Earth Challenge 2020 is recognizing, and elevating, ongoing citizen science activities.  Our approach seeks first to document a range of data quality practices that citizen science projects are already using to help the global research and public policy community understand these practices and assess fitness-for-use.  This information will be captured primarily through the metadata repository and data journal.  In addition, we are leveraging a range of data quality solutions for the Earth Challenge 2020 mobile app, including designing automated data quality checks and leveraging a crowdsourcing platform for expert-based data validation that will help train machine learning (ML) support.  Many of the processes designed for Earth Challenge 2020 app data can also be applied to other citizen science data sets, so maintaining information on processing level, readiness level, and provenance is a critical concern.  The goal of this presentation is to offer an overview of key Earth Challenge 2020 data documentation and data quality practices before inviting the ESIP community to offer concrete feedback and support for future work.

Speakers
avatar for David Moroni

David Moroni

Data Stewardship and User Services Team Lead, Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center
I am a Senior Science Data Systems Engineer at the Jet Propulsion Laboratory and Data Stewardship and User Services Team Lead for the PO.DAAC Project, which provides users with data stewardship services including discovery, access, sub-setting, visualization, extraction, documentation... Read More →
avatar for Ge Peng

Ge Peng

Research Scholar, CISESS/NCEI
Dataset-centric scientific data stewardship, data quality management
avatar for Yaxing Wei

Yaxing Wei

Scientist, Oak Ridge National Laboratory


Wednesday January 8, 2020 2:00pm - 3:30pm EST
Linden Oak
  Linden Oak, Breakout
 
Thursday, January 9
 

10:15am EST

Working Group for the Data Stewardship Committee
This session is a working group for the 2020-2021 year for the Data Stewardship committee. We will discuss priorities for the next year, potential collaborative outputs, and review the work in progress from the last year. 

Notes Document: https://docs.google.com/document/d/1B_0K5jGnFgH72U3P2-oGr5vEqHOGU8CWU-IkZ6pjXbM/edit?ts=5e174588

Presentations

View Recording: https://youtu.be/am-ZLfHgM4w

Takeaways
  • Wow, the members of the Committee really are active! Practically everyone has their own cluster or two!
  • Six activities proposed for the upcoming year have champions who will lead the effort to define the outputs of their selected activity.


Speakers
avatar for Alexis Garretson

Alexis Garretson

Community Fellow, ESIP
avatar for Kelsey Breseman

Kelsey Breseman

Archiving Program Lead, Environmental Data & Governance Initiative
Governmental accountability around public data & the environment. Decentralized web. Intersection of tech & ethics & civics.


Thursday January 9, 2020 10:15am - 11:45am EST
Forest Glen
  Forest Glen, Business Meeting

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

10:15am EST

Connecting Data with Data Usage: a Graph Approach
We will investigate graph-based methods of connecting data with the uses made and the knowledge gained from those data, from science research to applications to strategic planning. We will examine the diverse capabilities enabled by connecting uses with data for a variety of stakeholders, and explore how to connect existing knowledge graphs together to scale out across the ESIP federation and related communities toward an inter-connected mega-graph.

0-5 min: Chris Lynnes (NASA): Documenting how data matters...
5-15 min: Doug Newman (NASA): EOSDIS Knowledge Graph
https://doi.org/10.6084/m9.figshare.11561805.v1
15-25 min: Reid Sherman (GCIS): Global Change Information System
https://doi.org/10.6084/m9.figshare.11560011.v1
25-35 min: Dave Blodgett (USGS): SELFIE
https://doi.org/10.6084/m9.figshare.11559093.v1
35-45 min: Joe Conran (NOAA): Interagency Coordination of Satellite Needs
https://doi.org/10.6084/m9.figshare.11561946.v1
45-55 min: Wil Doane (IDA): Assessing the Impact of Land Imaging
https://doi.org/10.6084/m9.figshare.11561913.v1
55-90 min: The Way Forward:
1 - Got Use Case?
2 - ESIP Cluster? https://www.esipfed.org/get-involved/collaborate
3 - Who's In?

Session Notes

View Recording:
https://youtu.be/yi05crW6Ya0\

Takeaways
  • How to connect data with the uses of that data = Documenting how data matter.
    Federating knowledge bases is daunting task but possible.
  • Connect research and data to place (but gap around using place identifiers in linked data).
    Discussion of potentially make a new cluster or using another one. Decision to recharter/repurpose/rename the data discovery cluster.
  • Sin of computer science is giving people impression that things are mostly 1 to 1 relationship, but more accurately life and universe is full of many-to-many relationships, i.e., graph databases > RDBMS




Speakers
avatar for Christopher Lynnes

Christopher Lynnes

Systems Architect, NASA/EOSDIS, NASA/GSFC
Christopher Lynnes is currently System Architect for NASA’s Earth Observing System Data and Information System, known as EOSDIS. He has been working on EOSDIS since 1992, over which time he has worked multiple generations of data archive systems, search engines and interfaces, science... Read More →
avatar for Doug Newman

Doug Newman

EED Data Use Architect


Thursday January 9, 2020 10:15am - 11:45am EST
White Flint
  White Flint, Panel

12:00pm EST

Datacubes for Analysis-Ready Data: Standards & State of the Art
This workshop session will follow up on the OGC Coverage Analytics sprint, focusing specifically on advanced services for spatio-temporal datacubes. In the Earth sciences datacubes are accepted as an enabling paradigm for offering massive spatio-temporal Earth data analysis-ready, more generally: easing access, extraction, analysis, and fusion. Also, datacubes homogenizes APIs across dimensions, allowing unified wrangling of 1-D sensor data, 2-D imagery, 3-D x/y/t image timeseries and x/y/z geophysics voxel data, and 4-D x/y/z/t climate and weather data.
Based on the OGC datacube reference implementation we introduce datacube concepts, state of standardization, and real-life 2D, 3D, and 4D examples utilizing services from three continents. Ample time will be available for discussion, and Internet-connected participants will be able to replay and modify many of the examples shown. Further, key datacube activities worldwide, within and beyond Earth sciences, will be related to.
Session outcomes could take a number of forms: ideas and issues for OGC, ISO, or ESIP to consider; example use cases; challenges not yet addressed sufficiently, and entirely novel use cases; work and collaboration plans for future ESIP work. Outcomes of the session will be reported at the next OGC TC meeting's Big Data and Coverage sessions. How to Prepare for this Session: Introductory and advanced material is available from http://myogc.org/go/coveragesDWG

Presentations
https://doi.org/10.6084/m9.figshare.11562552.v1

View Recording: https://youtu.be/82WG7soc5bk

Takeaways
  • Abstract coverage construct defines the base which can be filled up with a coverage implementation schema. Important as previously implementation wasn’t interoperable with different servers and clients. 
  • Have embedded the coordinate system retrieved from sensors reporting in real time into their xml schema to be able to integrate the sensor data into the broader system. Can deliver the data in addition to GML but JSON, and RDF which could be used to link into semantic web tech. 
  • Principle is send HTTP url-encoded query to server and get some results that are extracted from datacube, e.g., sources from many hyperspectral images.

Speakers

Thursday January 9, 2020 12:00pm - 1:30pm EST
White Flint