Loading…
This event has ended. Create your own event on Sched.
Join the 2020 ESIP Winter Meeting Highlights Webinar on Feb. 5th at 3 pm ET for a fast-paced overview of what took place at the meeting. More info here.

Sign up or log in to bookmark your favorites and sync them to your phone or calendar.

Monday, January 6
 

4:00pm EST

Council of Data Facilities General Assembly Meeting
The Council of Data Facilities (CDF) is committed to working with relevant agencies, professional associations, initiatives, and other complementary efforts to enable transformational science, innovative education, and informed public policy through increased coordination, collaboration, and innovation in the acquisition, curation, preservation, and dissemination of geoscience data, tools, models, and services. Existing and emerging geoscience data facilities – through the Council – are committed to serving as an effective foundation for EarthCube. The General Assembly meeting is open to the official representatives from all member data facilities, additional member organization personnel as desired by the members, as well as observers. How to

Agenda:
400-415 Welcome/introductions/sign-in - Danie415-430 High level Summary of OKN workshop - TBA
430-435 Updates on shared infrastructure - Kerstin, Danie
435-445 Update on COPDESS-Kerstin, Shelley
445-515 Update and next steps on P419-Doug, Adam
515-530 Progress on EC supplements for CCHDO and MagIC related to P418/P419 (GeoCODES)-Steve
530-550 Update from tech team EarthCube Office-Kenton McHenry
550-600 Summer topics - Danie
      • Suggested Charter changes (to be voted on at july 2020)
      • Announce  CDF exec elections in july 2020 - 2 co-chair and 3 at large positions


Speakers
avatar for Jessica Hausman

Jessica Hausman

Data Engineer, PO.DAAC JPL


Monday January 6, 2020 4:00pm - 6:00pm EST
Glen Echo
  Glen Echo, Business Meeting
 
Tuesday, January 7
 

11:00am EST

Creating a Data at Risk Commons at DataAtRisk.org
Several professional organizations have become increasingly concerned about the loss of reusable data from primary sources such as individual researchers, projects, and agencies. DataAtRisk.org aims to connect people with data in need, to data expertise, and is a response to the clear need for a community building application. This “Data at Risk” commons will allow individuals to submit and request help with threatened datasets and connect these datasets to experts who can provide resources and skills to help rescue data through a secure, professional mechanism to facilitate self-identification and discovery.

This session will provide an overview of the current status of the DataAtRisk.org project, and aims to expand the network of individuals involved in the development and implementation of DataAtRisk.org

How to Prepare for this Session: Please check out https://dataatrisk.org/ for some background on the activities.

Presentations: http://bit.ly/303gig7, https://doi.org/10.6084/m9.figshare.11536317.v1
Link to use case / user scenario: https://tinyurl.com/yh4rnk7b

View Recording: https://youtu.be/96NMQwx_EtI

Takeaways
  • Perfection is the enemy of getting stuff done
  • Something is better than nothing
  • Triage will be necessary at several places in the process



Speakers
avatar for Denise Hills

Denise Hills

Director, Energy Investigations, Geological Survey of Alabama
Long tail data, data preservation, connecting physical samples to digital information, geoscience policy, science communication


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

11:00am EST

Interoperability of geospatial data with STAC
SpatioTemporal Asset Catalogs is an emerging specification of a common metadata model for geospatial data, and a way to make data catalogs indexable and searchable. We have already seen STAC being adopted for both public data and commercial data. Catalogs exist for several AWS Public Datasets, Landsat Collection 2 data will be published along with STAC metadata, and communities like Pangeo are using STAC to organize data repositories in a scalable way. Commercial companies like Planet and Digital Globe are starting to publish STAC metadata for some of their catalogs. Session talks may cover overviews of the STAC, software projects utilizing STAC, and use cases of STAC in organizations. How to Prepare for this Session: See https://stacspec.org/.

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

Takeaways


Speakers
avatar for Dan Pilone

Dan Pilone

Chief Technologist, Element 84
Dan Pilone is CEO/CTO of Element 84 and oversees the architecture, design, and development of Element 84's projects including supporting NASA, the USGS, Stanford University School of Medicine, and commercial clients. He has supported NASA's Earth Observing System for nearly 13 years... Read More →
avatar for Aimee Barciauskas

Aimee Barciauskas

Data engineer, Development Seed
MH

Matthew Hanson

Element 84
STAC


Tuesday January 7, 2020 11:00am - 12:30pm EST
White Flint
  White Flint, Breakout

4:00pm EST

Defining the Bull's Eye of Sample Metadata
In recent years, the integration of physical collections and samples into digital data infrastructure has received increased attention in the context of Open Science and FAIR research results. In order to support open, transparent, and reproducible science, physical samples need to be uniquely identified, findable in online catalogues, well documented, and linked to related data, publications, people, and other relevant digital information. Substantial progress has been made through wide-spread implementation of the IGSN as a persistent unique identifier. What is missing is the development and implementation of protocols and best practices for sample metadata. Effort to do this have shown that it is impossible to develop a common vocabulary that describes all samples collected: one size does not fit all and each domain e.g. soil scientists, volcanologists, cosmochemists, paleoclimate scientists, and granite researchers – to name a few examples - all have their own vocabularies. Yet there is a minimum set of attributes that are common to all samples, the ‘Bull’s Eye of sample metadata’. This session invites participants from all walks of earth and environmental science to help define what is the minimum set of attributes needed to describe physical samples that are at the heart of much of Earth and environmental research.

How to Prepare for this Session:
Participations should come with a list of the mimimum metadata requirements for their institutions or domains.  They should be prepared to give a brief introduction to their needs.

Session Agenda:
  1. Introduction to the issue
  2. Review of existing examples and discussion of the limitations
  3. Discuss minimal requirements; propose changes/addition
  4. Summarize outcomes and discuss next steps
Google doc with the current metadata list and proposed changes

Presentations: ​​​​

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

Takeaways

Speakers
avatar for Lesley Wyborn

Lesley Wyborn

Adjunct Fellow, Australian National University
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 →


Tuesday January 7, 2020 4:00pm - 5:30pm EST
Linden Oak
  Linden Oak, 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

FAIR Laboratory Instrumentation, Analytical Procedures, and Data Quality
Acquisition and analysis of data in the laboratory are pervasive in the Earth, environmental, and planetary sciences. Analytical and experimental laboratory data, often acquired with sophisticated and expensive instrumentation, are fundamental for understanding past, present, and future processes in natural systems, from the interior of the Earth to its surface environments on land, in the oceans, and in the air, to the entire solar system. Despite the importance of provenance information for analytical data including, for example, sample preparation or experimental set up, instrument type and configuration, calibration, data reduction, and analytical uncertainties, there are no consistent community-endorsed best practices and protocols for describing, identifying, and citing laboratory instrumentation and analytical procedures, and documenting data quality. This session is intended as a kick-off working session to engage researchers, data managers, and system engineers, to contribute ideas how to move forward with and accelerate the development of global standard protocols and the promulgation of best practices for analytical laboratory data. How to Prepare for this Session:

Presentations:

View Recording:
https://youtu.be/LOfb_4r7DBA

Takeaways
  • Analytical and experimental data are collected widely in both the field and laboratory settings from a variety of earth environmental and planetary sciences, spanning a variety of disciplines. FAIR use of such data is dependent of data provenance. 
  • Need community exchange of such data consider use of data is broader than the original use of data in the domain. Brings to mind interoperability of such data. Need networks of these data to be plugged into evolving CI systems. In seismology a common standard for data implemented by early visionaries was a massive boon to the field. 
  • Documentation of how analytical data were generated is time consuming for data curators providers etc. Having standards/protocols for data exchange protocols is urgently required for emerging global data networks. OneGeochemistry as example use case for international research group to establish a global network for discoverable geochemical data.


Speakers
avatar for Lesley Wyborn

Lesley Wyborn

Adjunct Fellow, Australian National University
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 →


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

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

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

Citizen Science Data in Earth Science: Challenges and Opportunities
Citizen science is scientific data collection and research performed primarily or in part by non-professional and amateur scientists. Citizen science data has been used in a variety of the physical sciences, including physics, ecology, biology, and water quality. As volunteer-contributed datasets continue to grow, they represent a unique opportunity to collect and analyze earth-science data on spatial and temporal scales impossible to achieve by individual researchers. This session will explore the ways open citizen science data sets can be used in earth science research and some of the associated challenges and opportunities for the ESIP community to use and partner with citizen science organizations.

Speakers:View Recording: https://youtu.be/jTNgWZI6Cik

Takeaways


How to Prepare for this Session: https://www.nationalgeographic.org/encyclopedia/citizen-science/
http://www.earthsciweek.org/citizen-science

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.


Wednesday January 8, 2020 4:00pm - 5:30pm EST
Linden Oak
  Linden Oak, Breakout

4:00pm EST

Structured data web and coverages integration working session
This working session will follow on the "Advancing Data Integration approaches of the structured data web” session and the Coverage Analytics sprint as an opportunity for those interested in building linked data information products that integrate spatial features, coverage data, and more. As such, inspiration will be drawn from projects like science on schema.org, the Environmental Linked Features Interoperability Experiment, the Australian Location Index, and those that session attendees take part in. Participants will self organize into use-case or technology focused groups to discuss and synthesize the outcomes of the sprint and structured data web session. Session outcomes could take a number of forms: linked data and web page mock ups, ideas and issues for OGC, W3C, or ESIP groups to consider, example data or use cases for relevant software development projects to consider, or work plans and proposals for suture ESIP work. The session format is expected to be fluid with an ideation and group formation exercise followed by structured discussion to explore a set of ideas then narrow on a focused valuable outcome. Participants will be encouraged to work together prior to the meeting to design and plan the session structure. Outcomes of the session will be reported at an Information Technology and Interoperability webinar in early 2020. How to Prepare for this Session: Attend the coverage sprint and the "Advancing Data Integration approaches of the structured data web" session.

Shared document for session here.

Full Notes: https://doi.org/10.6084/m9.figshare.11559087.v1

Presentations:

View Recording: https://youtu.be/u2x3I0cr46A

  • Takeaways
    Breakout session information interoperability committee and webinar series. See notes: https://docs.google.com/document/d/1LpcTMwP0mAD4G4Gb8mStI5uSDV61_qWPUkQ9nI1x1cI/edit?usp=sharing
  • Foster cross-project consistency via breakouts. Such as dealing with science on schema.org issue of Links to “in-band” linked (meta)data and “out of band” linked data. Content negotiation and in-band and out of band links Use blank nodes with link properties for rdf elements that are URI for out of band content. Identify in band links with sdo @id, out of band links with sdo:URL
  • Incorporating Spatial Coverages in Knowledge Graphs; Next Steps? Need to explore more on tessellations as an intermediate index. Will carry forward some of these ideas at the EDR SWG Will represent some of these ideas to the OGC-API Coverages SWG Will mention these ideas to the UFOKN Role of ‘spatial’ knowledge graphs Will spatial data analysis and transformation tools grow to adopt/support RDF as an underlying data structure for spatial information or will RDF continue to be a ‘view’ of existing (legacy) spatial data in GI systems?


Speakers
avatar for Adam Shepherd

Adam Shepherd

Technical Director, Co-PI, BCO-DMO
schema.org | Data Containerization | Linked Data | Semantic Web | Knowledge Representation | Ontologies
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 →
WF

William Francis

Geoscience Australia
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 →
DF

Doug Fils

Consortium for Ocean Leadership
avatar for David Blodgett

David Blodgett

U.S. Geological Survey


Wednesday January 8, 2020 4:00pm - 5:30pm EST
White Flint
 
Thursday, January 9
 

10:15am EST

Do you have a labeling problem? Three tools for labeling data
The ESIP community and others in machine learning regularly lament the lack of labeled datasets, needed for certain classes of training algorithms. Generating accurate, useful labels is a hard problem, with no general automated solution in sight. Thus, labeling generally involves human effort, which is challenging because the volume of data needed for training can be very large.

Tools exist to help in labeling data. This session will demonstrate three labeling tools and associated processes:
  • Image Labeler, a fast, scalable cloud-based tool to facilitate the rapid development of Earth science event databases, to aid in automated ML-based image classification, Rahul Ramachandran
  • Labelimg, an open source graphical image annotation tool, https://github.com/tzutalin/labelImg, Ziheng Sun
  • Bokeh, a Python based plotting and annotation tool set for building arbitrary labeling workflows, https://bokeh.org/, Jim Bednar
Time permitting, the session will conclude with a short discussion of thoughts and tradeoffs about the tools.

This session is followed by a hands-on workshop for using Labelimg and Bokeh. Please see the session abstract for "Hands on Labeling Workshop" for information on preparing for that workshop if you are interested in participating.

Presentations
https://doi.org/10.6084/m9.figshare.11629110.v1
https://doi.org/10.6084/m9.figshare.11591739.v1

View Recording: https://youtu.be/3ufBOoD3M1E

Takeaways
  • Machine learning based classification applications require high-quality labelled data sets for both model training and evaluation. There are many existing tools for labeling images (including earth science data), but labeling tasks are very labor and time intensive.
  • If the pre-built labeling tools don’t work for your problem, Anaconda provides a general-purpose labeler-building toolkit based on Bokeh for Python users; see https://examples.pyviz.org/ml_annotators/ml_annotators.html
  • There is opportunity in combining partly automated, partly human labeling, to automate the easy cases while leaving the final call to a person. Currently not much tool support or good practices, hard to integrate.The art of avoiding extra work!

Speakers
avatar for Ziheng Sun

Ziheng Sun

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

Anne Wilson

Senior Software Engineer, Laboratory for Atmospheric and Space Physics
avatar for Yuhan (Douglas) Rao

Yuhan (Douglas) Rao

Postdoctoral Research Scholar, CISESS/NCICS/NCSU


Thursday January 9, 2020 10:15am - 11:45am EST
Glen Echo
  Glen Echo, Breakout

12:00pm EST

License Up! What license works for you and your downstream repositories?
Many repositories are seeing an increase in the use and diversity of licenses and other intellectual property management (IPM) tools applied to externally-created data submissions and software developed by staff. However, adding a license to data files may have unexpected or unintended consequences in the downstream use or redistribution of those data. Who “owns” the intellectual property rights to data collected by university researchers using Federal and State (i.e., public) funding that must be deposited at a Federal repository? What license is appropriate for those data and what — exactly — does that license allow and disallow? What kind of license or other IPM instrument is appropriate for software written by a team of Federal and Cooperative Institute software engineers? Is there a significant difference between Creative Commons, GNU, and other ‘open source licenses’?

We have invited a panel of legal advisors from Federal and other organizations to discuss the implications of these questions for data stewards and the software teams that work collaboratively with those stewards. We may also discuss the latest information about Federal data licenses as it applies to the OPEN Government Data Act of 2019. How to Prepare for this Session: Consider what, if any, licenses, copyright, or other intellectual property rights management you apply or think applies to your work. Also consider Federal requirements such as the OPEN Government Data Act of 2019, Section 508 of the Rehabilitation Act of 1973.

Speakers:
Dr. Robert J. Hanisch is the Director of the Office of Data and Informatics, Material Measurement Laboratory, at the National Institute of Standards and Technology in Gaithersburg, Maryland. He is responsible for improving data management and analysis practices and helping to assure compliance with national directives on open data access. Prior to coming to NIST in 2014, Dr. Hanisch was a Senior Scientist at the Space Telescope Science Institute, Baltimore, Maryland, and was the Director of the US Virtual Astronomical Observatory. For more than twenty-five years Dr. Hanisch led efforts in the astronomy community to improve the accessibility and interoperability of data archives and catalogs.
Henry Wixon is Chief Counsel for the National Institute of Standards and Technology (NIST) of the U.S. Department of Commerce. His office provides programmatic legal guidance to NIST, as well as intellectual property counsel and representation to the Department of Commerce and other Department bureaus. In this role, it interacts with principal developers and users of research, including private and public laboratories, universities, corporations and governments. Responsibilities of Mr. Wixon’s office include review of NIST Cooperative Research and Development Agreements (CRADAs), licenses, Non-Disclosure Agreements (NDAs) and Material Transfer Agreements (MTAs), and the preparation and prosecution of the agency’s patent applications. As Chief Counsel, Mr. Wixon is active in standing Interagency Working Groups on Technology Transfer, on Bayh-Dole, and on Research Misconduct, as well as in the Federal Laboratory Consortium. He is a Certified Licensing Professional and a Past Chair of the Maryland Chapter of the Licensing Executives Society, USA and Canada (LES), and is a member of the Board of Visitors of the College of Computer, Mathematical and Natural Sciences of the University of Maryland, College Park.

Presentations
See attached

View Recording: https://youtu.be/5Ng5FDW1LXk.

Takeaways



Speakers
DC

Donald Collins

Oceanographer, NESDIS/NCEI Archive Branch
Send2NCEI, NCEI archival processes, records management


Thursday January 9, 2020 12:00pm - 1:30pm EST
Forest Glen
  Forest Glen, Panel

12:00pm EST

Hands-on labeling workshop
Intended as a follow on to the "Do You Have a Labeling Problem?" session and to get your feet wet, this working session is for people to experiment with two of the tools presented in that session, Labelimg and Bokeh. Presenters will provide some sample data for participants to work with. Attendees can also bring some of their own data to work with in the time remaining after the planned activities.

It would be best for workshop participants to preinstall Labelimg before coming to the session.   Regarding Bokeh, Anaconda is providing 25 accounts for workshop participants. (Thank you, Jim and Anaconda!).  Installing Bokeh is also an option.  Links for getting these tools are:
  • Labelimg via https://github.com/tzutalin/labelImg#installation
  • Bokeh as part of the HoloViz suite via http://holoviz.org/installation.html

Presentations

View Recording: https://youtu.be/y8NqTLgT8Ao

Takeaways


Speakers
avatar for Ziheng Sun

Ziheng Sun

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

Anne Wilson

Senior Software Engineer, Laboratory for Atmospheric and Space Physics
avatar for Yuhan (Douglas) Rao

Yuhan (Douglas) Rao

Postdoctoral Research Scholar, CISESS/NCICS/NCSU


Thursday January 9, 2020 12:00pm - 1:30pm EST
Glen Echo
  Glen Echo, Workshop