Call for sessions has closed. Please contact Annie Burgess (firstname.lastname@example.org) if you were not able to submit on time.
A list of submitted sessions is below, please click on the session title for more information.
ESIP Education Sampler Session - 10:30 to 11:30 am - July 19th
Drones meet STEAM: (W)rapping data & science into flight
Shelley Olds, UNAVCO
Melding the concepts of data, drones, and science together, the ESIP Education committee is involving teachers from around the country to create activities demonstrating how small recreational drones can be used in educational settings to conduct science, technology, engineering, art, and math (STEAM) investigations. Get an overview from this fun and exciting talk.
Sensors and Drones: Connecting for Science
Lindsay Barbieri, UVM
Exploration of connecting & using earth monitoring sensors with recreational drones (carbon dioxide sensor, wind, thermal and imagery: RGB and near infrared camera and multi-spectral cameras)
Placed Based Learning: Pairing Satellite and Drone Data
Preston Lewis, NASA
Using the MY NASA DATA Live Access Server, you can pair your Drone collected data with NASA Earth System Science data to better understand what’s going on in your backyard (Your schoolyard too)!
Model Aviation as a Tool for Engineering and Remote Sensing Education at the University of Alabama in Huntsville
Casey Calamaio, UA-Huntsville (email@example.com)
Hobby grade unmanned aerial systems (UAS) offer a unique opportunity for Earth System Science and Aerospace Engineering students and teachers to research innovative, interdepartmental projects at the University of Alabama in Huntsville.
Droning in New Zealand: flying a DJI Phantom and generating 3D models from imagery
Sean Barberie, UAF
Lessons learned from a proven methodology where “small aircrafts answer big questions” easily duplicated in STEM education.
Connections between drone cameras and instruments on polar-orbiting satellites
Presenter: Margaret Mooney, CIMSS
Recreational drones provide the perfect stepping stones for G6-12 students to consider undergraduate research projects or careers in remote sensing. This talk explores similarities and differences between aerial photography collected by drones and digital data acquired during satellite flyovers, including a very cool way to acquire satellite images via the SatCam app.
NetCDF-CF is a community-developed data standard first released in 2003. Originally designed to represent climate and forecast (CF) model output encoded in the netCDF binary format, the standard is now widely accepted in the climate, weather, remote-sensing, and other geoscience research communities.
This sesion will provide a venue to discuss current and planned efforts to advance netCDF-CF. Updates will be given on current efforts to draft proposals for specific enhancements to the CF specification.
Building Semantic and Syntactic Interoperability Into EnviroSensing Systems: Part 2
The ESIP EnviroSensing Collaboration Area was organized around the need to create resource guides and share deployment strategies for real-time sensor networks. The NSF EarthCube Integrative Activity called the X-DOMES (Cross-Domain Metadata EnviroSensing) Network is actively building tools and seeks to develop a community of stakeholders within the ESIP community to foster sensor metadata best practices that result in the creation of machine-harvestable, standards-based descriptions of how an observation came to be.
The first half of the workshop is intended to guide participants in the creation of sensor-related vocabularies that include observable properties, sensing technologies, observational parameters and processing methods as spreadsheets and then to assist them in the registery of the content using the newly implemented ESIP-COR (Community Ontology Registry) or a registry within their domain, such as the MMI-ORR (Marine Metadata Interoperability - Ontology Registry & Repository). This will provide a resolvable resource (URLS) for each term which can be used in annotating web services (such as OGC-SWE SOS).
The second half of the session enables participants to develop SensorML profiles for sensors within their domain, referencing the registered terms. This exercise prefaces X-DOMES planned work to engage sensor manufacturers to build machine-harvestable sensor descriptions, which will be also be registered so the content can be resolvable, discoverable and persist within the ESIP Enviro-Sensing community. As the participants assess the SensorML Editor/Viewer, we will develop a cross-domain approach that engages sensor manufacturers and sensor field operators. The main goal is to capture knowledge where it is best understood and provide the capability to fully-describe content to enable data quality assessment and automated quality control.
This workshop relates to activities being planned by Tom Narock and the Semantic Web Committee.
Towards a Data Commons for the Geosciences
Modern scientific discovery, particularly in the geosciences, is driven by a model which entails collaboration around data and software by teams of specialized experts. Common to these collaborations is the need to share and control data and descriptions of the data, to share compute resources and tools, to share and develop code, the need to move data between compute resources and team members, and the need to save and publish data and results. Several groups have been developing technological solutions to enable data-centric collaborations based on the concept of a data commons. However, the notion of a data commons and what constitutes a data commons is not well defined. We propose a workshop to discuss what a data commons should provide for the Geoscience community based on some representative science use cases, where we are today, and what needs to be accomplished.
Validation of Services, data and metadata
Validation of services in important to guarantee that clients can properly be used to exercise those services. Validation can serve as curation process to improve discovery on registries  or for certification purposes .
This session will provide an overview and a demo of the OGC Validation tools. The tools are used to test servers, data and clients. The tests can be customized to not only test implementations against OGC standards but also community profiles. The validation engine (TEAM Engine) and the tests encoded in the compliance testing languages and TestNG are available as open source in GitHub.
 ESIP Discovery Cluster Testbed: Validate and Relate Data & Services - Draft - http://commons.esipfed.org/node/406
 Community Inventory of EarthCube Resources for Geosciences Interoperability - http://earthcube.org/group/cinergi
 OCG Validation Website - http://cite.opengeospatial.org/teamengine/
Sustainable Data Management for Environmental Science Repositories – Summary Session
Many environmental data repositories were initiated to fulfill specific needs or objectives, i.e. archiving and disseminating data from a project, network of research sites, institution, or funding source. The sustainable data management cluster is exploring how we might develop this network of repositories in a way that produces new collaboration and curation strategies within a framework that provides a positive return on our investment (ROI).
Two working group sessions at this meeting will continue the work conducted at a November 2015 workshop, in Tempe, AZ. This session will give those groups the opportunity to share additional progress, and for the larger group to consider the next steps in this process.
Colleagues who have not been involved to date are welcome to attend, as we wish to extend this dialog to the broadest possible audience.
DreamBIG: Brainstorm Tools, Analytics, Apps, and Value using Analogies
Effective adaptation to our changing environment requires public, business, academic, and non-profit organizations to communicate and collaborate to make decisions for the long term. In practice, it can be confusing to determine how to get the necessary information and expertise to flow across these organizational boundaries. We propose this DreamBIG session to brainstorm ways to leverage the shared robust public collection of large and complex environmental data sets, data resources and environmental models and develop a collective set of application ideas.
Using analogies from medicine, psychology, marketing, investing, and other BIG data-generating fields-of-practice we will do a group participatory brainstorming exercise with a one-minute, one-slide presentation format to describe our great ideas on how to use geophysical data to analyze conditions surrounding and adaptation solutions to environmental change’s grand challenges and opportunities. At least one background webinar will proceed the ESIP Summer Meeting session. Innovation takes thinking!
Please participate in this work session to take a leadership role in developing the emerging interdisciplinary field combining science, environmental analytics, and business.
“NASA GIBS/Worldview Visualization – Granules / Vectors / Curtains”
NASA’s evolving Global Imagery Browse Services (GIBS) project provides raster imagery for a wide range of geophysical parameters across EOSDIS missions. This imagery is available through a set of web services and associated standard interfaces which facilitate efficient transmission of raster layers to mapping clients which consume geospatial imagery for a wide spectrum of applications - visual metadata for search and discovery, exploration and identification of environmental events and other phenomena, GIS, education and outreach, or simply contextual reference.
The varied types of Earth science data within the ever-growing holdings of EOSDIS require GIBS to move and evolve beyond its current operational focus of serving daily global and polar raster composites. This ESIP session focuses on current GIBS development and planned near term activities which accommodate the various flavors of EOSDIS science data products, including granule/sub-daily/scene imagery, vector-based data products, and curtain/vertical profile plots. The purpose of this session is to solicit comments, questions, and user scenarios from data providers, data users, and potential data users alike. We will also present some R&D work in progress facilitating direct interaction with the source science data behind the GIBS imagery, locally within a browser.
The Users’ Perspective: How are Energy Utilities and Developers Using Earth Observation Data to Address Climate Resilience and Support Renewable Energy?
Energy utilities and power project developers are increasingly recognizing the climate-sensitivity of their day-to-day operations and planning on the 20-30 year timescale. Solar and wind power project developers require resource data and forecasts for project design, operations, and financing. Increasingly sophisticated software and models from value-added providers and in-house meteorology groups at some utilities rely on Earth observations from NASA, NOAA, and other sources to support their decisions. Hear from energy sector end users on their current and emerging decision-support needs focused on a climate resilient infrastructure and renewable energy development. A summary of a recent NASA-sponsored workshop on this topic will provide context for the panel discussion.
Earth Science Data Analytics Tools, Techniques and More
The Earth Science Data Analytics (ESDA) Cluster has made great strides in understanding the utilization of data analytics in Earth science, an area virtually untouched in the literature. In achieving its goal to support advancing science research that increasingly includes very large volumes of heterogeneous data, the ESDA Cluster is in the process of categorizing existing tools and techniques utilized in Earth science data analytics data preparation, reduction, and analysis. This session will provide a student’s ‘student of Data Science’ point of view showcasing the usage and usability of Data Analytics. This will set the stage to address a more detailed ESDA categorization, and begin the discussion on how best to perform the gap analysis between data analytics research needs and tools/techniques available.
Describing the repository landscape for data curators
We have many repositories in scientific domains for natural and social science research data, and an increasing expectation that primary research data will be deposited there. Data centers and repositories offer a variety services to researchers for this purpose, and a growing community of data managers and curators act as liaisons between primary researchers and repositories. To understand how to work with repositories, data managers need to know their basic features. Several groups have embarked on a discussion of the landscape of repositories and their services, eg, the Research Data Alliance (RDA), the Council of Data Facilities (CDF), and at a recent workshop focused on planning collaborative efforts among repositories in Tempe, AZ, that culminated in an ESIP cluster (Sustainable Data Management). This session will continue the discussion. We will become familiar with the existing and planned material describing repositories (e.g., from RDA, CDF, re3data.org), and assemble questions asked by curators and researchers when deciding which repositories to contribute to, and how to work with them.
Who said a catwalk can't be a bridge?
Got an R-based model looking to strut its style?
ArcGIS has an R bridge, new scientific python libaries, and multi-dimensional support. This session will work with you to showcase your models and science on the ESIP runway (don't fear... the "runway" is our fashion-metaphor for a breakout session). Working together in advance and then together in the session, we'll look at the models through these different tools.
The idea is to connect up some of your data, models, and methods to the out of the box tools to see what new analysis and visualizations can result.
Trying out a new way of doing and a different way of presenting, who knows what new connections result?
Full Motion Video & Drone Data Processing: Collaborative Experiment
You've got the drones, and we've got some software... let's do processing. We're looking to collaborate with some drone folks to understand how Eri's Full Motion Video and Drone2Map could be used in science activities and missions.
For this mini-session - possibly a session inside a session? - we're looking to collaborate ahead of time, work with you and the drone(s) before or during the ESIP Summer Meeting, and then report together findings on the experience. Poster, Session, or Lightning talk - looking forward to an experiment together!
Ontology Design Pattern-driven Linked Data Publishing
In recent years, Linked (Open) Data has emerged as a prominent framework for publishing structured data on the Web adopted by various domains including geosciences. Linked Data allows data from different sources to be interlinked using HTTP Uniform Resource Identifiers (URIs) and be machine-processable in a standard way via the Resource Description Framework (RDF). Interoperability and integration across different datasets are achieved by the use of vocabulary that is agreed upon by the community or standardized by some governance body. Such a vocabulary is often specified in an ontology, which formalizes the semantics of the vocabulary terms being used. The challenge is that many ontologies, including domain ontologies, are too complicated, restrictive, and difficult to use and understand. This makes many linked data publishers avoid ontologies and prefer to simply use less formal vocabulary. Although this allows linked data publishing staying relatively simple, the resulting datasets would only have a low quality metadata, making the datasets harder to understand, interoperate, and integrate. In this tutorial lecture, we shall introduce a modular ontology architecture based on the so-called ontology design patterns, which are sufficiently flexible, easier to understand, and less restrictive, while allowing the linked datasets to be equipped with a sufficiently high quality metadata, enabling interoperability and easier integration across semantically heterogeneous datasets. We will demonstrate how such an ontology architecture works in a data integration setting, catering multiple perspectives from different data providers, as well as accommodating existing vocabulary that are already employed by the community.
A Framework to Evaluate the Return on Investment (ROI) of a Data Repository
This working session will continue the efforts initiated at the Tempe Workshop in November, 2015 and continued at the ESIP 2016 Winter Meeting. For background information, please see below. All are invited.
This effort seeks to develop a framework to evaluate the return on investment (ROI) of a data repository, providing help in determining the value of data and services around them to stakeholders of varying perspectives.
Our agenda for this working session is to:
1) BRIEFLY recap the summaries of our discussions of the references provided on this page: http://wiki.esipfed.org/index.php/Return_on_Investment_ROI_References. This is only a recap as we expect to more thoroughly discuss these references via telecons leading up to this session. We request that participants in the session either participate in those telecons or peruse the references beforehand in order to arrive up to speed at the session.
The summaries are very short reviews of the references with respect to these issues and questions:
· How is value (to stakeholders) defined / discussed?
· What are the definitions / explanations / categories of repository stakeholders?
· How were similarities among data repositories defined / discussed?
· How were differences among data repositories defined / discussed?
· What, if any, were the metrics used to measure the value(s) returned to repository stakeholders?
· What do the references say about the reason(s) for caring about this topic?
b) Discuss potential funding possibilities for a planning grant to develop this idea and scope some work. We will lay groundwork for this part of the discussion beforehand by investigating possible funding opportunities and their requirements and goals, also via our telecons.
c) Target one of these possibilities and develop an outline for a proposal that takes into account their requirements, schedule, project scope, etc.
In November 2015 representatives from various data repositories, data service providers, and others participated in a two and one half day workshop in Tempe, AZ, sponsored and funded by NSF, to discuss collaborative strategies for sustained environmental data management. As an introduction, see the following quote from a briefing document participants received before the workshop:
“Many environmental data repositories were initiated to fulfill specific needs or objectives, i.e. archiving and disseminating data from a project, network of research sites, institution, funding source, to accompany paper publications, or more recently, as data papers. This initiative was funded with the goal of exploring how we might develop this network of repositories in a way that will produce new collaboration and curation strategies that also cater to the currently underserved single investigators and move environmental data from ‘available’ to ‘usable’, in order to accelerate scientific inquiry.
With this goal in mind we are bringing together data curators from a range of environmental research fields, data aggregators, tool developers, computer scientists and environmental scientists (both data providers and users) for an informed dialog which draws on our collective experience managing data and repositories.”
Several of the topics that surfaced during the workshop garnered enough interest from participants to request that discussions continue under the auspices of a new ESIP cluster Those topics have coalesced to be:
⁃ Defining a Return on Investment (ROI) of Data Repositories for Society
⁃ Conducting a Landscape Analysis and Gaps for Environmental Data Repositories and Describing a Common Technical Vision
The ESIP cluster, Sustainable Data Management, was recently formed. The wiki page is http://wiki.esipfed.org/index.php/Sustainable_Data_Management.
The ROI working group exists under this cluster. Notes from the ROI session at the ESIP Winter Meeting and other information are available at http://wiki.esipfed.org/index.php/Return_on_Investment_Subgroup_%28ESIP_....
Interdisciplinary Data Curation for Socio-Environmental Research
In the Earth Sciences, many researchers are striving to address larger environmental challenges. From understanding our changing climate, to surface processes that result in water issues, deforestation, biodiversity loss - these earth science questions can be framed at various spatial scales, ranging from local to global. These complex earth systems are best understood not just through any one disciplinary approach, but through an interdisciplinary lens.
Research on these complex, systems science problems, then, is often better organized around the site (geographic location) instead of by discipline. This has implications for:
- Data collection and management: sampling sites must be well documented and contextualized, and data must be collected in a way that is usable and interpretable for researchers in a range of fields
- Data sharing and archiving: repositories must take steps to avoid becoming disciplinary silos, and researchers must take additional steps in their metadata creation
- Data analysis: researchers must be careful in scaling up the understanding / knowledge from site-specific to regional or global levels
This is especially true when considering that many environmental challenges within the earth sciences have a human/social component, often bringing social-science research (economics, psychology, decision-making) into the interdisciplinary fold. There are organizations, such as SESYNC, addressing social-environmental problems via case studies and interdisciplinary data analytics, and this Session is intended to bring the ESIP community into the conversation.
This Session will look at specific case studies and discuss ways in which the ESIP community might be able to offer insights into the data management and analytics necessary for addressing interdisciplinary research more broadly.
- Yellowstone: geobiology at Mammoth Springs
- Los Angeles, California: paleontology and paleoecology research at the La Brea Tar Pits
- Agricultural Sites: Ecosystem Services (Climate, Water Quality and Farmer Livlihoods) Vermont
- Vermont Monitoring Cooperative (present brief series of Case Studies or general overview)
Hoperful Collaborations with ESIP Clusters:
- Data Stewardship
- Data Analytics