2022 ESIP January Meeting

The United States federal government makes available a great number of datasets around environmental governance. But how easy are these datasets to use in answering real questions from environmental justice advocates?

Building on some of the work and ideas from this summer’s session “Designing a Public Portal for Participatory Environmental Governance”, participants will engage with questions from various environmental justice stakeholders and advocacy groups, attempting to map questions to public datasets using new tools provided & researched through the ESIP Lab-funded project “Developing an Environmental Enforcement Data Portal for Grassroots and Congressional Action” and their own savvy and ingenuity.

For those who joined this summer's session: welcome back, let us show you all the new things we've built!

For those who are new: welcome, we have lots to show you!

What to expect

• This is a high-participation session! Come ready to roll up your sleeves.
• Ideally we'll have a mix of attendees: people totally unfamiliar with this space, people who know EPA datasets really well, etc. It's helpful for us to get a range of perspectives; come as you are!
• The majority of the session will be in team breakouts, working together to solve specific challenges. We've designed these challenges so that your work will materially advance the project.
• Expect to walk away with a better understanding of the needs of environmental justice advocacy groups and the tools at their disposal (including some we are building).

Recommended ways to prepare for this session:

• Newcomers are welcome to participate. NO preparation or prior experience is required.
• Prior work in this space can be seen at environmentalenforcementwatch.org and https://github.com/ESIPFed/Environmental-Enforcement-Watch.
• It might be helpful to skim the notes from the summer session

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Many scientists are actively experimenting AI/ML methods to either replace the conventional methods or improving the existing data products to higher accuracy and resolution. However, most people complains that the experiments reported in research literature are very difficult to neither reproduce nor reuse. The source code and notebooks and associated data, models, and results are hard to find, access, interoperate, and reuse. Meanwhile, the trained models are often biased towards the majority and common patterns due to sampling strategy or natural distribution. These issues are significantly harming the usability and trustworthy of AI/ML in geoscientific application. This session aims to solicit community experiences, opinion, and vision to enhance the FAIRness and fairness of AI/ML.

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The federal government’s Small Business Innovation Research (SBIR)-Small Business Technology Transfer (STTR) programs are highly undervalued by the very agencies they were intended to benefit. SBIR-STTR programs can provide federal agencies with young but proven technologies that can be rapidly adopted to address agency goals and objectives…on a sole source basis. Established in 1982 (SBIR) and 1992 (STTR), these programs provide billions of dollars in competitive funding for high tech development by small businesses that could be tapped by more agencies and their contractors to promote innovation and rapid adoption of new technology.

SBIR contracts/grants could be a valuable source of support for public-private collaboration and innovation in the ESIP community and could help ESIP increase private sector participation in its initiatives while making more data available for all people from Data Generation to Data Use and Understanding.

A key challenge, however, is that many agencies and federal contractors don’t understand the value that SBIR-STTR contracts and subcontracts can bring to the table, or the steps needed to access these resources. This session will identify specific SBIR examples and discuss the benefits and gaps that exist in the program that may be hampering their agency adoption. Opportunities exist for agencies that need to share their data, work across line offices, and use their data as strategic assets—as well as to meet their goals for diversity and equity in procurement. Diverse opportunities exist for small businesses as well as academic and nonprofit organizations that work with small businesses as subcontractors to access procurement opportunities that could scale up your work in high-impact applications. Come to this session to learn how you can take advantage of SBIR-STTR technologies and accelerate procurement opportunities for your organization and accelerate data-driven decision making!

You will leave this session with a clear understanding of how your agency, your non-profit, or your commercial enterprise can move forward and engage SBIR small businesses as we work to rebuild our nation’s economy.

We will hear from: Jason Kessler, NASA SBIR Program Executive, NASA Headquarters who will provide us with an overview of the SBIR program
We will also hear about a successful STTR project from Bob Chen, Director, NASA SEDAC & about a successful SBIR Phase III technology from Dave Jones, CEO, StormCenter Communications, Inc. and John Williams, Director of Innovation and Technology, Office of Innovation and Technology, Office of Investment and Innovation, U.S. Small Business Administration will be available during the session to answer any questions from the SBA.
Please join us for this exciting ESIP Session.
Recommended ways to prepare for this session: This session will offer excellent information about the SBIR-STTR programs which is good for any level of participant in the ESIP Federation. This session should also provide good information for program managers and contract officers in any US Federal agency, government lab, prome contractor and university. It will be highly educational for agency representatives, non-profit leaders and commercial company leaders.

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Data professionals who engage in CDI and ESIP Collaboration Areas have many mutual interests both in terms of technical topics and application areas. In an effort to increase communication between these groups, we will host a session to share and explore potential synergies. This session will make connections between people in both communities, bring to light lessons already learned or resources already produced, and help to identify common interests and challenges to collaborate on in the future. We will also explore mechanisms for continued sharing across ESIP, CDI, and other related groups going forward.

We will focus on connecting people, expertise, and resources from the ESIP Community Resilience and Disasters collaboration areas and the USGS Risk Research Applications Community of Practice. After brief introductions to the groups and their purpose by the group fellows, we will use this example to address the questions: How do you know where to go when you need help or expertise or want to share something? How can we usefully map the expertise that resides in these separate groups?

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Agenda

The ESIP Information Quality Cluster, collaborating with other groups from around the world, has led the formation the baselined International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets (see https://doi.org/10.31219/osf.io/xsu4p). The baselined dataset quality guidelines offer an opportunity for improvement to serve multiple disciplines, use cases, and domains of applied sciences. In addition to the Earth sciences and related study areas, various disciplines and data types each need information about data quality when assessing data for potential reuse and when deciding how to use the data. For example, when studying climate change, environmental hazards, and other multidisciplinary issues, often, data from various disciplines are integrated. Such multidisciplinary data integration activities raise cross-disciplinary questions about the quality of individual datasets and approaches to fusing such cross-disciplinary quality information. Also, new questions about data quality emerge when planning to use the products and services that include datasets that have been integrated from various disciplines. Session participants will discuss use cases and data quality issues for interdisciplinary data (re)use and integration in terms of the implications for enhancing the dataset quality guidelines.

Recommended ways to prepare for this session: Identify data quality questions and issues of interest.

Session Notes

Session Recording