[ESIP-all] Some AGU Fall Meeting Sessions to Consider Submitting To

[Megan Carter]

ESIP Community Participants suggest you consider submitting an abstract to this
updated list of 2020 AGU Fall Meeting sessions
<https://docs.google.com/document/d/1XqEdPLvbDnrezkXLgKMCRIVtREVeFgAfEGLlZvjkv18/edit?usp=sharing>.
Please feel free to add your suggestions to this list by directly editing
the document. Note: the abstract submission deadline is *this week* July
29th, 2020.

On Mon, Jul 20, 2020 at 11:32 AM Megan Carter <megancarter at esipfed.org>
wrote:

> ESIP Community Participants suggest you consider submitting an abstract to
> the following AGU Fall Meeting sessions. To avoid an overload of individual
> messages to the ESIP-All Mailing List, here is a summary of recommended
> sessions that have been shared recently:
>
>    - IN028 - Linking knowledge in the Earth and Space Sciences
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/103318>: Pioneers
>    of a new paradigm: The challenges confronting the Earth and Space Sciences
>    (ESS) are increasingly complex, avoiding categorization or solution within
>    neatly defined disciplinary boxes. Transdisciplinary, or antidisciplinary,
>    approaches are required to address threats in ESS like climate change and
>    space weather.  However, existing approaches to integrating data and
>    knowledge remain crippling to progress and collaboration. Thus, now is the
>    critical time to bring together the antidisciplinary communities to create
>    a new paradigm of knowledge integration. We welcome contributions that
>    illustrate better structuring knowledge across projects. We will feature
>    pioneering progress on three broad topics: 1) the use of data science as a
>    common language between disciplines, allowing methodology transfer to
>    change how we work; 2) cutting-edge approaches to knowledge management
>    through knowledge graphs/networks; and 3) pioneering advances in project
>    integration. This session will emerge the success stories and best
>    practices for antidisciplinary projects across ESS, ushering in a new
>    paradigm of linked knowledge.
>    - *IN031 - Near Real-Time/Low Latency Data for Earth Science and Space
>    Weather Applications
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/104084>*: Near
>    real time/low latency data and new big data techniques applied to
>    satellite, airborne, marine (including uninhabited aerial/marine
>    systems-UxS), and surface sensors are transforming existing end-user
>    applications and spawning new ones. These applications demonstrate the
>    utility of timely data and advanced analyses in diverse Earth and space
>    science disciplines including weather prediction, flood and river
>    forecasting, earthquake hazards and tsunami forecasting, volcanic
>    eruptions, natural and human-caused hazards, public health, agriculture,
>    marine, early warning, and space weather applications. In addition to
>    traditional and emerging computer analyses, the use of apps for smartphones
>    and tablets presents an opportunity to improve and expand the timely usage
>    of data products and services. This session seeks contributions that
>    demonstrate the benefit of near real time/low latency scientific or social
>    media data, discuss innovative real time analysis approaches including
>    machine learning and big data strategies, decrease data delivery latency,
>    or identify gaps in current capabilities.
>    - IN037 - Scalable Cloud Optimized Spatiotemporal Data Platform (SDP)
>    for Data Driven Analytics
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/105626>:
>    Geospatial data has been effectively used to plan, assess, and predict the
>    effects of extreme events. The diversity and complexity of geospatial data
>    pose challenges in how it is stored, accessed, managed, shared, visualized,
>    and fused for answering many analytical questions. Spatiotemporal Data
>    Platforms (SDP) for Earth and Space Sciences are built on frameworks that
>    enable efficient access, usage, and analysis of temporal sequences of
>    spatial data generated by satellite, airborne and ground-based
>    observations, and models. Such frameworks allow us to interoperate within
>    systems of systems, scale using cloud computing or high-end computing, and
>    accelerate analyses that are reusable and collaboration agnostic.SDPs also
>    support efficient data-driven approaches such as Artificial Intelligence to
>    extract valuable information out of large volumes of data. This session
>    explores the critical components of SDPs including spatiotemporal data
>    ingest, archive, storage, computing (including machine/deep learning),
>    visualization, distribution, modeling, analysis ready data and GIS.
>    - IN038 - Shelter in Place: Mapping Population and Infrastructure in a
>    Vulnerable World
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/103648>: Understanding
>    where people are located, at home or work or elsewhere—and the
>    characteristics of the buildings and structures they shelter in and the
>    critical systems they depend on—has never been more essential. New sources
>    of data on economic and social activity, communications, population
>    movement, health, and resource use, coupled with traditional sources of
>    socioeconomic and infrastructure data, are being harnessed to improve near
>    real-time mapping and monitoring of human behavior and vulnerability vital
>    to disaster response, public health planning, climate risk assessment, and
>    other applications. This session will highlight recent use of geospatial
>    data on population, infrastructure, and environment in the COVID-19
>    response and recovery efforts, and in other major application areas, with a
>    particular focus on overlapping or interlinked hazards and on ways in which
>    scientific data can be utilized more effectively in decision making.
>    - *IN039 - Solving Training Data Bottleneck for Artificial
>    Intelligence/Machine Learning in Earth Science
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/103091>*: While
>    there are successful applications of Artificial Intelligence/Machine
>    Learning (AI/ML) in Earth Science, the wider adoption of AI/ML has been
>    limited. The challenge is no longer the lack of algorithms, tools, or
>    computing resources, but rather the dearth of training data. Access to
>    training data for supervised learning is required to attract AI/ML
>    practitioners to tackle Earth Science problems. Creating labeled data at
>    sufficient scales to support AI/ML algorithms is still a bottleneck and new
>    strategies to increase training data size and diversity need to be
>    explored. This session seeks submissions from AI/ML practitioners and data
>    curators using different approaches or existing products to create new
>    datasets. This session will enable the practitioners to share successful
>    approaches to scale the process of generating labeled datasets. We also
>    seek submissions focusing on best practices for labeling and structuring
>    data including catalog and standardization to benchmark and share training
>    data.
>    - SY014 - Earth Intel: Open-Source Data Analytics and Tools to Address
>    Eco-Security Challenges
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/103814>: Environmental
>    change and variability are increasingly recognized as key drivers of
>    threats to human security at local, national, regional, and global scales.
>    Interdisciplinary data and analytic tools and methods are critical for
>    strengthening the ability of society to improve understanding of past
>    trends and interactions, monitor current conditions and key drivers,
>    anticipate or predict future conditions or extremes, and assess policy
>    options. Widespread access to these data and tools through open source
>    approaches helps to accelerate innovation, increase the reproducibility of
>    and trust in outputs, and facilitate engagement by all stakeholders. We
>    welcome papers on approaches to improving the interoperability of existing
>    tools and data to better support eco-security studies, case studies of the
>    application of data and tools to specific eco-security problems, analyses
>    of stakeholder needs for improved data and tools, and examples of academic,
>    government, private sector, and civil society collaboration on eco-security
>    analysis and decision making.
>    - SY021 - Interactive Data Visualizations to Empower Scientific
>    Projects: Improving Communication from Initial Research Development to
>    Decision Support
>    <https://agu.confex.com/agu/fm20/prelim.cgi/Session/104330>: The need
>    for scientific data visualization became apparent during the COVID-19
>    pandemic, with various visualizations popping up on a regular basis. These
>    tools were created to fill a need by the general public and decision-makers
>    to understand, communicate, and inform on the concerns surrounding the
>    spread of the disease. Interactive data visualizations and related
>    algorithms can help distinguish hidden patterns, reduce complexity, or
>    raise new insights on complex scientific issues.  During a project, these
>    tools can improve collaborations within and among groups, advance
>    communication, and provide support for decision-making. Sharing related
>    experiences can benefit many scientific groups in applying these emerging
>    technologies. From this session, we hope to learn from the success stories
>    and increase application in more scientific projects. We welcome
>    submissions from all disciplines that show their use of these tools and how
>    it has benefited them, especially in interdisciplinary projects with a
>    broad range of stakeholders.
>
>
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