[ESIP-all] Some AGU Fall Meeting Sessions to Consider Submitting To
Megan Carter
megancarter at esipfed.org
Mon Jul 20 11:32:26 EDT 2020
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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