IEEE Geoscience and Remote Sensing Magazine - December 2022 - 275

able to support the scalability needed for big data analyses.
Furthermore, to the best of our knowledge, Rasdaman is
the first native Array database management system that efficiently
manages both data and metadata.
Prof. Baumann closed his inspiring presentation with
a live demonstration. He presented a real-life example of
massive data analysis to illustrate various aspects of Rasdaman,
such as the data cube query language, large-scale distributed
processing and fusion, security, and visualization.
This step-by-step demonstration was useful to showcase
the unique abilities of the Array data model.
Our second speaker, Dr. Manil Maskey, talked about
his vision for NASA's Earth Science Data Systems Program
(Figure 4). He described the data evolution in NASA as a
result of the increase in quantity and quality of remote
sensing satellites, resulting in a 58.6-PB data archive with
more than 2 billion distributed data products. Not only is
this massive data collection an opportunity for Earth science
research but it also presents novel challenges in data
management, storage management, cloud computing, data
discovery, data access control, information retrieval, and
knowledge discovery.
Dr. Maskey also discussed how data collection is driving
the research activities in NASA's Earth science data
systems by introducing some NASA systems/tools under
development, including the Multimission Algorithm and
Analysis Platform and the Visualization, Exploration, and
Data Analysis project.
In the third speech, Dr. Mike Rilee presented a novel
system for analyzing and harmonizing data (Figure 5) with
his talk, " Event-Based Analyses and Associates on a Data
Diversity Harmonizing Framework. " This system is built
on top of an approach known as spatiotemporal adaptiveresolution
encoding (STARE) for combining geospatiotemporal
coordinate location and neighborhood into unified
integer indices (64 b). STARE addresses big data challenges
(volume, variety, and velocity) for Earth science data analyses
by combining diverse data sets (arising from different
FIGURE 4. Dr. Manil Maskey delivers his keynote about data
systems evolution.
satellites with different data formats and resolutions) in
their native states for integrated analysis. This approach is
known as spatiotemporal coalignment. Additionally, the new
system also provides a platform
for scalable high-performance
parallel processing
required for in-depth
event-based analyses.
The audience was impressed
with the user-friendliness
and efficiency of the
system when Dr. Rilee concluded
his presentation with
an engaging demonstration.
The demonstration focused
on using his framework to
capture the partial evolution of a precipitation event over
four days (23-26 January 2021) from the Integrated Multisatellite
Retrievals for Global Precipitation Measurement
database. The demonstration showed that a visualization
of the massive amount of data could be completed in a
few minutes.
Dr. Katie Baynes presented an overview of data management
strategies across NASA (Figure 6). According
to Dr. Baynes, the strategy of NASA's Science Mission
THIS WORKSHOP CALLED
FOR THOUGHT LEADERS TO
PRESENT THEIR IDEAS AND
VISION ON RESEARCH
OPPORTUNITIES IN BOTH
APPLICATION NEEDS AND
TECHNOLOGY FRONTIERS.
FIGURE 3. Prof. Baumann presents " Serving Earth Datacubes With
the Rasdaman Array Database System. "
DECEMBER 2022 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
FIGURE 5. Dr. Michael Rilee presents " Event-Based Analyses and
Associations on a Data Diversity Harmonizing Framework. "
275
IEEE Geoscience and Remote Sensing Magazine - December 2022

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