DTIC ADA438833: Future Science Direction: Environmental Information Science Plan

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Future Science Direction: Environmental
Information Science Plan
January 2005
By Anne F. Frondorf, David R. Boldt, Deborah R. Hutchinson, William G. Miller,
Douglas R. Posson, and Stuart A. Sipkin
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iii
Contents
Introduction.....................................................................................................................................................1
Scientific Challenges and Research Questions .......................................................................................3
Environmental Information Science: Major Scientific Challenges .......................................................3
Challenge #1: Acquisition and Extraction of Information from Environmental Systems
and Processes .........................................................................................................................3
Challenge #2: Synthesis, Analysis, Interpretation, and Modeling of Information on
Environmental Systems and Processes ..............................................................................4
Challenge #3: Communication and Representation of Information on Environmental
Systems and Processes .........................................................................................................4
Defining the Unique Role and Potential Contribution of the USGS in Environmental
Information Science ........................................................................................................................5
Example 1: Modeling the Spread of Invasive Species ...................................................................5
Example 2: Sediment Transport Modeling in the Coastal Ocean ..................................................6
Responsiveness to NRC Report on Grand Challenges in Environmental Sciences ...........................6
Past and Current USGS Activities in Environmental Information Science .........................................7
Example 3: New Methods for Analyzing Seismograms ..................................................................7
Building an Environmental Information Science Workforce .................................................................8
Scientific Information Infrastructure Requirements ................................................................................9
Example 4: Mapping the Sea Floor ..................................................................................................10
Opportunities for Collaboration .................................................................................................................10
Example 5: Understanding Earthquake Fault Zone Structure .....................................................11
Implementing a USGS Environmental Information Science Research Plan .....................................12
Summary........................................................................................................................................................12
References ....................................................................................................................................................13
Appendix I: Framework for a Long-Term Environmental Information Science Research
Agenda .............................................................................................................................................14
Appendix II: Examples of Scientific Questions ......................................................................................15

Future Science Direction: Environmental Information
Science Plan
January 2005
By Anne F. Frondorf, David R. Boldt, Deborah R. Hutchinson, William G. Miller, Douglas R. Posson, and
Stuart A. Sipkin
Introduction ing the Scientific Frontier” (see http://internal.usgs.gov/
director/frontier) and in reports from the National Research
Council (NRC) (NRC, 1999, 2001a, 2001b) and the National
Increasingly, U.S. Geological Survey (USGS) scientists are
Science Foundation (Pfirman and others, 2003). The need for
called upon to develop fundamental understanding of inher-
a more focused, Bureau-wide emphasis in this interdisciplin-
ently complex environmental systems and processes. Their
ary area has also been identified as a high-priority objective
objectives are to use this understanding to develop more
in the Bureau’s long-term “Information Strategy” and in the
accurate and meaningful models, assessments, forecasts, and
5-year program plan for the Bureau’s Enterprise Information
predictions of how these complex systems and processes may
Program.
react to specific natural changes and human alterations. A
The NRC report on Future Roles and Opportunities for
fundamental USGS goal is to effectively communicate this
the U.S. Geological Survey (NRC, 2001a) emphasizes that:
increased knowledge and understanding of complex systems to
support society in meaningful ways.
The questions posed to the agency increasingly
The complexity and diversity of the earth and biological
call for multifaceted, analytical, and integrative
systems and processes we seek to understand lead directly to
investigations of complex processes and systems.
a set of significant scientific challenges in how we acquire,
By evolving into a natural science and information
interpret, and communicate the information represented or
agency, the USGS will be able to play a leadership
contained in these systems and processes. Many physical,
role in the elucidation of the geological, hydrologi-
chemical, and biological systems and processes—­from DNA
cal, geographical, and biological processes that are
to entire ecosystems—­can be most effectively elucidated and
important to the nation… The USGS should give
understood when viewed as systems of information and com-
more attention than it has in the past to integrative
putational elements. It follows that the concepts, principles,
data analysis, problem solving, and information dis-
and techniques of information/computer science can be used
semination…the USGS should do more to interpret
in an interdisciplinary way with our natural science capabili-
what the data mean…In the twenty-first century, the
ties to help USGS scientists solve formidable natural science
USGS should emphasize that system modeling is a
research problems and to better communicate complex con-
powerful tool for integrative science. System model-
cepts. This is the realm of Environmental Information Science.
ing would enable the USGS, in coordination with
“Environmental Information Science” is defined here as
other agencies and partners, to develop a greater
the development, testing, and application of interdisciplinary
understanding of complex science problems that
approaches—­integrating physical, biological, computer, and
involve natural and human systems…
information sciences—­to advance understanding and yield
new insights into environmental phenomena at all levels of Achieving scientific understanding of inherently com-
complexity. plex, interdependent systems is not easy. These systems,
While not explicitly called environmental information processes, and phenomena are often multidimensional in space
science, this research direction has been highlighted in several and time and involve nonlinear interactions of myriad physi-
recent USGS science program planning documents (e.g., cal and biological factors. Spatial scales of interest may span
Bohlen and others, 1998; USGS, 1999), in the results of the orders of magnitude from submicroscopic to global levels;
January 2001 USGS workshop on “USGS in 2050: Envision- temporal scales may range from instantaneous to millennia.
 Future Science Direction: Environmental Information Science Plan
Issues involving the movement, processing, or cycling of understanding of complex systems and processes into the
materials and living organisms within and across systems are decisionmaking process with the result of achieving greater
pervasive. Systems and processes are frequently difficult to societal benefit and impact with our science.
observe and study in their natural state owing to their irregu- This plan proposes a “Future Science Direction” for the
lar and infrequent occurrence, physical remoteness, extremes USGS that will focus on the development of an enhanced
of size, and (or) hazards posed to humans. In some cases, interdisciplinary capability linking natural science and com-
direct observation or measurement can alter the system being puter/information science to address key research questions
observed. Sometimes such overwhelming amounts of data facing the USGS today and over the next 25–30 years. This
are available that traditional techniques are insufficient to future science direction would build on existing USGS activi-
extract useful information. In other studies, extremely limited ties and expertise in this interdisciplinary area, recognizing
amounts of data are collected at small scales and (or) for very that some environmental information science-type research
limited time periods, for which standard statistical approaches is currently underway in all four of the major USGS science
for extrapolation or interpolation over larger areas or longer disciplines. Creating a more Bureau-wide focus on this subject
time periods are not adequate to capture the inherent complex- and providing a long-term research agenda for the Bureau as a
ity of the systems being studied. Undertaking the interdisci- whole can help leverage these independent ongoing activities,
plinary research needed to address this complexity is even share techniques and approaches across science programs and
more challenging due to the need to accommodate the differ- disciplines, and move the entire effort ahead in a significant
ent techniques, cultures, languages, and ontologies of different way even without a significant influx of new funds. It will bet-
scientific disciplines. ter position the USGS to take advantage, as an integrated part
Further issues involve the effective communication of of our natural science research, of the significant evolutionary
this environmental complexity to better inform public policy advancements in information science and technology that are
and decisionmaking (Sarewitz, Byerly, and Pielke, 2000). likely to occur over the next 25–30 years.
USGS scientists face a range of challenges in how they can In addition to Environmental Information Science, the
effectively communicate their new understanding of these USGS has identified seven other Future Science Directions
extremely complex, multidimensional systems and processes; (Coastal Environments; Earthquake Hazards; Ecosystem
of the relative likelihood of potential outcomes; and of the Health, Sustainability and Land Surface Change; Energy;
nature of scientific uncertainty itself, to a diverse assortment of Ground-Water Resources; Invasive Species; and Rivers) as
different constituencies and audiences, ranging from scientists topics meriting special attention from the USGS and from our
and resource managers, policy and decisionmakers, teachers partners in the scientific research community over the next
and students, to the interested citizen. several decades, because of their importance to the Nation.
Many of the scientific questions outlined above are Each of these seven Future Science Directions has, in turn,
fundamentally related to the complexity, multidimensionality specifically noted the importance of information science and
and nonlinearity of the information represented in the systems computational techniques to the resolution of some of the
and processes we study. Information science1, by focusing on most pressing scientific questions in each area of inquiry.
the informational elements of complex systems as specific It is believed that by facilitating the development of a more
objects of study, can offer natural scientists complementary focused, Bureau-wide research agenda in this interdisciplinary
approaches that can help address these questions. Examples of area, this Environmental Information Science Future Science
information science-based capabilities that can be applied to Direction plan can help address those information science
the study of complex environmental systems include algorithm requirements which are common to all the other seven subject
development, multidimensional modeling, multivariate statisti- areas.
cal modeling, computational complexity, machine learning, Research partnerships between the USGS and other gov-
neural networks, chaos theory, emergent properties, pattern ernment agencies, academic institutions, and private industry
recognition, artificial intelligence, advanced visualization, and will also be an essential part of this future science direction.
analysis of the basic properties and structure of information This is a way for the USGS to take greater advantage of the
itself. The specific examples provided throughout this plan extensive computer/information science expertise and fund-
show how USGS natural science and computer/information ing resources of potential partners, and to work together with
science are already intersecting to forge new directions in this partners on these crosscutting, societally relevant research
type of interdisciplinary research. These illustrations share challenges.
a common thread in that information science holds part of One of the greatest challenges that the USGS will face in
the key to solving these diverse, and sometimes intractable, pursuing this future science direction is to ensure it is effec-
numerical, conceptual, and integrative research questions. tively linked to and integrated with the scientific goals and
Advanced information and computer science can also sig- activities of the USGS science programs. This new research
nificantly enhance USGS ability to communicate scientific direction should not come at the expense of discontinuing
the invaluable foundation of USGS national databases that
1 Note that “information science” is being used generically in this plan to maintain data about resources and hazards (e.g., earthquakes,
represent both the scientific disciplines of computer science and information
streamflow, topography, biological resources, etc.) or of our
science.
Environmental Information Science: Major Scientific Challenges 
basic research into physical, chemical, and biological pro- • Scientists can combine raw data and new models from
cesses that remain poorly understood. Rather, the strength of many sources, and utilize the most up-to-date tools to
the environmental information science research direction is analyze, visualize, and simulate complex interrelations.
to use information science to build bridges across and within
• Scientists can collect and make widely available far
the natural science disciplines to reveal their complex inter-
more information (the outputs of all major observato-
relationships. Environmental information science research
ries and astronomical satellites, satellite and land-based
is at the core of integrated systems science and helps lay the
weather data, three-dimensional images of anthropo-
foundation for many conceptual systems models. Maintaining
logically important objects), leading to a qualitative
this vision of using environmental information science to fur-
change in the way research is done and the type of
ther scientific understanding of natural processes and human
science that results.
alteration, and recognizing but not becoming focused on mere
technological requirements, will be essential to the success of
• Scientists can work across traditional disciplinary
the initiative.
boundaries: Environmental scientists will take advan-
tage of climate models, physicists will make direct use
of astronomical observations, and social scientists will
Scientific Challenges and Research analyze interactive behavior of scientists.
Questions • Scientists can simulate more complex and exciting
systems (cells and organisms rather than proteins and
The 2003 National Science Foundation report entitled Revolu- DNA, and the entire earth system rather than air, water,
tionizing Science and Engineering Through Cyberinfrastruc- land, and snow, independently).
ture: Report of the National Science Foundation Blue-Ribbon
• Scientists can visualize the results of complex data sets
Advisory Panel on Cyberinfrastructure (Atkins and others,
in new and exciting ways, and create techniques for
2003) describes how current and future developments in the
understanding and acting on these observations.
computing and information sciences can help transform the
conduct of research in the physical, biological, and social sci- • Scientists can work routinely with colleagues at distant
ences. These changes include: institutions, even ones that are not traditionally con-
• The classic two approaches to scientific research—­ sidered research universities, and with junior scientists
theoretical/analytical and experimental/observational—­ and students, as genuine peers, despite differences in
have been extended to computer simulation and model- age, experience, race, or physical limitations.
ing to explore new possibilities and to achieve new
precision. Within this overall context of scientific evolution and
change, USGS research in the area of environmental informa-
• The enormous increase in processing speed of comput- tion science should be directed at extending and deepening our
ers and networks have enabled simulations of far more understanding of complex environmental systems, processes,
complex systems and phenomena, as well as visualiz- and phenomena by focusing on the three major scientific chal-
ing the results from many perspectives. lenges relating to the acquisition, analysis, and communica-
tion of information.
• Advanced computing is no longer restricted to a few
research groups in a few fields, such as weather predic-
tion and high-energy physics, but pervades scientific
and engineering research, including the biological, Environmental Information Science:
chemical, social, and environmental sciences, medi-
Major Scientific Challenges
cine, and nanotechnology.
• Crucial data collections in the social, biological, and
physical sciences are now online and remotely acces-
Challenge #1: Acquisition and Extraction of
sible; modern genome research would be impos-
sible without such databases, and soon astronomi- Information from Environmental Systems and
cal research will be similarly redefined through the Processes
National Virtual Observatory.
This challenge focuses on the need to significantly advance
• Groups can collaborate across institutions and time
our capabilities to extract information from complex systems
zones, sharing data, complementary expertise, ideas,
and processes in three major ways: (1) increasing the amount
and access to special facilities without actual travel.
of meaningful information acquired, (2) increasing the qual-
ity of information acquired, and (3) increasing the efficiency
 Future Science Direction: Environmental Information Science Plan
with which information is acquired, used, and reused (e.g., by (1) effectively representing inherent information-related prop-
reducing or eliminating the need for direct human interven- erties, such as complexity, uncertainty, or credibility, to widely
tion in observations and measurements, increasing real-time different audiences; (2) developing more advanced approaches
data-acquisition capabilities, and using previously collected for visualization and simulation of complex multidimensional
data in totally new applications). This challenge includes systems and phenomena; (3) increasing the ability to com-
improving our ability to observe and measure environmen- municate newly acquired data and information in real-time or
tal systems in totally new ways, such as through the use of near-real time; (4) increasing the speed with which research
computer-designed, deployed, and operated sensor networks, methods can be provided as operational analysis tools; and
robotics, wireless technologies, or the use of molecules, cells, (5) design and development of a new generation of scientific
and organisms as programmable biological or chemical sen- data and information products and delivery services (e.g., new
sors/messengers. USGS scientists can use “virtual laborato- approaches for continuously measuring how scientific data
ries” within computers to conduct experiments and repeatedly and information are used and understood by different custom-
“observe” phenomena (such as earthquakes, volcanoes, or the ers so that products and delivery services can be continuously
spread of wildlife-transmitted human diseases) that cannot be refined).
readily or realistically observed in situ. We can also signifi- The three Environmental Information Science research
cantly increase our ability to extract previously “hidden” or challenges described above require scientific insight, strong
“unused” data and information from existing data sets for use links to the disciplinary sciences of the USGS, and the capac-
in new applications and to discover new cross-disciplinary pat- ity to focus our science on environmental issues of greatest
terns in data (emergent properties, patterns and trends, etc.). significance to society, including those identified in the other
seven USGS Future Science Directions. Some of the scientific
issues that will need to be addressed to meet these challenges
Challenge #: Synthesis, Analysis,
include:
Interpretation, and Modeling of Information on
(1) Issues of scale play a significant role. Scales of
Environmental Systems and Processes analyses are rapidly expanding from local to global as
additional computational power and seamless data sets
This challenge focuses on the need to significantly advance become more readily available.
our capabilities to use the information we have extracted
from complex environmental systems and processes to bet- (2) Complexities associated with scientific domains are
ter elucidate how these systems and processes function at a complicated by complexities caused by data gathering
fundamental level, to understand how and why they react to and sampling, leading to complexities associated with
specific natural and human-induced changes, and to develop data volume (Gahegan, 2001). Understanding is often
more accurate predictions of, or scenarios for, possible future complicated by local variation.
outcomes. This challenge includes: (1) improving our ability
(3) Increase in dimensionality is allowing geometric mod-
to integrate complex multidisciplinary and multidimensional
els to be treated as n-dimensional, instead of the more
data; (2) accelerating the scientific process itself and expand-
traditional simple curves and surfaces. The demand to
ing our knowledge of complex systems by allowing scientists
store and provide direction, in addition to location and
to collaborate in entirely new ways (e.g., enabling scientists to
time, increases requirements for the expressive power
work more effectively together across disciplinary “language”
of systems, requiring at least seven degrees of freedom.
barriers or facilitating more real-time, remote collaborations);
and (3) developing a new generation of advanced modeling (4) Linear analyses in the form of photogrammetry and
techniques and algorithms (e.g., three- and four-dimensional map algebra are common. The increase in dimension-
modeling, more accurate and reliable statistical modeling ality of many problems leads to requirements for the
and forecasting, more rigorous approaches for quantifying ability to study nonlinear systems. Examples include
and incorporating uncertainty in predictive models through unexpectedly organized behaviors of nonlinear differ-
risk analysis, autocalibration of models, and advanced spatial ential equations (solitons) and unexpectedly disor-
analysis). ganized behaviors (chaos). These nonlinear methods
allow us to study many facets of complexity.
Challenge #: Communication and (5) Development of standard semantics for expressing
Representation of Information on Environmental scientific domain activities.
Systems and Processes
(6) Limitations of mathematics, formal reasoning and
computation (computability) need to be explored and
This challenge focuses on the need to significantly advance
understood. Not all problems have solutions that can
our capabilities to communicate our increased understanding
be computed or modeled (Chaitin, 1998).
of complex environmental systems and processes to a diverse
set of audiences and constituencies. This challenge includes:
Defining the Unique Role and Potential Contribution of the USGS in Environmental Information Science 
(7) Need to develop more appropriate (intelligent) meth- cated on the recognition that a fundamental advancement
ods for organizing complex, multidisciplinary data for in the Bureau’s capabilities to understand, model, and pre-
efficient storage and retrieval. dict complex environmental systems and processes can be
accomplished through a more focused effort to link and
Appendix I provides an initial framework for a long-term apply information science principles and methods, together
environmental information science research agenda for the with the Bureau’s extensive natural science capabilities. The
USGS. A more detailed research agenda would be developed unique set of information-related challenges inherent to the
in close collaboration with the USGS natural science pro- study and understanding of complex environmental systems
grams. Appendix II lists examples of some scientific questions and processes (i.e., multiple levels and types of complexity,
that could be addressed, in the context of specific USGS natu- multidimensional in space and time, multiple types of flux of
ral science investigations, through an interdisciplinary research materials and organisms, difficulties in measurement/observa-
emphasis in environmental information science. tion in situ, etc.) represent an intersection of environmental
science and information science. These are true interdisci-
plinary research challenges, unique to the mission of USGS,
Defining the Unique Role and
which cannot be addressed by the mere application of existing
Potential Contribution of the USGS in computer/information technology.
The USGS is uniquely positioned to make a significant
Environmental Information Science
contribution over the next 25–50 years in this type of inter-
disciplinary environmental information science research.
The development of an interdisciplinary USGS research First and foremost, the natural science research challenges
emphasis in environmental information science is predi- facing the USGS over the next 50 years—­such as the need
for improved predictive
capabilities for natural haz-
Example 1: Modeling the Spread of Invasive Species ards and disasters, modeling
of diminishing ground- and
One of the major long-term science goals identified in the USGS Invasive Species Future surface-water supplies,
Science Direction plan is to improve our capabilities to rapidly assess and predict risks of discovery of potential new
invasive species on native species, ecosystem functions, and resource management sys- energy and mineral resources,
tems. To meet this goal, USGS scientists are developing computer models of the distribu- and preventing the spread of
tion and spread of selected invasive species. Complex, multivariable data sets, including invasive species—­will pro-
remote-sensing data from satellites and a variety of other biological and physical variables vide the underlying research
measured on the ground, are used to create these models. The long-range goal of these context for the environmental
studies is to eventually develop an “ecological forecasting” capability, similar to weather information science research
forecasting, where certain key ecological variables would be tracked constantly in order agenda. Secondly, as noted
to provide information on where and how fast invasive species are moving so that species above, the needed research
invasions can be suppressed before they become unmanageable. must, by definition, be truly
As many as 40 different ecological variables, such as carbon or nitrogen levels in soil interdisciplinary—­pushing
or reflectance values from satellite data, play some factor into the creation of these models. the boundaries of both natural
USGS scientists can apply computer-based statistical analysis on each individual variable and information science. The
to identify those variables that are statistically important. But the complexity of invasive Bureau has a strong existing
species systems and ecological processes calls for the use of combinatorial assessments, multidisciplinary scientific
where all possible variations of variables are considered simultaneously and the most workforce, including natural
accurate models are produced quickly so that scientists can design and refine models in scientists in all major disci-
real time or near real time as new data come in. Because the number of possible models plines and a relatively small
increases exponentially with the number of variables, massive computation is required for cadre of experienced computer
data sets involving more than just a few variables. and information scientists. The
Serial processing algorithms, designed for running on individual personal comput- Bureau can also build on its
ers or workstations, can take more than a month of constant processing to analyze one existing collaborative relation-
data set. Scientists at the USGS Fort Collins Science Center are investigating the use of ships and research partnerships
high-performance computing (using a super computer or Beowulf cluster) to perform the with other Federal agencies,
same invasive species analysis in a matter of minutes. The activity requires computer sci- academic scientists, and private
entists to work closely with the biologists to transform complex existing ecological model industry, all of which have sig-
algorithms from serial processing to parallel processing and to test and adjust the models nificant strengths and resources
on the high-performance computing platform. This technique has important potential to to complement USGS in-house
advance USGS understanding and modeling of other complex systems and phenomena. capabilities. Finally, the USGS
has a significant, long-term