Respondant
2. Briefly describe the scientific questions you are trying to address in your current work, and hope to address in the next 5 years.
What is your vision of the scientific work you would want to accomplish 10 years from now?
3. What data and/or data products, including digital and physical data types, do you need to do your research and will you need in the future?
Does/will this data come from observing systems supported by the NSF, or other agencies? Please choose all that apply
Do you require near real-time data?
Open-Ended Response Open-Ended Response Open-Ended Response NSF DOE NASANOAAUSGSOther (please specify)Yes No
1
Data sharing across institutions via WMS, WFS and WCS technologies
Muti-layered image and graphic displays using web/native client apps accessing distributed Web Mapping servers to view cross discipline datasets.
Desire linkages between other geo-science web based
servers that contain terrestrial image and graphical datasets. NSF DOE NASANOAAUSGS Yes
2
What are the drivers and controls of river migration? I'm interested in the nexus of land surface processes, water resources and climate as they relate to river dynamics.
I application for river migration and flood plain construction that could serve as a predictive model for coastal rivers.
Land surface data- historical data (aerial photos, topographic surveys), land cover information,
surface/geologic information. Climate information- climate model outputs (scaled down to basin size scales), historical climate records. Hydrologic informations-NWIS and
groundwater information, sediment gage information. NSF NASA NOAA No
3
"Sequencing the Fossil Record." What is the precise order of all species-level origination and extinction events in deep time on Earth's oceans? How are these events distributed geographically? How is the clustering of these events related to changes in landscape, ocean configuration and climate, particularly as recorded in the isotopic composition of ancient ocean sediments?
"On-Line Time-Line of Life on Earth" To have replaced the computationally-intensive algorithms, which a few individual PIs now use to sequence thousands of events from the fossil record of hundreds of localities, with a continually updating- reoptimizing community web service that automatically incorporates new information contributed from the whole geobiology community to sequence millions of events from thousands of localities. To have linked this information with global climate models to interpret the course of organic evolution.
Descriptions of fossil-bearing drill cores, quarry faces, and
natural outcrops. NSF DOE USGS No
4
I have recently shifted from physical sciences (space physics) to data management (IARC Data Archive). My previouse work entailed the ELF system at HIGHPASS, statistical analysis of geomagnetic indices and incoherent scatter radar data. I'm filling this out as I have noticed a significant difference in approach between the scientists and the data people.
Future work will depend on future opportunities. I would like to get back into scientific research at some future point.
services I could have really used in the past include:
searching available data by altitude, geomagnetic location, date of observation and instrument orientation (I needed data taken when the radar was pointed along the magnetic
field line). NSF DOE NASANOAAUSGSwhoever has data that I need for whatever studyYes
Do you require data or data products from outside your immediate discipline?
4. Is there a place for products of your own work to be archived and accessed?
Please list the databases where you archive or access data.
What improvements to these resources would facilitate your use of data and tools?
5. What cyberinfrastructure (CI) is important to the conduct of your research?
Are there sufficient tools (software, computational resources, visualization, etc.
tools) to analyze your data? Describe the tools that would advance your scientific work.
CommentYes No Name or describe the fields from which you would want data. Yes No CommentOpen-Ended Response Open-Ended Response Open-Ended Response Open-Ended Response
Yes Satellite, radar and other remote sensing platforms as well as historical datasets that can be displayed via wms technologiesYes UW-SSSEC Web Map Services Space Science and Engineering Center - UW
Madison NASA Langley National Severe Storms
(NSSL) - Norman,OK Unidata High speed com links between wms facilities Web, WMS data sharing
Advanced data Visualiztion tools (VIS-AD, McIDAS)
Yes Climate data and land cover data is outside my discipline.Yes No I'm not sure, but I believe there are several projects in the works for this type of analysis. One is One World Water and the other is being developed by CIDA at USGS.
NARR, NWIS, TNRIS-aerial photography, TWDB sediment gages, USGS sediment gage information, USGS seamless landcover data, USGS dem
The biggest improvement would be to make them accessible from one location and to provide a better description of the data.
Yes Global climate and ocean circulation models for ancient Earth configurations.Yes The Paleobiology Database is a good start. The Chinese Geobiodiversity Database has more promise.Paleobiology Database, Neptune, Zoobank.
Currently the databases store the raw information, not the timelines developed from them. They may deliver the sequencing tools but do not attempt to sequence the data they contain.
Distributed computing and parallel programming.
The limiting factor is the speed of the algorithms that optimize the sequence of events. This is a Non-deterministic Polynomial-time Complete problem.
I needed realtime data for the ELF study, not so much for the other 2Yes Both the incoherent scatter radar study and the geomagnetic indicies study required solar cycle/solar wind data. Using the same data I could have looked for the connection between ionosphere and lower atmospheric conditions. The questions a researcher is able to answer is determined by the data avialable. Cross diciplanary data is vital.Yes Files submitted with paper to Journal of
Geophysical research and uploaded to Archive at the Interenational Arctic Research Center.
The IARC Archive needs a more functional system for entering metadata. Currently we are using Geonetwork, but that program assumes that data entered is a map. Thus it does not have the proper metadata fields to properly describe the data.
Data must be available online, so whatever is done needs to be accessable from a web browser.
For the most part yes. It may be more convienient to use an online tool to get preliminary graphs and/or maps, but I have to write the Mastlab or IDL program for the final graphs anyway.
Do you require near real-time data?
6. What tasks do you currently spend time on that you believe could be automated?
7. What common cyberinfrastructure capabilities are needed across the geosciences? What capabilities are unique to your discipline?
8. Please detail any other comments about the cyberinfrastructure needed for your research.
Open-Ended Response Open-Ended Response Open-Ended Response
Visualization of multi-spectral satellite imagery
Common data visilization environs like WMS to view work from other institutions and associated influences across may areas of study.
Extracting information from published papers that the authors could better enter themselves. Waiting for sequencing algorithms to run on single computers at the limits of their capabilities.
Geology is a historic science, like genetics and astronomy. We explain the present as the outcome of a sequence of ancient events distributed in time and space. The ages and places of these events must be estimated. Our best estimates of the number, sequence and timing of events is continually improving. We should not tolerate a static database of estimated ages. A dynamic model of the history of species on Earth supports better speculations about the future course of environmental change.
One thing needed, that I am not seeing in the computational community is the need to fully describe the instrument, setting, orientation, etc...
describing how the data was origionally taken.
There needs to be required documentation on the background/source of the data so that it can be used correctly. If I had used scanning ISR data rather than, or mixed with, the field aligned data, my results would have been nonsense. Researchers need to know how the data was taken and there needs to be a place for me to assure a future user that I only used field aligned data to obtain my results.
The biggest contribution of cyberinfrastructure is to allow networking. This reduces duplication of effort and allows researchers (and more importantly students who have no funding) to have access to a wide variety of data, thus allowing them to ask/answer more questions and widen their horizons by talking to people in differing diciplines.
While some research is done by asking the question and then taking data and studying the result, a good amount of it is also done by looking at data that already exists and seeing what they can tell you.
5
I'm looking at a wide range of questions involved post-mass extinction recovery, esp. the Lilliput Effect, as well as the changes in biodiversity associated with various abiotic controls.
To undertake more of what I outlined above, but do so with the hope of making temporal, spatial, and taxonomic comparisons in an attempt to tease apart the role of different controls and constraints.
I need a spectrum of data ranging from stratigraphic information about taxonomic ranges, to size data across mass extinction boundaries, to data from various
paleoenvironmental proxies. NSF NOAAUSGS No
6
In nature, waveform singal can be propagated or delivered by the noise, seemlngly noisy, singal or media.
Clear seperation of sinusoidal component and fully stocastic component from the variation of the meteorologicla parameters such as rainfall amount and air temperature and others. I guess the separation might help improving weather forecsts, especially for quatative amount of precipitation.
Observed rainfall amounts in a lengthy time series from all over the world and the outputs from the numerical weather
forecast model. NOAA No
7
Origin of magmas in different environments and relation between petrological evolution of magmas and the behavior of volcanic systems
To incorporate geochemical and petrological data, including spatially resolved data and images into petrological and geochemical interpretations of magmatic systems
Geochemical data from rocks and minerals, geologic maps, digital images, in-situ chemical measurements of solid
materials NSF USGS No
8
My goal is to more accurately forecast rainfall by modeling radar data in three dimensions at high spatial and temporal resolutions.
I would like to have a rainfall model that could be the input to a hydrological model that accurately predicts where flooding will occur.
WSR-88D radar reflectivity values, satellite-derived radar data and data pertaining to cloud structures, ground
measurements of rainfall and runoff to verify model outputs NSF NASANOAAUSGS Yes
9
Enable data interactive publications using standards-based web services. See
https://sites.google.com/site/datainteractivepublications/home /white-paper-on-data-interactive-publications
Implement organizational and technological systems that enable the scientific community to publish their research in online documents that enable the reader to access the data and analysis and display processes that are described in the publication.
My own focus is on real-time environmental data but my objective is to develop systems that make all data AND PROCESSING systems involved in publication available
online NSF NASANOAAUSGSlightning data and data from instruments on commercial aircraftYes
10 Land use change and it's effect on water quality
ground truthing of remotely sensed and model
predicted natural resource conditions. Geographically related time series data NSF NASANOAAUSGS Yes
11
I'm helping build a new Cyberinfrastructure for ocean (and other?) science, under the Ocean Observatories Initiative, and continuing to lead the Marine Metadata Interoperability project. I hope to create solutions and communities that make ocean and environment science research faster, easier, and better.
Even more of the same, perhaps encouraging use of some of the best practices and tools that have been created.
Having the maximum amount of core and contextual data relative to a research topic is the fundamental driver toward better science. The contextual data must be appropriately
presented, but is always noted in the absence. NSF NASANOAAUSGSIndividual resources who are not currently submitting data (quickly, or ever) to any outside repositoryYes
12
Properties of magmas such as temperature, density, viscosity, pressure and temperature of melting, at spreading ridges, islands and island arcs
Establish methods of determining conditions of partial melting in the Earth's mantle beneath volcanoes and relate those to global tectonic processes and mantle source compositions
Compositions of constituent phases (minerals glass) in basaltic rocks, in rocks that form during differentiation of primitive magmas, and in likely mantle source rocks for
those magmas. NSF NASA USGS No
Yes Paleobiology Database; Chronos; More data being entered. Mostly the storage of large amounts of data Yes, I would say in general that there are.
No Yes WMO NCEP and NASA data distribution centers Fast electronic delivery Fast communication for data download NCL GRASS UDIG R-package, Python
Yes Geologic maps, geophysical data sets (seismic, heat flow, gas compostions etc.Yes GEOROC, PetDB
Better data interrogation and interpretation tools.
Improved methods of manipulation of large data sets, dedicated geochemical working environment
for data storage and manipulation Access to data bases
Sophisticated (ie better than excel) data bases and interpretation enviroments for looking at petrological data. Good examples include IOGas, Abel, JMP etc, but none of these are aimed at hard rock geochemistry and are lacking in other ways (and are not free). Also need scripting capability.
Yes geology, hydrology, meteorologyNo My university won't even support my computer running Linux!
NCDC is my primary source I've also used Giovanni to access TRMM data
easily customizable scripts for someone to be able to proces bulk data orders who isn't a computer programmer
I am having trouble finding a software that does a true 3D interpolation of data and has input/output files types that can work with other programs I am using
Yes Yes This is one of the objectives of the work I have in mind A few examples are THREDDS servers at NCAR, NCDC NOMADS, Live Access Servers, Unidata motehrlode, ERDDAP (Environmental Research Division's Data Access Program), etc.
Enhance the server side web processing services so that a wide variety of data analysis and display can be done on the server and included in online publications
Standards-based web services for data access and processing
The tools are available for the most part.
It's just that they now are available for powerful desktop systems or supercomputers and are not readily available for control via more modest mobile devices such as browsers, tablets and smart phones
Yes No not yet
It is why these systems are being built, but it is also the paradigm that the web (the world wide cyberinfrastructure) is marching toward.Yes Atmospherics. And, all science fields support good oceanography.Yes No There are many, depending on the field. None use good semantic practices and vocabularies. Most of them have relatively low standards for data submission and sub-optimal practices.
All internal right now. In future will extend to national databases. Individual data set archiving via netCDF is core.
1) Having really good tools to interact with the resources. (2) Having good baseline vocabularies across a range of science domains. (3) Proper stewardship of those vocabularies. (4) More resources for standardization.
Did I mention OOI Cyberinfrastructure? (Not important to others yet, but soon...) Beyond that, a good semantic infrastructure, and good digital publication infrastructure.
No, no, and no. (1) Really good, solid, tool- supported protocols for working with different 'features' (meaning data model organizational features) in
geospatiotemporal data sets. (2) Really good semantic tools, including repositories, tuned to the casual scientific user but well integrated with the semantic web and linked open data constructs.
Except for measurements of physical properties of molten lavaYes Marine geophysical data, satellite observations of volcanoesYes Journals and data basdes
PetDB (Lamont Doherty Earth Observatory)
Georock Earthchem IODP Repository for mineral data
Presently, data files and manipulation techniques are managed using spreadsheets and personal computers. However, there is no single good application combining rock and mineral data for petrological use.
An image analysis system dedicated to the petrographic microscope and high- resolution analysis and imaging procedures (e.g., electron probe).
Not many unfortunately
More integration of datasets/respositories so that various types of data can be more effectively analyzed in tandem
Frankly, I wish I knew more about what exists and what capabilities it might have to facilitate the types of research questions I'm interested in.
Displaying NETCDF data (unstructured grid format) on grass. Accessing and analyzing mass data.
Secured data sources. Safe communication protected from hackers.
data manipulation in excel
Improved ability to handle and integrate large data sets. Better storage and backup options.
having to name each file separately, having to preprocess the data one at a time to be able to use it in a GIS
Developing international standards for data access services.
Parts of this process are maddeningly routine and time consuming, e.g., routine nit-picky formatting.
Across the sciences, standards-based data access and processing services are needed. In the atmospheric science, especially meteorology, there is more emphasis on real-time data.
If we are to transform the scientific publication process by implementing systems for "data interactive publications," it will be necessary to engage some forward-thinking organizations in the scientific publications industry.
Vocabulary construction and management. Discovery of ocean assets like visualizations. Discovery of ocean data.
Almost all cyberinfrastructure capabilities are best if available in common across all geosciences. I would emphasize most visualizations as being particularly cross-cutting. There are unique flavors of capability that are domain-specific (gene- folding/matching, taxonomic identification, sonar analysis, etc.), and corresponding visualizations, but these are not CI capabilities, they are domain science capabilities.
It has to be interoperable. It has to be well supported. It has to include high-quality user tools to access the features.
Data input into different programs (mineral structural formulae, temperature evaluation programs, etc.) must be separately entered into each program.
Better Earth imaging, especially higher 3-D resolution of landforms with uniform contrast and, in many places, no cloud cover. Better ways to scale and locate objects. Google Earth is good, but not ideal. A similar procedure for underwater and marine geophysical images, with ways to suture them to on-land images, show sample locations, etc.
Seems to me that all of this is on the way, but as usual with computer developments, the process is very chaotic and irregular.
13
My primary question is to explore the evolution of development, using data from the fossil record and from Recent taxa. Phylogenetic systematics is a major tool, as is computed tomography, magnetic resonance imaging, synchrotron CT, and other non-destuctive volumetric imaging techniques that allow enhanced data mining from scientific specimens. Use of these tools leads to a second scientific question that my research addresses involving design for cyberinfrastructure and data management.
A deeper understanding of the role of paleontology in evolution; and a more sophisticated infrastructure for the growing volumes of digital information that are advance my primary question.
Voxel based datasets on important fossils and Recent specimens are the basis of my research; continued improvement in discrimination between soft tissues and between fossils and the matrix containing them are future goals for all types of scanners. Data from a greater diversity of species, and a broader sample of variability in populations and in the ontogeny of individuals is of
increasing importance to future research. NSF No
14
Detection and monitoring of groundwater resources in arid regions. Capacity building in 3rd world countries for remote sensing data analysis and applications.
See above. Making remote sensing data and information ubiquitous and easier to use at the Google-Earth level.
(What is a 'physical data type'?). Remote sensing data:
Visible-near IR; interferometric radar- especially processed to time series of change; archives running back decades;
New remote sensing data: subsurface sensing. NASA USGSForeign Space agenciesNo
15
Surface-groundwater interactions at the watershed scale, along with inorganic and organic solute fluxes.
Synthesize these insights at the regional, national, and inter- national scales
Remote sensing products, hydroclimate, geochemical
weathering, land cover, geologic formations, DEMs NSF NASA USGS Yes
16
Primarily focussed on providing access to data in a single discipline. Also worrying about integration of data sets across disciplines.
Seamless integration of data sources, products, intellectual output. A system where scientists spend time doing scientific research and not hunting and gathering for data.
Primarily seismological data in easy to use formats. Access to models (velocity models) as well as synthetic seismograms is key. Access to clean datasets is also
importnat. NSF USGS No
17
The exchange of momentum, energy, and moisture between the ocean and the atmospheric boundary-layer.
I want to understand how wind, waves, and currents intereact to modify many processes and how these processes combine to influence climate. I am also curious if geological disturbances can be seen in these observations
Satellite estimates of stress, 10meter air temperature and humidity, sea surface temperature, and spectral wave
characteristics, currents NSF NASA NOAA No
18
What will happen to tropical and subtropical coral reefs, coastlines, watersheds, and the people they support as climate change proceeds.
Integrated, flexible scenario-testing models of these systems, linked to global forecasting systems, to support decision- making.
Spatially-explicit information of many types, including the results of field and environmental modelling studies at all
scales. NSF DOE NASANOAAUSGSother agenicies around the worldYes
19 aviation weather better aviation weather forecasts
aircraft and pilot weather reports and numerical weather
forecast model data NOAA No
20
Simulating seismic sequences. Natural hazards release probabilities.
Understanding seismicity release in certain cases, may be possible.
Digital data about location and ocurrency of seismicity.
Analisis of seismograms forms and sequences. SEISAN
program. NOAAUSGSIAG, IGN (both from Spain).Yes
21
Linkages between extreme environmental events, climatic anomalies, and socio-economic problems. Also doing research in aviation meteorology, so robust atmospheric and impacts data sets are a necessity.
Linking high-resolution atmospheric databases with impacts and effects information in order to create automated decision- assistance tools for decision-makers in different professions (e.g., aviation, emergency management, policy planning).
Gridded model analysis and prediction data, archived and real-time satellite and radar data. Standardized formats and data types are important for portability to different computing environments (we've made a lot of progress in
the last 15 years!). DOE NASANOAAUSGSDoD (unclassified)Yes
The ability to quickly generate data on th latest paleontological discoveries will accelerate this research.Yes As a paleontologist, my primary data are on fossils; however more data on Recent species over their entire life histories will augment and extend what we can extract from fossils.Yes www.DigiMorph.org Turning DigiMorph into a communal repository (or
developing an independent repository) for the growing volumes of voxel data is a critical need.
Also hardware/software improvements to speed scanning, data processing, archiving, and for reducing costs is a critical future goal.
Enhanced scanning instrumentation;
communal storage infrastructure; advanced visualization technologies; accelerated training methods; advancement of IP policies governing these data.
Faster scanners; scanners that fill gaps in object sizes that can be scanned; currently there is neither a voxel repository or a community dialog on establishing such a repository; advancing visualization tools, particularly for quantitative 3D analyses on voxel datasets.
No Yes NASA and USGS DAACs, ASF
Standard, easy to use formats! CEOS is hard to use. Need a description of the data.
Fast web access and download of data.
Catalogs. Meta data.
Barely. Problems with 'standards'. Big need for tools to process and analyze InSAR data- too many formats.
Yes No
NWT LTER, CZO, NSIDC, NASA EROS,
CUAHSI-HIS Data are not interoperable.
The ability to query and return specific data types collected in the field.
Near real-time hydro-climate data with sufficient metadata. The lack of such information is the largest impediment to advances.
Yes Yes IRIS DMC and data centers of the FDSN Common access methods, Federated Data Centers
Big question. Most important would be middleware that allows integration of data across the disciplines.
No, some tools like MatLab are a step in the right direction. Visualization tools are presently rather week.
Near real time would be great.Yes timing, location, and strength of geological motionsYes We archive and share with NOAA and NASANASA PO.DAAC
convenient access to data outside my wide range of activities
Fast serving of data. Appropriate formatting and reference material for the data. Read tools are nice, but less important to me
sometimesYes Hydrodynamic models and empirical water movement readings, nutrient, physical water properties, solar influx, productivity estimators,fishery and land-use information, socio-economic information.No only myriads of disparate sources each with major learning curves and admission protocols ReefBase, FishBase, Data Navigator South Florida,
Data Navigator St. Croix, Coris, Ocean Observing System GOM Portal, Reefs at Risk GIS at WRI, many others
Consolidation and/or seamless integration. Hosting of improved data interfaces and online simulation systems.
Web and linked in data systems. Large capacity servers with parallel simulation support.
No. Cloud based data assembly, simulation, and visualization tools.
No No
NWS Aviation weather Center NWS National Centers for Environmental Prediction NOAA National Operational Model Archive and
Distribution System Larger archive in NOMADS
Yes Tectonic and volcanic data. Geophysical and estructural geology data also.Yes SEISAN, USGS, IGN, IAG,
Uniformity of data order and presentation should
be very grateful. No. At least of easy access.
Yes Aviation operations data (e.g., airport closures due to weather, airline impacts due to weather), socio-economic data (e.g., food and energy security, population demographics).Yes We have local servers where we archive and access
data, but I also use a number of web-based sources such as NCDC, NCEP, and UCAR (e.g., Locust MMM).
Accessibility to more sources of archived satellite data from different platforms (e.g., NASA, NOAA). Easier user interfaces with NCDC data would be helpful, and more archived local data instead of selected regions from the Locust MMM site. Access to "non-standard" network archived
data would also be helpful. Fast and efficient access and data transfer.
Visualization tools have advanced enormously in the last 20 years. I'd like to see similar advances in user-interfaces and capabilities such as 3D animations, etc.
Data management, archiving, visualization, and analysis;
descriptions of new species; training.
Generally we lack the sorts of data archives that biologists have embodied in GenBank. We generate expensive data that has a broad audience, but rarely is our data used by those who did not generated it in the first place.
A more robust community attitude about managing and releasing data for verification and re-purposing will offer a far greater return on every dollar invested in data generation.
Figuring out poorly documented formats. Registering data into map coordinates (still!). Creating time series of InSAR data.
Common: easy geo-coding and ortho-rectification of remote sensing data (all bands, full resolution).
Data costs are a problem- especially for foreign remote sensing systems.
Downloading and formating hydroclimate data.
Clearning house/central data portals for specific types of data where the data have been QA/QCed, have appropriate metadata, and can be easily formatted, eg time series of discharge from ten sites with similar units all in one table.
Data harvesting from multiple centers.
Loosely coupled web services that produce an understandable output to people outside a specific domain.
We need infrastructure that does not complicate usability such as portals that require passwords.
Coordinated services and systems from NSF would be beneficial rather than having to create our own wheels every time.
Data access with good information about the strengths as weaknesses of the data
Assembling the data I need. Finding a way to easily submit and maintain data sets.
All environmental data should be easily accessible to all users, in a system that supports spatially- explict user-initiated socio-bio-physical simulations, statistical analysis and exploratory visualization.
Should tie together all Ocean Observing System, NEON, and LTER data systems for a start.
Searching and recording data.
Searching for "unique" data types. Google is a wonderful tool, but it would be nice to have some type of central location to search for "all things atmospheric" in terms of data, especially archived data.
Nothing beyond what I've already described. Easier and more standardized is always needed and appreciated.
22
Deep mantle mineralogy, Ultra-high pressure metamorphism and petrology, envoronmental and engineering mineralogy
The scientific work of my interests should contain interdisciplinary approaches and provide larger explanation to the society.
easy access to publications through on-line (now we are restricted by the Institutional subscribtion). Scientific literature should not be sold by any other organizations through on-line - it must be FREE for scientists. We need more database that would include list of chemical analyses and experimental data performed by different laboratories -
access for scientists to such databases must be also FREE. NSF DOE NASA USGS Yes
23
How do convergent margin magmas form, and how does this
lead to the generation of continental crust? Answer the above questions
Need to be able to easily access and manipulate
geochemical and isotopic data for igneous rocks produced at
convergent plate margins. NSF No
24 Planetary formation and transformation processes
Better understanding of planet formation and differentiation through study of volcanic systems on Earth and through study of planetary materials.
Acquisition of instrumentation for generating high-precise elemental abundance and isotopic data to resolve chronological and tracing problems to achieve our scientific
goals. NSF NASA No
25
What are the main controls of nucleation? How does nanoparticle surface chemistry vary from bulk minerals?
What is the mechanism of silicate dissolution? Realistic molecular simulations of water-rock reactions. Simulation results, experimental rate data, spectral results NSF DOE USGS No
26
How and does continental crust respond to the forces of compression and extension during mountain building and collapse? How fast do minerals in metamorphic rocks grow? What is the record of mountain building and collapse recorded in metamorphic minerals?
Determination of high precision rates for strain, heating, and cooling in deformed mid to lower crustal rocks.
Better methods for high resolution spatial sampling of rocks and minerals and better techniques for analyzing isotope ratios in low volume samples. More robust models for modeling the stability of complex mineral phases at high T
and P. NSF No
27 Critical Zone processes, biogeochemistry
Integration of environmental data sets and models at the landscape scale (i.e. 100km2) to predict near-real time processes
Hydrologic, water quality from sensors, weather from
climate sensors, remote sensing (i.e.lidar..) NSF DOE NOAAUSGS USFS Yes
28
Magnesium isotopic composition of the lower crust;
principles governing the distribution of Mg isotopes among different reservoirs
Understand the distribution of Mg isotopes in major reservoirs, behaviors of Mg isotopes during different geological processes and applications of Mg isotopes in
solving geological problems isotopic data of all kinds of materials NSF No
29
testing a biotic-abiotic hypothesis about a particular landform
More modeling and statistical work understanding landscape interactions
Old maps; a modest quantity (GB at most) of observational records; and a larger quantity of model run results for doing
ensemble analysis. Possibly using NCALM LiDAR maps.No
30
modeling to establish current and historic trends in transport and fate of agricultural and airborne toxic compounds
to establish minimum wetland/marshland recovery requirements for natural attenuation following disturbances of watershed areas for development and cleanup
first on the list: historic lithography for agricultural lands, including soil surveys, aerial photos, etc. as well as newer
sattelite data - as much as we can get ! NSF NASANOAAUSGS DOA, EPA No
Yes Materials science, environmetal mineralogy, inorganic chemistryNo I place them on my webpage as attached pdf fileswww.ucr.edu It is better to have a generilized cyberinfrastructure
I need to learn: (1) review papers for last 1-5 years related to my disciplines; (2) I need to have data on experiments at high PT conditions to get access through on-line.
Mineral structures - visulaisation wilmilat to software "crystal structure"; Simlified software allowing to predict mineral phase transformations at certain depth, for certain bulk chemistry
Yes geophysical data on the structure of arcs and continental crust and results of geodynamic modeling.Yes EarthChem, GeoRock, PetDBEarthChem, GeoRock, PetDB
Better filtered data for arc igneous rocks, including tools for normalizing geochemical and isotopic data to commonly accepted values for standards;
better integration of geochemical/isotopic data and
geophysical data and geodynamic models EarthChem, GeoRock, PetDB
No, need better tools for displaying spatial and compositional data and better statistical tools for analyzing multivariate
geochemical data
No None immediately, but there are some cases where we may need such data - from the remote sensing community, for example.No This is something we are talking about, and it would be very nice to haveMainly journal databases I am not sure I am not sure Yes
Yes Chemistry, biochemistry, molecular biology, solid-state physics, soil scienceNo
Need expanded capability to upload and store results from various computational chemistry programs. Software to access and visualize a wide variety of output from one portal.
High-performance computing and optimized software.
Mostly, but they are diverse and many are commercial which limits access.
Yes Thermodynamics Geophysics Physics ChemistryYes Limited data archiving is available for my research in New Zealand PETLAB GNS Science ARC GIS [personal
databases]
Greater size [more participants] Greater spatial extent [world wide] Greater speed [limited by web
speeds] Web-based databases. Yes, in general.
Near real time needed in next 5 yearsYes Remote sensing, human population and landuse changeYes
CZO vis San Diego super computer, LTER network
easier ways to qa/qc data from sensors before they are posted on our web sites
I am more interested in obtaining flat files with good mete data that standard visualization data
No No
Yes Botany.Yes One of the nature reserves I work in manages (and requires use of) a depository for publications and data gathered there.
On my computers (backed up on department
server). Standardized department database? Backups. GPS. Cheap CPUs.
I'm a programmer, so I write tools from scratch if I have to. SciPy saves me a lot of time.
of course, it would be niceYes flora and fauna survey data, water table data, well monitoring dataNo various environmental impact studiesno comment no comment
not sufficiently aware of what is possibly
available. we work with whatever we can find usually create our own
Search on-line literature and software showing how to predict phase transformation for specific bulk chemistry
Superarchives on prediction of the phase transformation during deep subduction and matle
convection Not righ now
Not sure
A. Tools for showing locations of data, profiles, and models. B. Tools for filtering and plotting geochemical and isotopic data.
Needs to become easier for beginners to begin to use data libraries.
None None None
Opening and translating files into various formats.
Large extensive databases that are readily accessed.
qa/qc of raw data meta data standards, standards for flat files
More focus on site based research needs (i.e.getting field measurements to the computer); less on visualization software and software that does what matlab and other programs can already do well.
Comparing maps in a lot of formats (several datums, and paper, scans of paper, and various file formats). There probably are automating tools, I need to learn them.
Interoperable maps; if a common finite-element modeling scheme is imaginable, that would be great. I worry that the idea of a completely reproducible digital workflow hasn't caught on, or works only in a 'walled garden' of proprietary tools (more common in biomed, I think).
integrating various data sources on a timeline basis (or correlating more than one sample set when the sampling data
are not concurrently dated no comment no comment
31
My current research work is entitled :Spatio-temporal dynamic and integrated water resources management in the Nyong river basin, Cameroon. This research will investigate the physical, chemical and environmental reasons behind the decisions to mitigate the impact of climate change, eutrophication of Nyong River as well as the factors that influence their current functional status. The work will be undertaken in Mbalmayo station with some examples elsewhere.
The outcome will be a better understanding of what contributes to the effective management of the eutrophic and dynamic in the Nyong River basin and will lead to recommendations for more effective and sustainable planning and management of this wetland.
I will need Data in meteorology, hydrology, geochemistry
and climate change. NSF Yes
32
Crystal-chemistry of the glaucophane-tremolite and glaucophane-pargasite joins. Pressure-temperature limits of stability of smectite at high-grade metamorphic conditions.
Trace element incorporation in diamond. Use of autocorrelation analysis for refining the shape of mineral miscibility gaps.
Improve our understanding of the depths and mechanics of crustal rock cycling to the mantle.
Crystallographic data. X-ray diffraction patterns and structure refinement methods. Infrared spectra. Mossbauer
data. NSF DOE USGS No
33
Analyze and simulate the environmental conditions near the earth's surface (atmosphere below a kilometer and surface conditions such as snow cover, soil and vegetative temperature and moisture) at very high spatial (order km) and temporal (order 5-60 minutes) resolution.
Provide capabilities for scientists, forecasters, and the public to understand environmental conditions near the earth's surface that affect public safety and economic well being of the country
Unrestricted access to weather and environmental
observations from many different sources. NSF DOE NASANOAAUSGS Yes
34
Modeling volcanic hazard, role of cyber infrastructure in volcanology, shallow conduit processes, development and rates of volcanism in monogenetic volcanic fields
achieve parsimony in complex volcanic hazard models, develop statistical bases for evaluation of long term and short term hazards, integrating geophysical data
Many! Radiometric age determinations are a data DISASTER in the US, with too little dating of young volcanic rocks being done, database of geological units on active volcanoes is a DISASTER in the US. Just try to find information about the surface area, volumes, or character of recently erupted products.
NSF NASANOAAUSGS No
35
Formation of terrestrial planets Understanding the upper mantle of the Earth to constrain geodynamics
Hopefully, keep publishing useful papers to the scientific community
Geochemical data that can be handled with Excel mostly.
Some high resolution mapping of rock samples or minerals
that requires image analysis and more computer memory. NSF NASA No
36
Currently, my dissertation research comprises a detailed metamorphic, structural, geochronologic and tectonic study of the evolution of the St. Cyr area, a poly-deformed and metamorphosed, high-pressure terrane within the Canadian Cordillera in Yukon, Canada.
My research aims to improve our understanding of (1) the metamorphic evolution and exhumation paths of high-pressure and ultra-high pressure rocks formed during subduction, (2) processes related to the exhumation of deeply subducted crustal material, (3) accretionary and post-accretionary regional deformation processes, and (4) the Mid- Paleozoic to Early Mesozoic tectonic evolution of the American Cordillera.
Data products that I use include: Adobe Photoshop, Illustrator, Acrobat Pro, Microsoft Word, PowerPoint, Excell, Image J, Allmendinger's Stereonet, Perplex, Google Earth, ArcGIS, Isoplot and Squid Data that I use include:
field maps, digital maps, field photos and
photomicrographs, structural measurements, geochronologic
datasets, geochemical datasets, SEM/EBSD/EMP datasets. The Yukon Geologic Survey and the Canadian Geologic SurveyNo
37
I am trying to understand the Phanerozoic evolution of Earth's surface environment from both biological and physical environmental perspectives, with special emphases on the interactions between the two. To do this, I basically integrate large datasets on the spatiotemporal data on rocks and fossils.
I want to be able to easily access and analyze our rapidly growing body of knowledge on the properties of Earth in a temporally and spatially explicit fashion.
Large volumes of data that are well constrained in space and
precisely located in time. NSF DOE NASANOAAUSGSstate geological surveys, private industryNo
Yes meteorology and geochemistry.No I access data from wed, science direct and agora.
I need digital like arcgis 9.3 and access to spatial data on Cameroon's river hydrology.
Cyberinfrastructure is important for data acquisition, storage, visualization and management.
Not at all, software and computational resources for hydrology and climate change modeling are lacking.
Yes Oceanography for hydrothermal fluid compositionsNo My work can be recorded/archived in journal articles MSA crystal structure database Geochemical Earth Reservoir Model (GERM)
Knowing what resources are available and whether
or not they are reliable. FTP Internet via conventional browsers
Tools are available but learning how to use them correctly is usually the limiting step.
Yes environmental conditions such as vegetative moisture and temperatureYes Home grown mysql databases with disk storage systems purchased from research grants
Maintenance costs for disk storage in terms of replacing 100s of terabytes of disk space every few
years 24/7 networking and raided disk storage
We have many of the tools we need but licensing of commercial software (Matlab and IDL) is an issue. Improved data mining tools and tools for managing metadata.
Yes meteorological data - but easily available through NOAA, geophysical data available through USGS etc. (not always easily available)Yes VHub.org, USF library system VHub.org, USF library system, Smithsonian
Holocene volcano database continued development of VHub VHub.org
No - visualization with tools like EarthVision is great but costly, OPENDX may be improving hthis, GMT is great and can use community support for improvements.
No No Anything better than microsoft products!
No No Network access
Adobe Photoshop, Illustrator, Acrobat Pro, Microsoft Word, PowerPoint, Excell, Image J, Allmendinger's Stereonet, Perplex, Google Earth, ArcGIS, Isoplot and Squid
Yes Geochemistry, geophysics, mineralogy/petrologyYes Paleobiology Database Macrostrat Integration with other data resources.
Fast and efficient data exploration and discovery, pre-analysis.
Once I have found and accessed the data, I can deal with them using my own programming and software development capabilities. Discovery and getting the data is the biggest challenge.
Modeling of hydrological data.
Capabilities of cyberinfrastructure for data acquisition and management.
I will also need cyberinfrastructure data integration extrapolation and exchange data with peer researchers.
Data file conversion, so the same data can be used by different programs. There is often a problem with file compatibility when one program produces a file that is presumably compatible with another program (often not the case).
The concept of the Wikipedia has caught on so well that it would be interesting to have a similar feature for all sorts of geoscience data, but with close supervision to keep the data accurate. Not sure there is any capabilities unique to petrology/geochemistry.
Considerable effort is required to collaborate with weather networks owned and operated by dozens of agencies, educational institutions, and commercial firms.
We are investigating shifting much of our more operational research and development research to cloud type computing. We see a distinct shift coming from internal research university computing environment to cloud computing
improved access to topographic data, improved methods for interrogation of geological map data
My opinion is that cyberinfrastructure tools for hazard assessments are very specific
None I'm not sure
Finding data and rapidly understanding what they are, how they were assembled, and what they can be used for.
Tools to make data discovery and data relationships very explicit and easy to interact with.
38
What is the climate pattern of the Middle East (Northern Fertile Crescent in particular) over the past 30 years. How has anthropogenic activity (esp. irrigation farming) modified the local climate?
Use remote sensor data to explore the various biophysical processes around the earth.
Landsat, other multispectral and hyperspectral data with
moderate temporal resolution. NASA NOAA No
39
Research with mesoscale atmospheric models - Data assimilation (3DVAR and 4DVAR)
very high resolution topography and albedo data (monthly data) available for very high resolution mesoscale model processing. To have satellite date wth higher vertical space resolution
polar orbiting satellite spectral radiance data with very high space resolution (NPOES data) - radar data over south
america NASANOAAUSGS Yes
40
What are the metrics that will tell us how well ocean models are working to solve specific environmental and social problems in specific regions? How well do existing models fare when evaluated by these metrics? What kind of advancements are required to most rapidly improve the skill of ocean models working (basic physics research, numerical horsepower, improved data assimilation, etc).
The same as now. We will always be seeking to improve our models of the environment in the most effective way possible.
Output from numerical weather and ocean models, remote sensing data, insitu data (profilers, drifters, time series measurements, point measurements), high resolution
topography/bathymetric data (e.g. DEM, LIDAR). NSF NASANOAAUSGSNAVYYes
41
oxygenation of the Earth, controls on sedimentary S-isotope record, evolution of complex life
develop a better biochemical and genome-based understanding of the global biogeochemical cycles and the variations of these cycles in time
annotated genome sequences, isotopic measurements,
chemical measurements probably not from observing systemsNo
42
Refining our knowledge of past plate motions, processes involved in mountain building, and characterization of the
geomagnetic field. I'll be long retired.
Databases of geomagnetic, rock magnetic and
paleomagnetic results. NSF No
43
Controls on body size evolution, extinction selectivity, mass extinctions, and biotic recovery.
Comparative framework for understanding controls on macroevolutionary pattern.
Global data on fossil sizes, occurrences, and ages. Isotope geochemical data. Carbonate petrographic data. Data from geochemical models (box models, models of intermediate
complexity, GCMs). NSF NASA No
No No collaborative storage facilities
The single biggest drawback is having to store data locally. This is a disadvantage because the process of download, extract, and preprocessing consumes a large amount of time. If there were a way to access data remotely and store derivatives of the data locally, it would really help.
No Yes only for research pourposepersonal - pc-compatible disk files LDM/GEMPAK
radar data processing and visualization - software more compatible under linux environment
Yes Weather data, water quality data, ocean and seafloor habitat dataYes We make most of our model output available on a THREDDS Data Server, but there is no real plan for long-term archiving UNIDATA IDD (realtime met data)
http://www.unidata.ucar.edu/software/idd/
http://www.unidata.ucar.edu/data/ NOAA/NODC (archived ocean data):
http://www.nodc.noaa.gov/General/getdata.html NOAA/NGDC Geodas (bathymetry soundings):
http://www.ngdc.noaa.gov/mgg/geodas/geodas.htm l NOAA/NOS (historical met model data) http://nomads.ncdc.noaa.gov/ USGS (realtime and historical streamflow data)
http://waterservices.usgs.gov/ UCSD: (realtime and historical ocean surface current data) http://hfrnet.ucsd.edu:8080/thredds NOAA/PFEG:
(blended sea surface temperature)
http://thredds1.pfeg.noaa.gov/thredds/dodsC/satellit e/GR/ssta/1day AVISO (remotely sensed sea surface height data)
http://www.aviso.oceanobs.com and many more....
Building middleware capability (semantic mediation, web services layers, common data models) that would help link all these different databases so that common search, processing and access methods could be used.
From CI, we need standards that describe structured grid, unstructured grid, and adaptive grid models in a common way.
Progress is being made (CF conventions, OGC standards) but we have a long way to go. We need services that provide these data that are asynchronous, and perform scalable
"server-side" functions, or remote workflow execution due to the massive size of the model datasets.
We need toolsets that work in the common high-level languages used by scientists and developers (currently Python, R, Matlab, IDL) as well as the lower-level languages (C, Fortran, Java).
Yes molecular microbiology, stable isotope geochemistry, genomics and proteomicsYes scientific journals, my laboratoryGenbank
my use of data and tools is primarily restricted by the available funding
computers, the INternet, in the future, computer clusters to process large amounts of genomic/transcriptomic information yes
Yes tomographic images, deep- and shallow-mantle seismic velocitiesYes GPMDB (no longer maintained), Magic
Magic is very complex and requires much time for data entry. As a result, it is not (yet) optimally functioning.
GMAP and GPLATES are probably my most valuable software programs.
Yes Geochemistry, geochemical and climate modeling.Yes Dryad, Paleobiology Database
download, extraction, and preprocessing of data collaborative storage
development of more observational data analysis - and model forecast products analysis tools
data from the areas of
meteorology/oceanography/chemistry/biology and others' available on one common structure
Finding data, trying to determine conventions (units, time, grid topology, etc), computing derived coordinates (e.g. z positions in surface-following layer models), building tools to access web-services in my preferred environment (Matlab), trying to figure out what workflows my colleagues use for similar problems.
I think common data models, semantic mediation, scalable web services, documented workflows and having tools that operate in the analysis environments/languages that scientists are using are all generic across the geosciences.
N/ANot me, but my graduate students manually position and reposition paleomagnetic samples in measurement positions inside a cryogenic magnetometer. This can (and has been
elsewhere) be automated. I am not familiar with this luxury.
44
I am interested in understanding the role of volatiles in generating seismic and infrasound signals at volcanoes;
understanding the timescales of magmatic process using seismic, GPS, gravity, etc.; and constraining the mechanisms that drive tectonic and volcanic earthquake swarms.
I would like to be able to have the capability to quickly and easily determine a unique source for seismic tremor and other low-frequency seismic data. I think this offers the best chance of forecasting eruptions. All of this work requires numerical modeling. As computing systems advance, more sophisticated modeling will be possible. But models must be constrained by data, so instrumentation must also improve.
I primarily need seismic and infrasound data and high-
sample-rate gas emission data. NSF NASA USGS No
45
1）如何认知和对复杂的地球（城市）系统过程建模
？ 2）设计和实现地球系统模拟引擎
面向气候变化问题，探讨实现新一代数字地球（城市
）系统模拟网络的理论，方法和技术。 NSF NASANOAAUSGS Yes
46
Will Earth be ready for the magnetic pole shift which is scheduled to coincide cyclically with the coming ice-age underway to climax in 989 years by the the years 2800 to 3000?
To show the true planetary motions as outlined in my model based on the true movements of our star the sun over its 25,000 to 26,000 year orbital path on the inner hub of our galaxy, dictating the cycles of ice-ages, hot spells, population explosions ,extinction of species and humans on a cyclical basis.
I need a totally revised /new model of planetary motions with the sun star moving in spiral circles on the inner hub of our galaxy with the planets crossing that orbit at right angles at all times, showing the gradual change of cyclical long term climate rhythmical forecasts based on this discovery of true planetary motions. I need computerized doumentation/illustrations that will best depict this model entailing extremely long term time frames of long term climatic changes vital to mankind's preparation and survival over millennia.
NSF NASA No
47 Better constraints on sources of long period volcanic signals high resolution, broadband seismic data NSF USGS Yes
48
What controls the initiation, distribution, and intensity of precipitation in mountainous areas How predictable is mountain weather - do topographic and land-surface contrasts enhance predictability, or does larger-scale flow uncertainty place limits on forecast skill.
Science at the speed of thought, with increased integration of atmospheric and geophysical data.
Numerical analyses and simulations, satellite, radar, in situ surface and upper-air data, aircraft data. In the future, these datasets will increase in resolution, which will likely result
in the need for access to peta-scale storage. NSF DOE NASA NOAA Yes
49
Experimental study trace elements distribution between different phases, and the diffusion of trace elements minerals to understand the geotectonic settings and geothermal history of the granitic rocks.
Explore the trace elments and accessory mineral tools to understand the geotectonic settings and geothermal history of the natural rocks.
I need to collect ICP-MS, EMPA, and ion probe data for the
chemical composition information NSF Yes
50
How does the evolution of sandy channel beds relate to the flux of bed material? How do records of Earth's past surfaces reflect variability in the constructive processes?
How are mechanical differences between river and submarine density current sediment transport manifest in the strata and landscapes they create? How do biota (incl.
humans) interact with their physical environment and specifically gain evolutionary value?
1) Create a baseline methodology for standard collection of bed-load fluxes in sandy river with acoustic surrogate technologies. 2) Produce a environmental phase-space relation between submarine density current structures and their associated bed forms. 3) Elucidate the habitats of fluvial benthic fishes and their evolutionary niches.
Topography, Bathymetry, Flow velocity, Sediment flux &
characteristics, Stratigraphic characteristics and ages, Climatic conditions (Temp, Precip, timing, variability, &
derived hydrologic conditions (runoff, discharge, stage), Biotic characteristics, movement, growth & reproductive
condition NSF DOE NASANOAAUSGSUSACE, Other DOI agencies: FWS, BOR, etc.Yes
51
Sedimentary shallow aquifer chemical weathering of arsenic in Asia, and hillslope weathering and soil production rates-- what rates do hillslopes geochemically weather? Basically, where most chemical mass loss is occurring in the subsurface to produce the shallow groundwater and soils we have.
I'd like to be able to tell how chemical weathering occurs in transient landscapes. We have ideas about chemical weathering in steady state conditions, but really no idea how geochemistry is linked with tectonics in dynamic settings.
I'd like the community to be better with relational databases and interlinking data. I'm thinking of CSDMS, Earth Chem, and Georef, which are really helpful, and perhaps expanding with a more Google, readily available interface (not that I want to make everything into Google). One platform, though, would be much easier to navigate, make use of,
contribute to, and manage. NSF No
In the future, I hope that we have the ability to model these data in near-real time. Until then, real-time data aren't necessary.No Yes Yes. The IRIS DMC handles seismic and infrasound data. VHub can manage other kinds of volcanological data (gas emission)IRIS DMC VHub Maybe IRIS DMC could be expanded to maintain
more data types?
Apart from the databases, I need clusters for modeling.
I could always use more processors to make more models faster.
Yes geology, astronomy, astro-physics, anthropologyYes World Science Data Base carbon dating,tree-bark dating, ice-splice dating
documentation of solar cycles as relative to long term climatic manifestations
No, my model can be perfected to accurately describe the cyclical progression of the cycles that punctuate the planetary cycles that affect long term climate on Earth and possibly other planets in the galaxy.
Possible applicationsYes Yes Passcal
Real-time weather and climate observations are integral to my research and teaching program.Yes Hydrology (water, snow, ice, land-surface processes), social sciences/geography (GIS)Yes This is currently in its nascent stages Most of the databases we use are housed at the
National Center for Atmospheric Research or the National Climatic Data Center.
Speed and ease of access. We currently download much of this data, when fast remote access could be more efficient. Documentation, documentation, documentation...
Everything. We require computer cycles for model simulations and data mining, large storage systems for databases, and network speed for accessing data in real time.
No. There remain barriers to analysis. It is time consuming to integrate disparate datasets, software is good at one thing (e.g., visualization), but bad at another (e.g., statistical analysis), etc.
No Yes ICP-MS EMPA FTIR, Ion Probe,Labview Updated software High temperature furnaces (>1600ºC)
No. we need to connect the controller with the controller, and the process need some software and hardware support
In some casesYes Fisheries ecology Climatology/Paleoclimatology Oceanography Limnology PaleontologyNo Not really sureHave not attempted to archive data. N/A N/A
More or less. I have never addressed a problem in a way that required a supercomputing answer (so I have not done that) and have always created code to fill software/analytical gaps.
I don't require itNo No Only through academic journalsMostly http://earthref.org/cgi-bin/er-s0-links.cgi
We should all be looking at each other's data. In volcanology, integration is critical. It would be beneficial if there were more tools for doing this I suppose, but I think they will have to be developed for specific applications and then shared.
computing climate data lor extremely long term time spans
My discovery can now be a milestone in the ability of mankind to determine long term climatic changes from time immemorial to infinity.
documentation of long term solar cycles as relative to long term climatic manifestations
database building
Writing code to alter the format of datasets so they can be analyzed by differing software packages.
Unique to my discipline is the extensive use of real- time data analysis and visualization. The Unidata program enables much of this.
1 atm furnaces. Ours are kindly old, some new programed furnace could save us a lot time to do the programming and replacing the dead heating elements
Our lab need great high pressure-piston apparatus.
and great analysis equipment, such us Ion probe.
None come to mind.
It would be really great to have a single repository that could be linked to any digital object identifier- i.e. datasets published in any journal could be accessed in a single location. Although we scarcely have a large enough community to duplicate eachother's work, it would be very worhtwhile to have a single resource where datasets could be accessed and analysis tools shared-
I'm all for it. Thanks to all those that have put effort into this.
It'd be great to have something like google earth, but, if all the geology data could be there, too.
That'd be an amazing contribution to a lot of users.
52
Develop a better understanding of the physics of geomorphic processes. Develop, test, and refine numerical models of landscape evolution and related phenomena.
Achieve an substantially improved level of quantitative understanding of terrestrial landscape evolution, including increasing demonstrated accuracy of theory and models and
an increasing number of case studies for testing such models. Digital elevation data. Hydrologic data. Sediment data. NSF NASA USGS No
53
I'm using tree-rings to reconstruct streamflows. The main scientific question is what are the different trees responding to in my region and how large and how strong is that synoptic effect. In the future I will be assessing land use impacts on fish habitat and implementing and monitoring land use practices designed to improve in-stream habitat.
Such work addresses the manner in which streams adapt to changes in management practices and how can we quantitatively assess those changes.
The big key are digital elevation models are key(especially things like LiDAR), flow, and meteorological data are key.
Getting continuous quality data on tributary streams is very very difficult. Precipitation data in the mountains is difficult mainly due to the shortness of record, but there's no
way to fix this. NASANOAAUSGS No
54
coupling between tectonic and climatic processe erosion processes during hydrometeorologic extreme events glacial landscape evolution in the Andes and Himalaya
Combine remote sensing and Earth Surface Processes in a more direct manner Utilize several air- and space-born satellite data sets to understand Earth Surface Processes
lidar radar near infrared data hyperspectral data
hydrometeorological data gps NSF DOE NASA NOAA ESA Yes
55
To understand the evolving science and technology for the GIS applications, through research such as LiDAR and even more accurate remote sensing techniques, to estimate the future trends
Through CI, internet and remote sensing, providing a series of solutions for the emergency respond and advanced decision-
support for real time issues LiDAR and satellite based observation data NSF NOAA Yes
56
What are the processes that control landscape evolution?
How can we quantify such processes and ensure that our mathematical models are capturing reality over appropriate length and timescales?
The use of field validated models of landscape evolution that incorporate atmospheric and lithospheric models to explore the controls and feedbacks on topography.
Digital elevation models at various scales.
Synthesized records of erosion and/or deposition.
High resolution geologic maps. High resolution
precipitation and other climate maps. NSF NASANOAAUSGS No
Yes Hydrology, especially related to flooding.Yes CSDMS, CZO n/a
Software is crucial, and very often overlooked in science. Current modeling and data analysis software in earth-surface dynamics tends to be idiosyncratic, poorly maintained, poorly documented, and lacking in modern software engineering standards. The infrastructure to support proper software development, testing, and life cycle needs is sorely lacking, though CSDMS is an excellent start. Still, it is under- funded relative to similar efforts in other disciplines.
See previous comment: support for scientific software is the biggest bottleneck.
Yes Dendrochronology, Ecology, Biology (plant physiology in particular)Yes My tree data will be hosted in NOAA's International Tree-Ring Databank. My other data does not have a place to be hosted.
A more interactive search engine. I feel like the spatial data is hosted in so many places, why not have the USGS host it? They do an excellent job with the National Map V2.
hazard monitoringYes meteorology, seismology, oceanographyYes NASA better and better accessible metadata data storage, access, and processing power computational resources
Yes Yes Access, SQL Server, Oracle free, real time
networking, super computer and large storage media
Not sufficient but there some, like MapWindow GIS/Dotspatial/PDAL/BCAL LiDAR tool and commercial software-- ArcGIS/Envi
Yes Tectonics, climate, ecology.No
Model coupling
Many fields across the geosciences have common needs when it comes to computational modeling.
We need a robust and reliable set of software tools and modules.
processing active and passive microwave data data storage, data merging
One important concept that should be included in the CI plan is the ability to merge different datasets by time and space (e.g., in a GIS system)
Data Processing
high speed internet and high performance computer and large storage
Create more opportunities for the researcher in the Geosciences
Generating products of digital elevation models. For example, extracting river profiles requires a number of DEM processing steps. If the products of DEMs were already generated (some are for 1km DEM, but not the 1/3 arc sec NED dataset), it would be rather straightforward to automate the extraction river profiles and watersheds. This, of course, is just one example.
Various derivatives of DEMs could be generated and be made available on something like earthcube (e.g. imagine one zooming in to their landscape of interest and having river profiles, relief, slope, watershed, any measurements of erosion rates or deposition, etc, etc available. This would be powerful.).
