1 of 17

Flood response manager

gain situation awareness of current flood situation and potential changes pe to optimally direct resources and ensure the safety of my first responder crews.

I have to go to several agencies’ Web sites and search for the relevant datasets.

all relevant data from ground stations, satellites, or social media (e.g., precipitation, wind, temperature, soil moisture), terrain (e.g., topography, vegetation, soils), for the wildfire location.

In the field, my first responder crews can go to a single applications portal, enter their lat-lon coordinates (or use “near me”), and get access to all the relevant datasets in easy-to-use, real-time-actionable formats.

Agriculture and Climate Cluster (Bill Teng and Brian Wee)

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2 of 17

DHS CISA

Find private sector data that I can incorporate into my WATCH OPERATIONS

I must access many different websites or just go and see what happens

Traffic Information, fastest route, state/federal waivers and Declarations impacting my route, toll booth locations, weigh stations / status, weather along route, delays at destination (loading/unloading, backup for fuel loading...) in geospatial formats for sharing into GeoCollaborate. Disparate sources are fine if offered as a REST service

I go to a single ORL Data Dashboard, click on the type of event, enter my role (i.e. truck driver, State Decision Maker) and get a list of all the datasets and apps relevant to that event as well as information about the operational readiness of the datasets presented along with the REST endpoints

Disaster Cluster (Dave Jones)

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3 of 17

post-wildfire response manager

gain situation awareness of the post-wildfire landscape to optimally direct resources and ensure the safety of my first responder crews.

I have to go to several agencies’ Web sites and search for the relevant datasets.

all relevant data from ground stations, satellites, or social media (e.g., precipitation, wind, temperature, soil moisture, burnt area, fire intensity), terrain (e.g., topography, vegetation, soils), for the wildfire location.

In the field, my first responder crews can go to a single applications portal, enter their lat-lon coordinates (or use “near me”), and get access to all the relevant datasets in easy-to-use, real-time-actionable formats.

Agriculture and Climate Cluster (Bill Teng and Brian Wee)

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How do I solve this problem now?

What would the Easy Button look like?

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4 of 17

Environmental Planner

Obtain data of sufficient quality to make a decision

I search data products and services on the topic, but am unable to determine the quality of some data.

Data and information that have been documented as having high quality

I find a set of data products, click on “Data Quality” and obtain information to identify issues relevant to data quality for the data products of interest. Issues are highlighted in a “Known Issues” section of data quality documentation.

Information Quality Cluster (Robert Downs)

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5 of 17

Environmental Research Scientist

Obtain data of sufficient quality for my study

I search for data products and assess the quality, based on metadata and documentation, but receive too many hits making it laborious to examine and extract the relevant set of products.

Data and information that have been flagged as having high quality

I would search for datasets with quality flags that contain a particular value. Results would be filtered by the system so I receive just the data products (files) of interest.

Information Quality Cluster (Downs)

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6 of 17

Early Career Researcher - Mineral Classification

do research in the field of mineral classification

I spent a few months asking many of my colleagues about the best data to use. It turned out that this was AVIRIS and AVIRIS-NG data.

I want to locate NASA data which I can read with my Python code with which I can perform a variety of mineral classification tasks.

I submit a query and see all datasets which have been used to achieve mineral classification.

Semantic Technologies Committee (Downs/McGibbney)

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7 of 17

Student in Environmental Science

analyze some environmental data to complete my assignment

I surf around the web, but do not know where to search and what search terms to use.

I want to find data about the environment for an interesting problem

I go to a single website and see a list of topics that I could choose from to find data

Semantic Technologies Committee (Downs/McGibbney)

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8 of 17

Student Researcher in Environmental Engineering

Thesis project about Hydrologic Balance in one subwatershed in Panamá

Used Giovanni to get evapotranspiration variable mean_FLDAS_NOAH01_C_GL_M_001_Evap_tavg but have doubts if it is really what I need for my project.

Evapotranspiration data for subwatersheds in Panamá

Simpler interface pointing to evapotranspiration with place (and time?)

GES DISC (I. Gerasimov)

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9 of 17

Masters student in Agricultural Economics

Study Daily means on the temperature and precipitation in Tanzania between 01/2005 - 05/2011

GES DISC recommended three MERRA-2 datasets and on-the-fly subsetting service and a HOW TO on creating daily means from NetCDF files

A dataset with daily means for each day for each latitude and longitude that can be exported into R

A service that determines the most appropriate dataset for temperature and precipitation over a given time period and given region and produces daily means of these variables

GES DISC (I. Gerasimov)

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10 of 17

Undergraduate student

Find out “what kind of soil or something like water is there at any depth of the earth”

Contacted GES DISC services, was recommended GLDAS-2 datasets that contain the soil moisture layers and variables

Data containing soil moisture variables for Earth layers.

A service that provides soil moisture data for Earth layers.

GES DISC (I. Gerasimov)

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11 of 17

NOAA Weather Forecaster

Studying dry thunderstorm events near Medford

Contacted GES DISC and was advised to use specific MERRA-2 datasets and Giovanni service to select parameters, location, vertical level, date and produce time series

multiple parameters, e.g. 850mb temperatures, 700mb winds, 850 mb winds, and Precipitable water of reanalysis data for multiple times, e.g. date and specific time

Simpler interface pointing to reanalysis data and parameters

GES DISC (I. Gerasimov)

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12 of 17

Staff member from German Research Centre for Geoscience

Daily precipitation rate data for 36 point locations in the European Alps

Contacted GES DISC, who recommended GRaDS Data Service for MERRA-2

time series of daily precipitation rate data for 36 point locations in the European Alps from several reanalysis datasets (ERA-interim, ERA-5, NCEP/NCAR, MERRA-2)

A way to obtain this data without the need to download thousands of files

GES DISC (I. Gerasimov)

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13 of 17

Doctoral researcher in Nigeria

Studying groundwater storage change in Lagos, Nigeria

Contacted GES DISC and asked for Giovanni access to GRACE data. Since Giovanni GRACE data covers North America only, a user was advised to use GLDAS soil moisture data and referred to the JPL GRACE project

Soil moisture data, asked for GRACE

Simpler interface containing soil moisture parameters for both GLDAS and GRACE

GES DISC (I. Gerasimov)

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14 of 17

Data Scientist at NASA Ames Research Center

Build a neural network model to estimate air quality from remote sensing imagery for urban environments.

We have to hunt for sources of air quality data from papers, online repositories, government sources and then wrangle all this data together into a cohesive dataset we can work with.

Air quality data - both directly measured as well as modeled. Ideally with high spatial and temporal resolution.

A queryable library listing sources of air quality data along with relevant metadata - location (extents), type of measurements, frequency, modeled/measured, etc.

Michael von Pohle

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15 of 17

Incorporated Town in a Large Metro Suburb

Provide information about local Air Quality metrics for use by Town officials to evaluate the impact of industrial-zoned business practices, such as AQ permits and waiver requests.

Permits are based on state AQ monitors; the nearest two units are 12+ miles distant and in more rural areas. Town officials are invited to comment on AQ waivers but have no data to support their concerns.

Appropriately located surface-level AQ metrics to help identify the accumulated impact, and sources of air pollution in heavy-industry areas located adjacent to residential areas.

An app with a map showing locations of the sensors providing AQ metrics with current values for the measured pollutants (particles, chemistry). The app would also analyze data to generate an AQ assessment and charts providing statistics over time.

Air Quality Cluster (Karen Moe)

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16 of 17

Ocean Science Researcher or grad student

Perform EOF (empirical orthogonal function) analysis on global ocean and atmospheric datasets to look for patterns and teleconnections in large interannual/decadal scale events like ENSO and PDO

Find and download datasets (across different data centers), regrid/reproject/aggregate in time and space, calculate anomalies, form covariance matrix, do EOF, analyze output.

Discover ocean/atmosphere datasets that are

  • Long time series and at least daily/0.25 degree resolution
  • Contain uncertainty information
  • Can be manipulated with external transformation services or data recipes

A list of datasets meeting the requirements for time/space and regrid capabilities. This includes having an API to granule level information to do data conditioning. Includes links to data recipes including data regridding and EOF analysis

JPL PO.DAAC (Ed Armstrong)

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17 of 17

Polar Climate Modeler

Large scale polar climate hindcasting, role of transport processes on understanding role for clouds and radiation and climate feedbacks, which are important for climate change problems.

A lot of effort goes into compiling the observation and numerical weather model data for climate modeling, and scientific inquiry currently proceeds by investigating event driven features and anomalies to elucidate gaps in the climate modeling and make inroads to represent underlying processes.

Parameter values from numerical weather models and meteorological observations to drive and constrain climate models for processes they do not resolve.

A knowledge map of numerical weather model output and meteorological observations that climate modelers have assimilated in specific model runs to enable reproducible climate modeling and model output inter-comparison. This should be a tool for scholarly dialog between Atmospheric Scientists from related sub-disciplines on processes occurring across weather and climate timescales.

Jonathan Blythe, BOEM

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