NEISGEI Reporting

Quarterly Report

1 Relevance

1.1 List number of interactions (e.g., phone conversations, e-mails, face-to-face communications) with key decision makers and expected users of your project's products.

1.1.a Number of Phone Conversations
1: Greg Stella

1.1.b Number of E-mails
1: Tom Pace

1.1.c Number of Face-to-Face Communications
1: We helped organize a NO2 Workshop (see http://wiki.esipfed.org/index.php/Workshop)

1.1.d Number of Other Communications and Types

2 Quality
2.1 Are you collecting data that is in conformance with formally established Standard Operating Procedures (SOP) within your research community?
No

2.2 If no, briefly explain in several sentences why you're not (e.g., there is no established protocol and the project is developing its own SOPs).
We are not collecting data but are working with data that follow standard data schema and formats. One of the objectives of our work is to help estalbish standard data interfaces for uniformly accessing and working with distributed, heterogenous data sources.

3 Performance

3.1 Cite any meetings, symposia, conferences, or workshops at which you presented your project.

• EPA-ESIP NO2 Workshop (),
• HTAP NASA briefing,
• EPA OEI Symposium,
• ESIP Federation Winter meeting

3.2 Did you achieve progress toward scalability as outlined in your implementation plan (e.g., is information/data able to be expanded/contracted spatially and temporally)?
Yes

3.2.a If yes, briefly describe. If no, briefly explain how it will be addressed next quarter.
OpenLayers, Flex charts, NEISGEI WCS, DataFed WCS integration, Grid analysis services, DataFed service workflow engine
Methods for accessing by space-time, visualizing in space-time, and exploring dynamically in space-time one or more emissions datasets

3.3 Did you achieve progress toward integration (e.g., is information/data from this project able to be combined with information/data from other complementary sources)? Yes

3.3.a If yes, briefly describe. If no, briefly explain how it will be addressed next quarter.

• Yes, WCS to DataFed. FeatureService WFS
• Registration in metadata catalogs

3.4 Did you achieve progress toward interoperability (e.g., is data being time and date stamped, longitude and latitude stamped, height/altitude/depth stamped, and is data being given metadata tags)?
Yes

3.4.a If yes, briefly describe. If no, briefly explain how it will be addressed next quarter.
WCS to DataFed. WFS Registration in metadata catalogs

4 Project Management

4.1 Are you on track in completing scheduled work tasks?
No

4.1.a If No, please explain delays.
Technical difficulties on both IT (learning curve with open source software) and data processing (data availability, access methods, reprojection, and handling large sizes). All issues that the project is addressing but that generated new challenges (see lessons learned).

1. 1. Problems encountered and lessons learned during the quarter.

1. 1. 1. Were there any problems encountered or lessons learned regarding funding vehicle management/money distribution?

Terry, I'll let you address this one

1. 1. 1. 1. If yes, please describe what you learned.
      2. Were there any problems encountered or lessons learned regarding the research process?
         1. If yes, please describe what you learned.
      3. Were there any problems encountered or lessons learned regarding the subject matter?
         1. If yes, please describe what you learned.
      4. Were there any problems encountered or lessons learned regarding information technology?
         1. If yes, please describe what you learned.
      5. Were there any problems encountered or lessons learned regarding equipment?
         1. If yes, please describe what you learned.
      6. Were there any problems encountered or lessons learned regarding new methodologies?
         1. If yes, please describe what you learned.
2. Comments
   1. Please add any additional comments below.

Final Report

1. Relevance 1.1. Interactions with key decision makers. List decision makers and their feedback.
GEIA Amber Soja Tom Pace Doug Solomon

1.2. Expected uses by decision makers. Please describe.
Data Access Data Visualization Data Analysis

1.3. Unexpected uses by decision makers. Please describe, if any.

1.4. List project collaborators (person and organization), and nature of collaboration.
Terry Keating (emissions comparisons, data sources/access) Rudy Husar (satellite data) Gregory Stella (data sources/access, emissions user, application tester)

1.5. List resources (i.e., money, equipment, data, methods, models) contributed by collaborators. List number of interactions (e.g., phone conversations, e-mails, face-to-face communications) with key decision makers and expected users of your project's products.

2. Quality 2.1. List all Quality Assurance, Quality Control, and technically relevant guidelines and methods, and SOPs used during your project that may be used "as is" by other projects in the future, or potentially used "as illustrative examples" to develop other project specific SOPs.

2.2. Describe any lessons learned regarding QA of the equipment used and its performance.

2.3. Describe limitations of project's data for inference, especially in terms of error propagation and scalability (to help other user(s) of these data to determine what it can be used for).

2.4. Describe strength of project's data for inference.

3. Performance

3.1. Describe how you met the project's proposed objective/goal. If you did not, please explain why.

3.2. Describe your project's ability to characterize human health and/or environmental outcomes quantitatively. 3.3. Describe the project's key deliverable(s). Scalability, integration, and interoperability are important characteristics that help turn the project's work products into "services" within the context of a service-oriented architecture.

3.4. Scalability:

a. In its present form, are your data, models and/or services scalable (e.g., able to be expanded/contracted spatially and temporally)? Please explain.

b. Are there identifiable scalability barriers (e.g., data, models, and/or services are so computationally intensive that it would require more computing capacity (e.g., storage, speed) than is currently available, so either more capacity or more resources are needed to make the algorithms more computationally efficient)? Please explain.

3.5. Integration: Was information or data obtained in this project integrated with data obtained from other sources? Please explain.

3.6. Interoperability:

a. Is information or data obtained from this project in a format such that it can be combined with other information or data? Please explain.

b. Is the software you used capable of exchanging data between different programs and reading and writing the same file formats?

c. Number of new user requirements for your software or hardware.

d. Problems incurred in meeting new user requirements.

e. Are all data time and date stamped? If not, why not?

f. Are all data longitude and latitude stamped? If yes, what is the spatial resolution (if multiple resolutions, provide range)? If not, why not?

g. Are all data height/altitude/depth stamped? If yes, what is the spatial resolution (if multiple resolutions, provide range)? If not, why not?

h. List Metadata Standards used (e.g., Global Change Master Directory - [1]).

4. Project Management

4.1. Key Learning: What did you learn over the course of your project regarding process/project management that is important to pass along to AMI/EPA GEO management and future PIs?