Energy and Climate Cluster Summer Meeting Agenda

From Earth Science Information Partners (ESIP)
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Energy and Climate

July 13, 2011 Wednesday

8:15 – 9:45 AM Track 5 Energy-Climate Breakout

  • GEOSS Architecture Implementation Pilot (AIP-3) Energy Scenario: Use case of the environmental impact assessment of the production, transportation and use of energy for the photovoltaic (PV) sector – Lionel Menard, École des Mines de Paris (via WebEx)
  • Wind Energy Resource Assessment – Daran Rife, NCAR
  • Application of Statistical Correlations of Sub-Hourly Irradiance Measurements and Hourly SUNY Data to Photovoltaic Array Performance – Marissa R. Hummon, National Renewable Energy Laboratory

9:45 – 10:00 AM Break

10:00 AM – 12:00 PM Track 5 Energy-Climate Breakout (Cont’d)

  • Partnerships for Wind Energy Siting Decision Tools – Alison LaBonte, OSTP, and Taber Allison, AWWI (via WebEx)
  • NREL Data Sources and Quality – Debbie Brodt-Giles, National Renewable Energy Laboratory (via WebEx)
  • The New Peer-To-Peer Architecture of the Earth System Grid Federation – Luca Cinquini, NASA/JPL
  • Impact of Climate Change on Energy Demand and the Optimal Site Selection of Wind and Solar Farms - Glenn Higgins et al, Northrop Grumman

July 15, 2011 Friday

8:30 – 10:00 AM Track 5 Energy-Climate Breakout


JULY 13, 2011 MINUTES

8:30-10:00 session

Attended: Lionel Mernard (MINES Paris Tech), Dr. Shailendra Kumar (Northrop Grumman), Marissa Hummon (NREL), Louis Kouraris (GSFE/NASA), Sky Bristol (USGS), Mike Inqlis (UNM/EDAC), Helen Conover (UAH/GHRC), Rob Raskin (JPL), Chris Lenhardt (ORNL), Danny Hardin (VA Huntsville), Chuck Hutchinson (UAZ), Bruce Caron (NMRI), Luca Cinquini (JPL), Kenton Ross (NASA DEVELOP), Tom Narocte (NASA/GSFC), Brent Maddox (UW-Madison), Bruce Barkstrom (SGA), Yasmin Zaerpoor (ESIP Student Fellow), Erin Robinson (ESIP), Carol Meyer (ESIP)


Lionel Mernard- GEOSS effort, MINES Paris Tech

  • GEOSS AIP-3: Architecture Implementation Pilot, Phase 3: Environmental impacts assessments of the production, transportation and use of energy.
  • Brief intro of MINES Paris Tech: 15 research centers at 4 sites in France, MINES ParisTech is an education institution facility- created in 1793. 5 major fields of research: one of which is Energy and Process Engineering. Has strong links with companies and industries and ranked numb 1 in France for industrial research partnership. 3 major research axes in Energy: 1) Energy efficiency,

2) decarbonization of process and fuels, 3) Renewable Energy. Renewable Energy Axe: a) Evaluation of energy resources (solar, offshore wind), b) Construction of databases, etc)

  • Scope of the GEOSS AIP-3 Energy Scenario
    • Goal is to provide spatial information of the life cycle environmental impacts of the production of PV electricity
    • Need information to help assess current enviro impact on a global scale (climate change) and local scale (landscape concerns)
  • Life Cycle Approach: Discussed environmental impacts of a PV system over its Life Cycle
  • Environmental Impacts Assessment Methodology
    • DPSIR assessment: Drivers, Pressures (on the enviro), State, Impacts, Response
    • Inputs/Outputs description: Inputs= PV System selection Site, LCA model parameters. Outputs= Environmental impacts/kWh produced (CC, Human Health, Ecostystems, Primary Energy, etc)
  • Partners datasets and components contributed shows who is providing the different components.
  • GEOSS Commons Infrastructure
    • GEO Portal and Websites/Webportals provide users the ability to find the information available by GEOSS
    • GENESIS Toolbox: Implemented various Enviro Impact computation methods as WPS using the GNEESIS Toolbox. The Toolbox is composed of two applications: development enviro and a run-time environment. Tutorial will be released in the next few weeks.
    • Webservice-energy.org: provides community-driven access to info about renewable energy and the enviro.
    • GEOSS Clearinghouse provides search across all GEOSS sites: provides a ‘yellow page’ feature to GEOSS
    • GEOSS Registry includes Component Basic Info, Contct info, Category, etc. Service (Catalogue) information includes link to the resources, GEOSS Classification, Update frequency and status.
    • GEO Portal: user can search for something (eg energy/environment)- for a more focused search, the user can go to the thematic Portal EnerGEO. The result provides a summary description of the Web Processing Service (WPS) with a link to the client that makes use of this WPS. Led to the GENESIS platform: has a map service (provides maps) and point service (environmental impact assessment point service). The user can then input paramaters and up to 5 locations. This results in the climate change impacts for each point selected (expressed in emissions of CO2 produced- CO2 eq/kWh). User will also get a map of the region showing the range of the expected environmental impact.
  • Conclusions
    • Scenario illustrates the benefit of combining resources for assessing Enviro Impact of a PV System based on its geo-location
    • Scenario provides components and tools for Enviro experts, policy planners and GEOSS community
    • Concludes with list of links that can be used

Questions

  • Kumar: Want to draft document for wind energy project during next meeting- how can we get GEOSS community involved?
  • Kumar: Are there other orgs (in Paris) that may be interested in this?

Marissa Hummon: NREL, Contact: marissa.hummon(at)nrel.gov

  • A year ago started working on down-scale satellite data to minute data
  • Motivation for high spatial and temporal resolution PV power output: Adding Solar Power to the Grid: Not many people are aware of how electricity gets to their house. A system operator has to balance the load (electricity produced) and what’s delivered on a second-to-second basis. Showed slide of energy load over a 5 day period for a home in CA: in general, the conventional electricity generation comes from hydroelectric plants, nuclear plants, some renewables and petroleum. These are all types of plants that run constantly- the remainder is often met with natural gas. People are interested in solar because it mimics this load profile (peaks in the afternoon)- would like to see an increase in solar energy because it will reduce carbon impact on the grid. As the solar power increases, in some cases we may have days that the solar power exceeds the load. NREL studies the integration of large amounts of solar power on the grid: looks at diversifying solar plants across an area and smoothing of impacts.
  • Locations and Existing Data slide: red shows where they could put solar plants. Green dots are needed to produced one-minute satellite data. Two data sources: 1) (Hourly) satellite data and 2) (Minute) Ground measurements of irradiance
  • Focus of the talk will be the statistics of satellite data and their relation to ground-based measurements. Satellite data comes out from SUNY: snapshot of the reflectance of the center pixel from the GEOS database. Resolution 1 hr. Ground measure irradiance data is point source measurement with a resolution of 1-10 min. Deficiencies: SUNY data is a probabilistic representation of the local cloud cover, ground-based irradiance data is accurate but expensive and represents a single point.
  • Clearness Index: ‘Expected’ Clear Sky model is the black line that shows what the irradiance would be if there were no clouds in the sky. Gray line describes the measured irradiance. Blue line= clearness index= ave of the two. Clearness index of 1= sky was clear, no distinct cloud shapes. 0= night.
  • Developed 5 classifications for the clearness index: Increasing degrees of variance. Developed them by looking at slices of one-hour data.
  • Site Clearness Index Analysis: Aerial satellite data issued to calculate the relative portions of cloud cover in an area for each hour. This data is related to the sub-hourly measurements of irradiance.
  • Measured one-minute irradiance values: try to relate the mean of the satellite data and compare to the mean of the one-minute data. Also looked at the standard deviations (SDs) for the data but it was not a good measurement.
  • Class I Sky slide: Charts on the top are the satellite data for each our. Plot on the lower right is the synthetic data that is produced.
  • Class II Sky slide: You’ll notice that the SD is proportional to the mean: ie the overall smoothness of the area is continuous.
  • Class III Sky: Not as smooth. Class IV and V sky: high degree of variation.
  • The last part of the synthesis is that PD plants are well represented by point data. This is where higher-resolution satellite data would be very useful.
  • After synthesizing the data they look for site-to-site correlation: a change in solar irradiance at a site of interest is very close to irradiance at a site close by.
  • Last thing of interest is a comparison of ramp frequency.
  • Conclusion:
    • Simulated 1 min time interval global horizontal irradiance for sites in Western US from clearness index ramp distributions and cloud event frequency and duration. Next steps are to develop better ‘filter’ to represent different sizes of PV plants, ...


Questions:

  • Relation to ESIP?
    • NREL has solar resource assessment group that uses SUNY datasets but don’t pursue other sources of data. A better partnership between the rest of earth satellite community and NREL would support NREL’s efforts.
  • Have you used this data to do any predictive analysis on what the cloud cover might be like?
    • The one-min data is being used by the Western Electric Coordination Council (WECC) to plan future transmission and capacity expansion. Need to transfer solar electricity very far distances and the electric grid industry operates on a tight margin: so deciding whether or not to build a large-load transmission line is a big consideration- what is the min capacity that line can handle to maximize distance energy is transferred. One-hr studies are for general resource evaluations.

10:30 Session

Alison LaBonte- OSTP, AAAS Fellow: ‘Facilitating Responsible Siting of Renewable Energy’

  • Goal: 85% of electricity from clean, diverse sources by 2035
  • Will talk about science based effort to achieve the administration’s long term goal.
  • The Planning Process: Define objectives, gather data, identify issues constraints and future constraints; develop alternatives; evaluate alternatives; implement plan; monitor and evaluate management measures; refine goals and objectives; cycles back to gather data
  • In wind siting: goal of planning process is to minimize effects on fish and wildlife. US. Fish and Wildlife Service drafted land-based wind turbine guidelines and an eagle conservation plan guidance.
  • AWWI Landscape Assessment Tool (DOE funded, TNC developed) has been developed. Several tools under development now.: Will do an overview of the Rapid Ecoregional Assessment (a BLM process), the Rapid Assessment Methodology (USGS in collaboration with USFS)
  • Classifications for functions that Decision Tool Functions can make available: Data management, Mapping and Visualization (helps identify the conflict and temporal/time-series data), Alternative Scenario Dev and Analysis (Impact Assessments, forecasting, etc), etc.
  • Bureau of Land Management: has developed an Interactive Layered Map (produced by BLM Oregon): most common example of tool available for land management users today.Maps are really just a snapshot in time and need to be updated.
  • BLM’s approach today include Rapid Ecoregional Assessment: will aggregate data on resource values and changes to create an interregional conservation strategy.
  • Another tool: Fish and Wildlife Service: Information, Planning and Conservation System (IPaC)- GIS related tool.
  • Last tool currently under development: Rapid Assessment Methodology (FWS-USGS joint effort) tool to be used by wind developers for preliminary screening and initial characterization of wind siting process. User enters region or location that is being considered for wind project development and get a ‘risk score’ in response + relevant info + next steps.
  • American Wind and Wildlife Institute’s Landscape Assessment Tool: developed in partnership with the Nature Conservancy to provide preliminary wind-wildlife sensitivity screening: developed a mapping tool that provides data on issues that were of concern to a potential developer that was screening a landscape for a potential site. Includes species that could potentially be affected by the wind sites.
  • Number of ways that this could be used by developers: eg. Developer can define a potential project area and generate report that lists species of concern, underlying data is available and can be downloaded.
  • Conclusion: Common concerns:
    • Lack of transparency to user on which decision tools to use, are the data sets comprehensive?
    • What’s the quality of data are the tools being used appropriately?
    • Quantification
    • Flexibility
    • Number of tools developed v. individual tool improvement

Taber Allison, American Wind Wildlife Institute (AWWI) Director of Research and Evaluation, Contact: Tallison(at)aww.org

  • AWWI’s mission: to facilitate timely and responsible development of wind energy while protecting wildlife and wildlife habitat.
  • AWWI has multiple initiatives: research, landscape assessment, mitigation and education
  • Research Information System (RIS)- will focus on the analysis of existing data. Premise of RIS is that there are over $100 mil of wind-wildlife data. These data are held by the companies/consultants for wind-energy companies and the goal of the RIS is to build a database that would house all this info and make it available for scientific analysis while safeguarding confidentiality of proprietary information.
  • Developing the RIS pilot with Oregon State University (OSU-NACSE): Collecting sample data to help contractor develop parameters of the sample data. Essentially creating a metadatabase. Need to present the data to the user in a format that can be easily analyzed.
  • RIS Vision: Conduct analyses across habitat, species, geographic and wind project types; improve understanding of known impacts and outline knowledge gaps for future research; and contribute to pre-construction risk-assessment
  • Challenges:
    • Assimilating data from diff sources
    • Providing protocol information while protecting proprietary information
    • To provide meaningful data without identifying specific project sites
  • Hope to link Landscape-Level Assessment with AWWI Tools
  • RIS + LAT: Evolve from ‘impact’ analysis to accurate predictions of project risk

Questions:

  • Do you have a rough idea of resolution when looking at impacts of wind sites and wildlife?
    • Taber: Tier 1-3 (pre-construction tools) focus on the landscape level- impacts at a large scale (10-100+ km in terms of siting) whereas RIS focuses more on the site level (within 1 km): provides information on individual turbines.
  • After you use the data, have you thought of capturing a snapshot of that data since it will change over time?
    • Taber: Even over the last 10 yrs there’s been a change in quality of the data and convergence of data collected and there will likely be continued evolution (esp as we learn what the key variables are). RIS will have to develop to deal with the desire to create consistency in data collection and also evolution of the variable framework.
  • Can you highlight key needs for data gaps that exist and/or data that are difficult to access that ESIP could consider identifying, preparing metadatabase, etc. Ie. top priority needs?
    • Alison: 1) The options for mitigation; 2) Have a very limited understanding of migratory pathways of bird species and being able to predict those pathways; 3) Seasonal variability of the activity patterns and how that might be correlated with changes in the atmospheric conditions and what the mitigation options might be.
    • Taber: Developers spend a lot of money on using radar to collect info on bird/bat activities and we aren’t able to connect data on what the risks are (?). Challenge is to take all the info and the tools and understanding what they mean in terms of risk in the project to wildlife.

Debbie Brodt-Giles, NREL, Open Energy Information (OpenEI.org)

  • Facilitating access, use, and contribution of worldwide energy data and information
  • Open Energy platform (wiki-based) to provide energy information worldwide to make better decisions
  • Creating a Clean-Energy Commons: improved access to energy-related information; providing a community of support to provide collaboration and contributions; Easy, legal, and scalable sharing (on Cloud); Actionable assessments of information quality and provenance
  • Commons: will have energy data, tools, energy maps, energy education materials, energy models and energy documents
  • Method: Provide transparent, participatory, collaborative energy info in accordance with the Open Gvt Initiative using Linked Open Data methodology
  • OpenEI
    • Collective: ‘The Wiki Way’: crowdsourcing, collecting data from the community and can be manipulated
    • Segmented: ‘The Census Model’: cities report information in a collective way but don’t overwrite other cities’ data
    • Authoritative: ‘Single Owner’: Users can upload their data but no one can modify that data.
  • Example of an application of Open EI: Individuals can add utility rate information on the platform since EIA does not publish electric utility rates.
  • Open EI provides linked open data so that users end up with ‘smarter’ data.
  • Unique attributes: publicly accessible text and info, easy formats to read and sort, visual mapping of data, geographic boundary analysis, facility to link external information, ability to track changes, downloadable spreadsheets of info, machine-readable data services
  • Described OpenEI website
    • Datasets: have ratings for the diff datasets, can download the dataset, get metadata. Users can also upload datasets.

Questions

  • Do you have any success stories to point to with OpenEI?
    • Debbie: Clean Energy Analysis area- U.S. OpenLabs: shows all the labs and tools available for intl labs to become more energy efficient. 2) Working with North Carolina State Univ: created incentives and policies related to using renewable energy.
  • Any success in getting private companies to provide data?
    • Debbie: Don’t want privately-held data: we want data that is completely open.

Luca Cinquini , JPL, Earth System Grid (ESG)

  • ESG: makes climate change data available worldwide, JPL/NASA
  • ESG: Historically started with DoE Earth System Grid project- but has expanded to be a collaboration with people involved with CMIP5 activities
  • Loosely coordinate by GO-ESSP (Global Org for Earth Science System Portals)
  • ESGF primary goal: Support current CMIP5 and IPCC_AR5 activities and future Ars
  • CMIP5: Climate Model Intercomparison Project phase 5: sponsored by World Climate Research Program (WCRP) to promote study of climate change, global archive of 40+ models contributed by 25+ modeling centers in 17+ countries
  • IPCC-AR5: 5th Assessment Report of the IPCC: Based on CMIP5 archive (due in 2014), will be very critical for global policy on adaptation and mitigation of climate change
  • ESGF is a system of distributed and federated nodes that interact through a peer-to-peer paradigm. Want to make the system decentralized. You can customize your Node to create a portfolio of services; once the Node comes online, it contains relation to other Nodes. Once each Node knows the URLs about the other Nodes, it needs to be able to use them.
  • Reviewed Data and Metadata Pipeline
  • Starting a few years ago, CMIP5 Data Requirements were outlined for Data Modeling and for Observations to ensure data could be easily shared and to ensure data quality.
  • NASA is working towards publishing selected satellite products into the ESGF so they can be used to validate model predictions for IPCC-AR5. Level 3 datasets (uniformly gridded) were specially prepared by science teams for CMIP5. Products published to JPL Node.
  • CMIP5 Quality Assessment Procedure: model output will have to go through three diff quality assurance processes (QC 1: Automatic Software Checks on Data, Metadata; QC2: Subjective Quality Control on Data, Metadata; QC3: Double and Cross Checks on Data, Metadata).
  • ESGF is changing its framework on searching for data (ESGF Search Architecture)
  • ESGF web portal features Data Cart so that files can be downloaded individually or in bulk.
  • Live Access Server (LAS): web application for server-side visualization that was developed by ESGF group at PMEL.
  • Ultrascale-Visualization Climate Data Analysis Tools (UV-CDAT): GUI front-end to CDAT developed by ESGF group at PCMDI.
  • Climate Data Exchange (CDX): project at JPL that would allow users to search, access, and analyze data stored at distributed and heterogeneous archives.

Conclusion

  • ESGF is developing its next generation global infrastructure for access to distributed Earth Science data based on open source, open development and peer-to-peer architecture
  • Planned as long-term infrastructure to support future IPCC Assessment Reports and climate research.

Dr. Shailendra Kumar, Northrop Grumman, Regional Climate Modeling and Energy-Related Decision Aids

  • Climate Modeling and Decision Aids: Show global climate change. Need regional downscaling to capture local effects. End result is an actionable decision aid.
  • Regional climate change in the southwest US: chart that shows methodology to regional climate modeling and decision aid development. Following slides show the data collected, modeled for SW US.
  • USG objective is to increase renewable energy generation from ~1% today to 20% by 2030. Two challenges exist: 1) Enabling system-level approaches to overall generation capacity expansion and integration, 2) Addressing the variability issues of renewable generation
  • MORE Power addresses these challenges: 1) Optimize the placement of wind/solar sites to maximize high quality power, 2) Quantifies real value of transmission as an enabler to aggregate diverse variable resources, 3) ?
    • MORE Power maximizes usable power through site diversity and power generation stability.
    • Transmission Expansion Study: Objectiv is to show the real value of transmission as an enabler to aggregate diverse wind.
    • Geographical Diversity can be used as an enabler to long-distance transmission expansion.
    • MORE Power: Future Work
  • Incorporate addtl features: Keep out zones, Addtl use cases
  • Demonstrate capabilites using higher resolution wind data over western states


JULY 15, 2011 MINUTES

Online Dynamic (Wiki) Wind (Power)-Wildlife-Habitat Decision Tools: Catalogue and Community of Practice Meeting Minutes

Attended: Shailendra Kumar (Northrop Grumman), Yasmin Zaerpoor (ESIP Student Fellow), Karl Benedict (UNM/EDAC), Tamara Ledley (TERC), Chuck Hutchinson (Univ of AZ), Uma Shankar (UNC- Chapel Hill), Brian Wee (NEON, Inc), Jerry Pan (ORNL), Bill Teng (NASA GES DISC), Mark McCaffry (CIRES-CU Boulder)

WebEx attendance- John Anderson, Rahul, Ramachandran, Douglas Johnson, Alison LaBonte

  • Kumar: Alison LaBonte and Taber Allison identified the need for responsible deployment of wind power during their talk on Wednesday (July 13th, see agenda) and that site selection is a key issue (i.e. choosing a site that has minimal impacts on the surrounding environment). Key issue is how you make sure key information is available to decision makers to choose the site. Alison and Taber identified the decision tools available that could help in making sure that the wind power is installed in a way that has minimal impact.
  • Alison: There are tools out there but there is difficulty in choosing which tools to use. Idea she had was to try to add a platform that would make tools (and the data behind them) more transparent. A gap study of decision making tools would also be very helpful.
  • Kumar: Given those leads, we thought we would discuss a potential project. Some of the ideas we have so far:

Slide: An online Dynamic (Wiki/Drupal) Wind (Power)-Wildlife-Habitat Decision Tools Catalogue and community of practice to

    • Build transparency of the decision tool architecture, data and functionality;
    • Aid decision makers in tool selection and use appropriate to their planning tools;
    • Focus improvements to the kit of decision tools where needed;
    • Facilitate partnerships in tool development and application;

Slide: Tool developers and users need to

    • Engage in defining/refining the proposed architecture
    • Develop a classification of the type of function that the tools can perform
    • Populate the catalogue
  • Tamara: Who are these tools for? For professionals or a broader community? Would students be able to contribute to this effort?
  • Kumar: Both- developers need it to make site selection, but there are planners and other stakeholders that need access to these tools. Yes, this would be an opportunity for universities to be able to contribute and provide the tools that they are developing.

It will include developers, users, and educational/research community.

  • Question 2: These stakeholders and end-users, are they already involved or are they people that you still need to contact?
  • Kumar: We will need to contact them.
  • Karl: So when we’re talking about users, what are we thinking about in terms of the different types of users that are part of the stakeholder community?
  • Alison: Primarily developers, but any stakeholder group that is developing a tool for decision making (non-profit groups, government, developers themselves). Anyone that is developing a tool would be interested in what else is out there- may give them perspective on why other tools are being heavily used, how they can update their tools and make them more valuable.
  • Mark (Univ of Colorado) Comment from audience: We’ve been doing user needs assessments to see if the tools from NASA and NOAA provide are meeting the needs. My comment is that it would make sense to have a needs assessment to get a sense of what the community’s needs are, what they’re using and what the gaps might be. You will also be able to tap their expertise along the way and, as things develop, bounce the beta version off them.
  • Kumar: I completely agree. Just to clarify-t he tool is a catalogue of tools that various people are developing. What are the gaps and the user needs that are not being identified by the current tools?
  • Brian: We shouldn’t limit the tool to just capturing the catalogue of tools or best practices. I think the last thing we want to add is just a ‘list of stuff’. What you really need is a more social sharing platform where the list of tools and best practices are there but there is also a means to see what other people are doing actively and people are engaged actively. You need a tool where you can see that they are actively using. If they download a tool, you want the facility infrastructure that you’re developing to tell other users that ‘someone is interested in this tool’... it needs to be dynamic so that the list doesn’t just die.

Slide: Wiki Information for Each Decision Tool

    • A matrix of decision tool functions and features
    • Listing of base data layers, their source, and follow on adjustments to the data layer that are component to the decision tool
    • Tracking of updates to decision tools
    • Keeping a tally of applications of each decision tool
    • Contact info for decision tools
  • Brian: I would add that it’s important that there is additional functionality that needs to be highlighted. What draws me to Facebook to check is to see what other people are doing. So that layer of social connectivity is important to this tool that we want to propose.
  • Kumar: I agree- the collaborative platform is important here.
  • Rahul: Who will this be open to? How do you ensure data quality?
  • Karl: One approach is to add mediators- that would add an intermediate step to adding data (i.e. like what Wikipedia does)
  • Rahul: If you restrict the users you have more control over the data quality.

Slide: An Example (Ecosystem-based Management Tools Network)

    • Gives you a list of tools, you click on them and the it takes you to the website. But this is pretty rudimentary- we need to go beyond this.

Slide: Tool Function Matrix:

    • On one side you have the tools listed at the top and then the criteria on the side to show which tool addresses which needs.
    • These are some ideas on how to present the information to end-users.

Slide: Community of Practice

    • Should include metadata, use cases, collaborative environment, mapping tools to user applications, connecting tools to datasets, how to better utilize the tool, gap analysis
  • Tamara: It may be useful to think about the mechanism by which, instead of the matrix, you have a faceted way of searching. When you click on each feature, it narrows the tools that fall under that category.
  • Mark: Instead, or in addition, to the matrix, it would be helpful to be able to sort through and find the tool. The added value of having feedback from peers, some sort of review about the tools, is important. Not just a laundry list of tools- but a community building aspect of how people use the tools, change the tools, etc.
  • Kumar: ESG is providing metadata to various places- but also going a step further to add information on how the tools are valuable and what they’re using it for. That’s a useful model to look to.

Slide: Use of the Wiki Information

    • This would be a place where we can start getting feedback from the end-user community.
    • Can also have peer reviews to evaluate the quality of the pool and for the end-users to see which tools are well-supported.
    • To identify areas for possible tool interoperability: that’s a big one. So that tool-users can better understand how a combination of tools can help them in their task.
    • Support activities to evaluate and further refine tools: e.g. there’s a workshop (AWWI-Western Governors’ Association Landscape Assessment Tool workshop) coming up that will be an opportunity to engage the communities.

Brian: Some of these areas, especially the parts about liking inputs/outputs, really bring up Chris Lynnes’s (NASA GSFC) proposal about earth science collaboration. Given that that is 4-5 years away just to pull the pieces together- Chris Lynnes uses ‘work flow’; his vision is to build a cloud-based collaborative platform. In this particular talk, you are injecting a good element which is not found in Chris Lynnes’s vision like ‘best practices’.

  • Kumar: We’re not going to do all these things right away... it will be a building process. Rahul, do you think it would be appropriate to use Drupal or stick to wiki?
  • Rahul: Drupal has much more expanded ability as a platform.
  • Karl: The ability to have much more structured content is easier in Drupal. Given the level of expertise in the Federation, Drupal would be more appropriate. An example is done in the wiki: the Information Technology interoperability developed a matrix of interoperability standards and tools and support for those. Essentially it was a table within the wiki. Another example was a product of a workshop- may already be using Drupal.
  • Brian: I would agree- Drupal has more flexibility, it is an open-source platform and easy to use.
  • Tamara: One other member of ESIP F is SERP- another content-management system. It speaks to the things that you’re doing.

Slide: Sample Listing of Wind-Wildlife Habitat Tools for the Catalogue

    • This is a list of tools that already exist and can be catalogued.
  • Alison: Most of these tools are under development. Only the last two are actually in existence. There are multiple other tools that aren’t on this list, but these are the major ones under development.
  • Tamara: Went to CLEAN homepage (cleanet.org) These are Educational Resources: we have 92 resources in here now. If you go down on the right hand side, we have various ways that we can categorize the tools. In our particular case, we have Climate and Energy topics at different levels. For each facet (regionally focused, type of tool you want to use, etc) that you want to refine it, it narrows down your list. Each tool page has a link to the tool, description of it, notes from the reviewers, etc. Through our review process, we’ve added more information about the science, the pedagogy, the technical issues that have come up while using the tool, etc. At the bottom, there is a link to ‘join the discussion’. What it doesn’t do, which this doesn’t have, is that you would also want to have discussion about a group of tools. All of this is information that you could add to your proposal.
  • Kumar: We could have discussion groups on topics or a need rather than specific tools.
  • Alison: There are only about a dozen tools out there... there aren’t that many. There is a question of ‘how much architecture we should be designing if there are only a number of tools out there’. It gets more complicated when you are considering the datasets that go into these tools.
  • Tamara: I also worked on a project called ‘AccessData’ which was trying to facilitate way to identify datasets that could be used in education. We have information about the dataset in human-readable form for the educator: i.e. what was collected, how, what use it is to the user, what it’s teaching. So here is architecture that you can take advantage of- you can develop this around tools that address a whole range of topics (not only wind... maybe also solar).
  • Rahul: Drupal could do something similar.
  • Tamara: The CMS was built by Sean Fox at SERC (part of the ESIP federation). It’s a tool design that we developed that easily engages users.
  • Kumar: The next steps are to come to an agreement- does this project make sense for us to take on? We’ll certainly need member participation in this. Is there usability here- does this project make sense for ESIP to take on?
  • Karl: It does make sense in an activity that crosses a range of expertise across the Federation. We have a committee that can add more detail and an assessment of what technology is needed. It might be good to identify a working group within that committee to determine what kind of work is needed and how to develop the kind of support to that. Just need to get into more of the details of how to design it and execute it.
  • Mark: The scope of work should definitely include a user-need assessment that will be ongoing- first to identify what is needed, and also to provide feedback on the beta version and provide input throughout the process. User involvement is very critical throughout the process.
  • Tamara: It’s a great idea- you can develop this tools even beyond wind.
  • Kumar: This would just be a starting tool- and can be extended to other fields (like solar).
  • Mark: Focusing on wind and ecological habitats is important. Big elephant in the room is sea level change. A lot of agencies (people here at NOAA) are wondering if their satellite data is enough to get a handle on sea level change.
  • Kumar: This cluster is really focused on energy and climate. Some of the issues that came up are ‘will sea rise impact power plants in low-lying neighborhoods’. I think the methodology can be extended to other areas.
  • Uma: May be useful to see what other web services are available to make your public presentations more compelling.

Slide: Target Schedule

    • Oct 2011: Workshop (Washington, DC?): can invite selected users, developers and ESIP community to have a dialogue about the user requirements, what the needs are and potential solutions. ESIP could possibly sponsor this workshop.
    • Jan 2012: Architecture Draft (ESIP Meeting): At that point we’ll have more user requirements, needs and scope that can be discussed within the working group.
    • Jul 2010: Online System 1.0 (ESIP Meeting)
    • Jan 2012: Update v2.0 (ESIP Meeting)
  • Tamara: Having extended face-to-face discussion time would be very helpful.
  • Brian: There is this thing called NSF Earth Cube that I think ESIP might be trying to contribute to. There may be a meeting in DC around November that Carol is thinking of sending people to- so that may be a good time to hold the workshop.
  • Karl: One potential date was the week of October 30th- either the 31st of October or that first week of November but they’re still trying to figure out the structure of that meeting... One logistical model that could streamline this is if it had a home in the ITNI group: they can ask for funding.