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Air Quality Workgroup Earth Science Information Partners The ESIP Air Quality Workgroup and its role in a Community Information Infrastructure

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Presentation on theme: "Air Quality Workgroup Earth Science Information Partners The ESIP Air Quality Workgroup and its role in a Community Information Infrastructure"— Presentation transcript:

1 Air Quality Workgroup Earth Science Information Partners The ESIP Air Quality Workgroup and its role in a Community Information Infrastructure http://wiki.esipfed.org/index.php/Air_Quality_Work_Group

2 ESIP Air Quality Workgroup Formerly known as the ESIP AQ Cluster The objective of the ESIP Air Quality Workgroup is to connect air quality data consumers with the providers of those data by:  bringing people and ideas together on how to deliver ES data to AQ researchers, managers and other users  facilitate and demonstrate the information flow among data providers to air quality consumers “Conversation is king. Content is just something to talk about.” -Cory Doctorow Communities of Practice are groups of people who interact about a common activity of interest with the objective of exchanging information, collaborating and learning how to improve that activity Based on definition by Etienne Wenger

3 Interoperability Efforts GALEON ESIP OGC OWS testbeds GEOSS pilots EPA Data Summit Portals / Catalogs NASA Programs/Projects EPA Programs/Projects NOAA Programs/Projects Air Quality Forecasting (Fine, NESDIS) NGDC (Haberman, Kozimor) Hazard Mapping System (Ruminski) REASoN (Friedl, Moe) WRAP (Ambrosia, Sullivan) EDAC (Morain, Benedict, Hudspeth) LAITS (Di, Yang) AQ Web Infrastructure (Husar, Falke) ACCESS (Lindsay, Maiden) Giovanni (GSFC – Kempler) DECISIONS (Friedl) 3D-AQS (Hoffman, Engel-Cox, Prados) RS for BlueskyRAINS (Sullivan, Raffuse) Aura in AQ Forecasting (McHenry) VIEWS/TSS (Shankar, McClure) AIST (Moe) SAMITS (Falke) Sensor Web Architecture & Demo (Mandl) DAACS AMI (Young, Keating) GEO (Young, Washburn, Lyon, Foley) AirNOW (Wayland, Dickerson) AQS OAQPS (Scheffe, Frank, Dimmick, Solomon) IDEA (Szykman) HTAP (Keating) Remote Sensing Gateway (Paulson, Walter) Environmental Science Connector (Kapuscinski) DataFed (Husar) Unidata (Domenico, Ramamurthy) CDE (Ambrosia, Sullivan) Giovanni (Leptoukh, Prados) LAITS (Di) RSG (Paulson) NEISGEI (Falke) VIEWS (McClure) Forest Service Programs/Projects Bluesky (Larkin, Goodrick) The Air Quality Web Landscape (not comprehensive) Mediators GEO Portals Earth Information Exchange (ESIP) Earth Observation Portal (GEO) Geospatial One Stop Environmental Science Connector (EPA) Global Change Master Directory (GCMD) ECHO (NASA) LEAD (NSF) International ESA/KMNI CEOS ACC State Aura in AQ Forecasting (Lamb, Vaughan) RPOs Vermont (Poirot)

4 ESIP Air Quality Workgroup datatools,methods,services AQ Workgroup brings together groups and helps build links among them in order to achieve an effective use of data in decision-making that could not be achieved by any organization acting on its own. datatools,methods,services a) b) c)...... AQ Workgroup aids in reuse of data, processing tools and other services so that projects, programs and agencies avoid the end-to-end burden of developing those capabilities or having to create the connections themselves. users “There is no one specific Internet or multiple Internets; it is a vast, shifting network connecting devices dynamically….No one entity owns it or controls it” - Governer et al., “Web 2.0 Architectures”

5 Recent Examples related to Proposal Responses ESIP AQ Workgroup should not serve as PI or co-PI –rather provide the framework or environment in which the PI, co-PIs and collaborators work among themselves and with others Collaboration Process Example: Response to recent GEO CFP –Because of regular interaction in the AQ Workgroup, two groups preparing an AQ application proposal for India became aware of their respective efforts –Identified ways to combine efforts into single proposal that was more responsive to the CFP and that enhanced each groups –The collaboration in the US also led to discovery of collaborations in India How do we do that kind of discovery, identification, acknowledgement and collaboration with data and other services within an information infrastructure?

6 Registered Community Resources Community Portals Client Applications Client Tier Business Process Tier Community Catalogues Alert Servers Workflow Management Processing Servers Access Tier GEONETCast Product Access Servers Sensor Web Servers Model Access Servers GEOSS Clearinghouse GEO Web Portals GEOSS Common Infrastructure Components & Services Standards and Interoperability Best Practices Wiki User Requirements Registries Main GEO Web Site Architecture Implementation Pilot Augmenting GCI

7 GEOSS Architecture Implementation Pilot Evolving AQ Architecture Web Apps CALPUFF WCS Get Capabilities GetCap To ISO Find Smoke data

8 GEOSS AIP – AQ Upfront Expectations Better awareness across community –Existing interoperability efforts –Complementary projects and programs –Develop collaborations Better understanding and use of proposed standards and gaps –Standardization of intra- and inter-system data exchange –Community-level Standardization (e.g., of parameter codes, etc.) Better use of existing data and services –Make data services available to more users within the air quality community –Acquire additional data sets from other servers –Connect across data services (capture data lineages) –Leveraging and reuse of existing resources through service-chaining –Increased value of existing development investments –Identification of complementary data sources and components for integrated analyses Better understanding of GEOSS and how to contribute and use it –Clarity and agreement on best practices, and approaches – “Killer” scenarios

9 Where do we go next? Engage participation – we don’t have critical mass yet Community-based conventions/best practices –Standards Implementation (defining standards is just part of the process. Implementing them hasn’t received the same attention) –Compliance/conformance engines can help More implementation (keep building on previous efforts) –Get past data registration and search and into use Convey concepts so that everyone sees where they fit in and what’s in it for them –Need to move from abstract to tangible, get past architecture diagrams –Needs to be something others can build on


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