Stefan Falke Center for Air Pollution Impact and Trend Analysis Washington University, St. Louis, Missouri Brooke Hemming US EPA/National Center for Environmental.

Slides:



Advertisements
Similar presentations
Air Quality and Health Scenario Stefan Falke, Rudy Husar, Frank Lindsay, David McCabe.
Advertisements

Future Directions and Initiatives in the Use of Remote Sensing for Water Quality.
Chapter 10: Designing Databases
Web Services Implementation Case Study: DataFed Air Quality Data & Services Project Coordinators: Software Architecture: R. Husar Software Implementation:
Chapter 2. Slide 1 CULTURAL SUBJECT GATEWAYS CULTURAL SUBJECT GATEWAYS Subject Gateways  Started as links of lists  Continued as Web directories  Culminated.
Federated PM and Haze Data Warehouse Project a sub- project of (enter your sticker & logo here ) Nov 20, 2001, RBH St. Louis Midwest Supersite Project.
New Approaches to GIS and Atlas Production Infrastructure for spatial data integration: across scales and projects Ilya Zaslavsky David Valentine San Diego.
16 months…. The Visibility Information Exchange Web System is a database system and set of online tools originally designed to support the Regional Haze.
Integrating Historical and Realtime Monitoring Data into an Internet Based Watershed Information System for the Bear River Basin Jeff Horsburgh David Stevens,
Proposal Outline: Extensions to the VIEWS: General CATT Analysis Tool R. Husar, CAPITA Revised, June 26, 2003 Proposed Sub-Projects CATT for VIEWS$20k.
Stefan Falke Center for Air Pollution Impact and Trend Analysis Washington University in St. Louis Networked Data and Tools for Environmental Management.
Data Sources & Using VIVO Data Visualizing Scholarship VIVO provides network analysis and visualization tools to maximize the benefits afforded by the.
Data Mining – Intro.
School of something FACULTY OF OTHER School of Computing FACULTY OF ENGINEERING PROJECT VISTA: Integrating Heterogeneous Utility Data A very brief overview.
Maps of PM2.5 over the U.S. Derived from Regional PM2.5 and Surrogate Visibility and PM10 Monitoring Data Stefan R. Falke and Rudolf B. Husar Center for.
Distributed Data Analysis & Dissemination System (D-DADS) Prepared by Stefan Falke Rudolf Husar Bret Schichtel June 2000.
Select, Overlay, Explore; Multidimensional data Maintain Distributed Data; Heterogeneous coding, access Connect providers to users; Homogenize data access.
Delivery of Forecasted Atmospheric Ozone and Dust for a Public Health Decision-Support System-Architecture and Functionality William B. Hudspeth, Jeff.
AIRNow-International The future of the United States real-time air quality reporting and forecasting program and GEOSS participation John E. White U.S.
Distributed Voyager (DVoy) Web Services
Introduction to Geographic Information Systems (GIS) Lesson 1.
GCMD/IDN STATUS AND PLANS Stephen Wharton CWIC Meeting February19, 2015.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 5-1 Chapter 5 Business Intelligence: Data.
TRLN High Performance Data Storage System 21 Sep 2006 Jim Porto Ken Galluppi.
Ideas on a Network Evaluation and Design System Prepared for EPA OAQPS Richard Scheffe by Rudolf B. Husar and Stefan R. Falke Center for Air Pollution.
EPA’s Role in the Global Earth Observation System of Systems (GEOSS)
REASoN REASoN Project to link NASA's data, modeling and systems to users in research, education and applications Application of NASA ESE Data and Tools.
Data Mining – Intro. Course Overview Spatial Databases Temporal and Spatio-Temporal Databases Multimedia Databases Data Mining.
Spatio-Temporal Data Sharing using XML Web Services Presented at the Workgroup Meeting on Web-based Environmental Information System for Global Emission.
Interoperability & Knowledge Sharing Advisor: Dr. Sudha Ram Dr. Jinsoo Park Kangsuk Kim (former MS Student) Yousub Hwang (Ph.D. Student)
Stefan Falke Center for Air Pollution Impact and Trend Analysis Washington University in St. Louis Brooke Hemming US EPA – Office of Research and Development.
Application of ESE Data and Tools to Particulate Air Quality Management The CAPITA REASoN Project August 15, 2003 Stefan Falke and Rudolf Husar Center.
Supersite Relational Database Project: (Data Portal?) a sub- project of St. Louis Midwest Supersite Project Draft of the November 16, 2001 Presentation.
Accessing and Using Fire-Related Data with the CAPITA DataFed.net* Services Framework Stefan Falke Rudolf Husar Kari Hoijarvi Washington University in.
Air Quality Data Services: Application of OGC specifications Air Quality Data: Multi-dimensional, multi-source, multi-format Point observations are collected.
GEON2 and OpenEarth Framework (OEF) Bradley Wallet School of Geology and Geophysics, University of Oklahoma
NASA Air Quality Applications Program and the ESIP Air Quality Cluster The goal of the NASA Air Quality Management program is to: Enable partners’ beneficial.
Current Project Objectives The project’s focus is on criteria pollutants and toxics because of their availability and accessibility. Recommend and demonstrate.
Select, Overlay, Explore; Integration of diverse data Distributed Data Heterogeneous coding, access Connects providers to users; Homogenize data access.
Stefan Falke and Rudolf Husar Center for Air Pollution Impact and Trend Analysis Washington University in St. Louis A NSF Digital Government Pilot Project.
Shinobu Kawahito JAXA / RESTEC Kengo Aizawa, Satoko Miura JAXA Update on Agricultural Services and Disaster Services projects.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
The Federated Data System, DataFed ESIP Winter MeetingESIP Winter Meeting, Jan 10, 2013, Washington DC Rudolf Husar, Washington University, St. Louis Presented.
COMMUNITY. Data Acquisition and Usage Value Chain.
Distributed Data Analysis & Dissemination System (D-DADS ) Special Interest Group on Data Integration June 2000.
Brooke L. Hemming, Ph.D. US EPA/National Center for Environmental Assessment Stefan Falke, Ph.D. Washington University in St. Louis Terry Keating, Ph.D.
U.S. Environmental Protection Agency Central Data Exchange Pilot Project Promoting Geospatial Data Exchange Between EPA and State Partners. April 25, 2007.
Compilation and Design of a Functioning Distributed Database of North American Electric Generating Emissions Stefan Falke Center for Air Pollution Impact.
Fire Emissions Network Sept. 4, 2002 A white paper for the development of a NSF Digital Government Program proposal Stefan Falke Washington University.
NASA REASoN Project SHAirED: S ervices for H elping the Air -quality Community use E SE D ata Stefan Falke, Kari Höijärvi and Rudolf Husar, Washington.
NASA REASoN Project SHAirED: S ervices for H elping the Air -quality Community use E SE D ata Stefan Falke, Kari Höijärvi and Rudolf Husar, Washington.
Object storage and object interoperability
Processes of the Information Value Chain Informing Knowledge ActionProductive Knowledge Information Organizing Grouping Classifying Formatting Geo-referencing.
Web Services-Based Mediator of Distributed Data Flow and Processing Project Coordinators: Software Architecture: R. Husar Software Implementation: K. Höijärvi.
An Integrated Fire, Smoke and Air Quality Data & Tools Network Stefan Falke and Rudolf Husar Center for Air Pollution Impact and Trend Analysis Washington.
Application of NASA ESE Data and Tools to Air Quality Management Stefan Falke and Rudolf Husar (Co-PIs) Washington University in St. Louis Project Period:
ESIP Air Quality Jan Air Quality Cluster Air Quality Cluster Technology Track Earth Science Information Partners Partners NASA NOAA EPA (?) USGS.
1 SEEDS IT Vision Scenario: Smoke Impact REASoN Project: Application of NASA ESE Data and Tools to Particulate Air Quality Management (PPT/PDF)Application.
Concepts on Aerosol Characterization R.B. Husar Washington University in St. Louis Presented at EPA – OAQPS Seminar Research Triangle Park, NC, April 4,
Application of NASA ESE Data and Tools to Particulate Air Quality Management A proposal to NASA Earth Science REASoN Solicitation CAN-02-OES-01 REASoN:
Harmonization and Integration of Semi- Structured Data Through Wikis and Controlled Tagging E. M. Robinson, R. B. Husar Washington University, St. Louis,
Proposal to MANE_VU: Extensions to the VIEWS: CATT Analysis Tool Full Proposal Text Full Proposal Text R. Husar, PI, CAPITA Revised, October 8, 2003 The.
Concepts on Aerosol Characterization R.B. Husar Washington University in St. Louis Presented at EPA – OAQPS Seminar Research Triangle Park, NC, April 4,
Voyager Data Services Services for Finding, Exploring and Presenting Distributed Environmental Data Outline Prepared by Voyager Interest Group on Environmental.
Fire, Smoke & Air Quality: Tools for Data Exploration & Analysis : Data Sharing/Processing Infrastructure This project integrates.
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION ESDS Reuse Working Group Earth Science Data Systems Reuse Working Group Case Study: SHAirED Services for.
Capacity Building Enhance the coordination of efforts to strengthen individual, institutional and infrastructure capacities, particularly in developing.
EC FP7 - Cooperation Theme 6: Environment (incl. climate change)
Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.
4/5 May 2009 The Palazzo dei Congressi di Stresa Stresa, Italy
Presentation transcript:

Stefan Falke Center for Air Pollution Impact and Trend Analysis Washington University, St. Louis, Missouri Brooke Hemming US EPA/National Center for Environmental Assessment Research Triangle Park, North Carolina Stefan Falke Center for Air Pollution Impact and Trend Analysis Washington University, St. Louis, Missouri Brooke Hemming US EPA/National Center for Environmental Assessment Research Triangle Park, North Carolina Networked Environmental Information System for Global Emissions Inventories ( NEISGEI ) Applying 21 st Century Advances in IT Technology to the Conversion of Air Quality Data into Scientific-, Management- and Policy-Relevant Knowledge

 A conceptual framework for the development of a fully integrated, distributed emissions inventory  Tie together data at all spatial (and temporal) scales  Allow merging and manipulation of any and all web-based, along with your own, air quality-relevant data  Serve the entire air quality community: scientists, regulators, policy analysts and the public Networked Environmental Information System for Global Emissions Inventories NEISGEI

A tool for strategic planning of air quality environmental management capacity building projects  A fully populated network will be a resource for identifying important missing datasets in regional, hemispheric and global scale studies

list of datasets Find/Discover Data AQ data from many distributed and heterogeneous sources MiddlewareUser These data sets meet your criteria metadata 1) Manger asks for data for specific time range and location range 2) The mediator interprets the query and identifies the relevant datasets I need summer, 2002, air quality data for California M E D I A T O R translate request M E D I A T O R send results

Access Data Great! Data sets 1 & 3 are what I need. I would like to view that data Here is the data in a format compatible with your software. dataset data 3) Manager selects subset of interest 4) Wrappers translate the data into a standard format M E D I A T O R translate request Data MiddlewareUser W R A P P E R translate request

Time Series Map View Data 5) Manager would like to see the data in maps and charts Data User T I M E V I E W display data M A P V I E W display data Middleware Viewed in Browser

mapped data fields Map Fields in Data Sets mapper settings Ratio op. settings Ratio 2:3 data set 6) Manager uses the data mapper to automatically create relationships among heterogeneous dataset field names A U T O D A T A M A P P E R map fields from multiple datasets R A T I O O P E R A T O R calculate ratio 7) Using generated field map, manager calculates the ratio between parameter x from data set 2 and parameter y from data set 3

Report Report gen. settings Create Summary Report R E P O R T G E N E R A T O R calculate ratio 8) Manager generates summary reports based on calculated values 2:3 Ratio Other Data

 Network concept introduced at the NSF Digital Government Research Conference 2002  NSF/EPA Workshop  Issues identified: Finding data Integrating data Quantifying data uncertainty  Resulting projects:  CAREN: A CARB-California AQMDs Network (NSF/CARB/EPA) – data wrapping and integration of same type data  Integrated North America Emissions Inventory (CEC)  Fire, Smoke and Air Quality Network (NSF/EPA/USDA) – data wrapping and integration of heterogeneous data plus tools to support environmental management NEISGEI Networked Environmental Information System for Global Emissions Inventories

CAREN: The California Air Resources Network US EPA RPOs AQMDsMunicipalitiesTribesStates ??? Automating the integration of heterogeneous databases:  Government information should be timely, thorough, and accurate.  But government agencies often do not share data effectively with each other or the public  Barrier: Technological incompatibilities  Barrier: Regulatory, organizational and financial barriers  Barrier: Fear of litigation due to inappropriate disclosure Eduard Hovy, Jose-Luis Ambite, Andrew Philpot USC Information Sciences Institute

Previous Work: Energy Data Collection  Employ as reference the Omega ontology: 120,000-term general purpose concept hierarchy  Augment Omega with domain-specific metadata describing energy data series and source characteristics  Use artificial intelligence query planner to provide uniform access to relational and web-based information sources  Successful in incorporating 50,000 data series from six heterogeneous data sources from three different agencies, using semi-automated mappings  Significant manual effort required.  Conclusion: More general methods needed! BLSCEC EIA (NSF Digital Government Program 1999-present)

Machine Translation-inspired Induction for Data Mapping  declared or detected metadata: e.g., field names, database schema, table headers, footnotes  learned data patterns: e.g., domain, range, formats, orthography  topological relationships: e.g., foreign key/subset discovery  terminological reference via ontology or thesaurus FR : Il y a un crayon jaune sur une grande chaise. EN : There is a yellow pencil under a big chair. } } DB1 : Smith, John, 2000 High St, Columbus, OH DB2 : Ohio, Franklin, Smith, 43201, 1108 } } R ecent advances in Machine Translation (MT) have allowed the automatic induction of cross- natural language correspondences from large multi-lingual corpora O ur system will use these techniques to learn cross-database correspondences, based on features such as: parallel French/English sentences (e.g., from Canadian Parliamentary Records) two databases denoting correlating records Emissions inventory databases from the municipal up to hemispheric scales will be integrated into the network automatically using this new technology.

Integrated N. American Emission Inventory The Commission on Environmental Cooperation (CEC) and the US EPA are supporting a project to develop a prototype web tool for enabling uniform access to distributed emissions data from North American electricity generating power plants. Co-investigator: Greg Stella, Alpine Geophysics The prototype tool will help:  Assess data gaps  Identify future IT tools that can aid collaborative emissions inventory project Air pollutant emission inventories for the US, Canada, and Mexico are compiled and stored using different methods

Fire, Smoke and Air Quality Network The US Environmental Protection Agency and USDA-Forest Service are partnering agencies The management of fire, smoke, and air quality is tasked to multiple agencies at federal, state, and local levels. The diversity in data collection methods, data reporting requirements, data formatting schemes, data analysis methods, and data presentation create a daunting challenge for the integration of these data. However, integration of these heterogeneous datasets is precisely what is called for by federal and regional organizations in order to derive a more comprehensive understanding of fire, smoke, and air quality. Co-investigator: Rudolf Husar, Washington U.

Fire, Smoke and Air Quality Network  uniform access to and cataloging of distributed fire related data and tools  easy-to-use interfaces for exploring fire related resources  powerful tools that contribute to fire related data analysis and modeling  a framework that encourages community-wide contributions The fire, smoke, and air quality network will consist of web-based data access and analysis facilities that are flexible and adaptive in meeting the diverse end use requirements of wildland and prescribed fire managers and air quality planners. The network will provide:

Fire, Smoke, and Air Quality Network The map and time views are linked so that changing the focus in one automatically updates the other. For example, clicking on a PM 2.5 monitor in the map displays the time series at that monitor. CIRA ColoState-VIEWS European Space Agency Integration of multiple sources of fire-related data aids in planning, management, and post-fire analysis. Time View Control Panel Generic Map Server NASA SeaWiFS Project Map View

Spatio-Temporal Data Browser Render Spatial Slice Find/Bind Data Time Slice Time Portrayal Spatial PortrayalSpatial Overlay Time Overlay OGC-Compliant GIS Services Time-Series Services PortrayOverlay Homogenizer Catalog Wrapper Mediator Client Browser Cursor/Controller Maintain Data GIS Data Vector XDim Data SQL Table OLAP Satellite Images Data Sources Queries yield slices along the spatial, temporal and parameter dimensions of multidimensional data cubes. Data Cube

What’s possible with NEISGEI ? NetworkedAssessment EvnNetworkedAssessment Evn  In the news: “The Bush administration is to hold an Earth Observation Summit in Washington this summer to which it hopes the G8 group of industrialised countries will send cabinet-level representatives. The US is to urge the world's governments to set up an "integrated Earth observation system" to "take the pulse of the planet". It would combine satellite and ground-based observations of weather, climate, vegetation and other environmental indicators.” ~~Financial Times (London), Friday Jun  NEISGEI will make possible:  Simplified, multi-party, cross-border collaboration in air quality management  Simplified development of environmental indicators, with the inclusion of data available on other environmental media 