1 exchange network – why should i participate??? whad’ya node? exchange network node mentoring...
DESCRIPTION
3 History In frustration, some states refused to report to national systems or had EPA Regional offices do the work –Data gaps now present Existing and old exchange mechanisms compromised the data quality Staff (data users) may spend up to 50% of their time looking for data – access is limited for all the reasons stated previouslyTRANSCRIPT
1
Exchange Network – Why Should I participate???
Whad’ya Node? Exchange Network Node Mentoring Workshop
Presented by Molly O’Neill
New Orleans, LouisianaFebruary 28-March 1, 2005
2
History• In the past, States had to report data to EPA in
many different formats for each regulatory program– Resource double data entry– Maintenance of interfaces– Tracking changes that EPA made to databases– Staff might need expertise in many different code
languages simply for the exchange processes alone
• EPA national data systems and state data systems not in sync– Huge problem when the press queries a national
database and lists issues with State (e.g., not following up on an issue) that might not be true
3
History• In frustration, some states refused to
report to national systems or had EPA Regional offices do the work– Data gaps now present
• Existing and old exchange mechanisms compromised the data quality
Staff (data users) may spend up to 50% of their time looking for data – access is limited for all the reasons stated previously
4
History of the EN• 2000 Blueprint and 2002 Implementation
Plan provides the conceptual design of the Exchange Network and initial focus areas
• Focus was on Type 1 flows with an understanding that other types of flows could also be supported in the future– Type 1 flows were the State to EPA data
flows
5
Early implementation findings• Other Federal Agencies adopting the
same EN core concepts of utilizing web services and XML language– Homeland Security, Dept of Justice,
Department of Defense, Dept of Health and Human Resources
– Initial technology decisions were the correct ones
– This means, sharing data across agency/department boundaries will/should be much easier
6
Early implementation Findings• The concepts of the EN can be
distributed and used eBusiness/eGoverment– Michigan DEQ demonstrates this with their
eDMR/eDWR data flow from industry to state databases to federal databases automatically
• Cost savings being documented and captured for both the state and industry are a great story (Associated Press article written)
7
Paradigm Shift • Publishing data on the Node provides
unparalleled access to data– Data owner can control access to secure
area where data is published – Owner can provide continuous real time
data to data consumers or users
8
Benefits and Examples• Real time and better access to data
– Pacific Northwest Water Quality Exchange– Linkages between Health and Environmental
Data
A Quick Case Study…..leveraging data published (web service) on Node
Washington Department of Ecology
9
Exchange Data Flow Model
INTERNET
Washington
Oregon
MetadataRegistry
EPA
HostDatabase
Data AccessApplication
NetworkNode
NetworkNodeData
Source
DataSource
NetworkNode Data
Source
Alaska
Idaho
CDX STORETData
Warehouse
.xml
.xml
.xml .xml
.xml
NetworkNode Data
Source
Later…
10
11
DOH EIEIO Application
Fish Tissue Contamination and Birth Defects Assessment Application
Leveraging information published for multiple purposes..how does WA DOH access and
store WA DOE data?
12
DOH EIEIO Application – Screen Shot 1Query Results – List of Studies
13
DOH EIEIO Application – Screen Shot 2DOH EIEIO Application – Screen Shot 2Query ResultsQuery Results
Date Range, Location, Taxon, AnalyteDate Range, Location, Taxon, Analyte
14
Benefits • Using the Exchange Network……
– Much better quality data being exchange• Data Standards embedded in XML Schema• Closely working with State/EPA Data Standards Council
for new standard adoptions to incorporate• Machine to machine – no human data entry mistakes• Schematron verifies business rules for exchange – more
validation– More data can be exchanged among new partners
• Infrastructure can be applied to new data exchange types• New State to state exchanges already occurring
– More timely data• Data can be published and exchanged as soon as
partners agree. Machines do the work!
15
Reflections and Learning• No longer dependent upon making sure
systems can talk – web services are interoperable
• Provides an infrastructure and mechanism to support new data flows between existing and new partners!
• Publishing data in a secure place on the Exchange Network has proven far easier and sets a new paradigm for future data exchanges