1. One Language. One Enterprise.™
EPA Pilot for Children’s Health
May 19, 2004 1
© Unicorn Solutions Inc.
February 5, 2019

2. The Problem
Children are extremely susceptible to environmental contaminants
Professional & public expect up-to-date health and environmental data and the ability to reason about it
E.g. to assess a risk may need to combine contamination data with data on extent of exposure with health data on risk levels etc.
But health and environmental data comes from many sources
Vocabulary may be unfamiliar and inconsistent
No single place to ask broad questions
No ability to infer using multiple data sources simultaneously
Finding & combining data is time consuming and error-prone
Data availability and formats may vary over time

3. Vision: Semantics for Government
Key Elements:
Business Analysis
Identify data sources that will need semantic meaning
Metadata
A catalog of relevant data sources across multiple technology formats and platforms – legacy, RDBMS, XML, Excel, documents
Information Model (“Ontology”)
A common language for talking about issues relating to a particular government agency - formally captured in an Information Model (or an “ontology”)
Semantics
Relevant data sources will have their own proprietary “data languages” mapped to the common language to capture their objective “meaning”
Query
Federated query technology will be used to turn all data sources into a single virtual database which will use the common language

4. Using IBM Information Integrator
Unicorn System: SIM Technology
Using IBM Information Integrator

5. Import and Catalogue Metadata
Automate the import of Technical Metadata.
Wide selection of supported common data sources (others are easily customizable).
Capture Technical Metadata- E.g. tables, columns and data types.
Add business metadata (descriptors) to document non-technical source information.

6. Information Model- One Language
Rich, Central, Neutral Business Language.
Object Oriented Model with Classes and Properties.
Enrich the model to fully describe the business:
Descriptors
Conversional business rules
Lookup tables

7. Semantic Mapping
Map each asset once only as a spoke to information model hub
Formal semantic mappings capture meaning of data in formal machine-readable form
Flexibility of Mapping
Map all assets: relational, XML, legacy, etc. to same model
Map groups (e.g. tables) and fields (e.g. columns)
Attach conditions to mapping

8. Semantic Discovery
Find all physical data relating to a business concept
Explore indirect relationships
Data which is a subset/superset
Data related by business rules
Expose redundancy
Apply business policy (E.g. Data Privacy regulations) consistently
Reasoning details

9. Semantic Comparison Semantically compare any two asset schemas
Look for overlaps
Find synonyms and concepts related by business rules
Support integration activities
Reasoning details

10. Graphical Reporting Generate reports on any metadata concept.
Drill down on graphical reports to determine the source assets for each statistic.

11. Query the Business Data
Natural language query tool
Query business data without understanding the underlying data sources
Add Selection criteria using business (not technical) vocabulary
Join data from disparate technology formats and platforms
Easy access and fast retrieval

12. Key Benefits to Government
Aggregate data from disparate sources
Common language for professionals and the public
Ad-hoc queries across multiple sources
Manageability to support changes in data sources, language and rules
Quality of information is increased (accuracy, clarity)
Flexibility to discover information quicker
Cost savings over traditional data warehouse technologies

13. For Further Details … Unicorn Federal Operations Loren Osborn
Phone: (703)
Mobile: (703)
Jeff Eisenberg
Phone: (866) 2 UNICOR(N) x124