1. Ontological Framework for Enabling Free-Form Search in Scientific Discovery
Chaitali Gupta, Madhusudhan Govindaraju
Grid Computing Research Laboratory
SUNY Binghamton
5/5/2019
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:

2. Motivation Most computer users today do not have to write programs
most end users of Grid and scientific data sets should be shielded from low-level details
Web Search engines search billions of web pages
use Natural Language Processing (NLP) and Information Retrieval (IR) technologies
return many links for any given search
XML based technology and ontologies can be used to categorize and organize information
machine-readable and understandable manner
retrieve specific information from Grid/scientific services.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

3. Project Vision
Our vision is that Web semantics can be leveraged to build search engine like interfaces even for Grid/Scientific Application Meta-Data.
abstract away the fundamental complexity of XML based services specifications and toolkits
Add a search box on portal dashboards
Automatically convert queries to Job description specification formats
All these related schemes work well for scientists who have a working knowledge of the query system. Our work extends the features provided by these systems with a free-form query based interface that provides ease-of-use for domain scientists without requiring them to learn any specific XML technology or query language details.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

4. Related Work
MDS.
WSRF compliant service to publish/retrieve resource information
Condor ClassAds.
Combines schema, data, and query in a simple but powerful query specification language.
Condor Gangmatching.
Overcomes bilateral matching limitations of the ClassAds.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

5. Comparing with SPARQL SPARQL Query Query in the Proposed Framework
PREFIX dc:<
PREFIX ns:<
SELECT ?machine-name    ?CPU
WHERE { ?x  ns:cpu ?cpu.
FILTER (?cpu   >   2.0).
?x dc:machine-name ?machine-name. }
“All machine names with CPU speed greater than 2.0 GHz”
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

6. Scope of Free-Form Queries
The problem of processing and acting upon arbitrary English is an extremely challenging
actively addressed in the AI community
Use many techniques from NLP and semantic web
Scope of our work is therefore limited
cannot accept any free-form query
designed to accept a limited form of English with a vocabulary taken from the ontology.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

7. Example queries for New York State Grid (NYSGrid)
List all sites of NYSGrid
All Sites of NYSGrid with Xeon processors
Processor configuration of nodes at Binghamton site of NYSGrid
All machine names in NYSGrid with CPU speed greater than 2.0GHz speed
Status of job ID 117 running on NYSGrid
Names of 16 free nodes on the NYSGrid with at least 4GB of memory
List all nodes of NYSGrid having CPU speed greater than 1Ghz and less than 4 Ghz
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

8. Example ontology model
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

9. System Components WSDL Processor User Query Interface Query Processor
Match Processor
Ontology Matcher
Dictionary Matcher
direct, stripped matching, hypernyms, hyponym
Lexicon
how people use words etc.
Relevance Checker
Glossary, input and output parameters of the Web service
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

10. Example query that lights up the model
The Ontology Matcher retrieves the ontologies from the ontology repository and matches them with the user query.
Ontologies built in OWL for storing the vocabularies
concepts include “CPU”, “memory”, “storage”, “job”, etc.
use Jena to process OWL models/statements
<subject, object, predicate>
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

11. System Components
Queries that hit Ontology Matcher have an average of 95% - 96% better performance benefit than those requiring both Ontology and Dictionary Matcher.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

12. Performance of System Components
Execution time taken by the major components
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

13. System Components
Recall and Precision increases when domain dependent ontologies are considered.
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019

14. Research Challenges
Design algorithms to automatically infer the context of user queries and map them to an appropriate set of Grid and scientific services.
Automatically extend and update domain knowledge using Semantic Web techniques and WordNet.
Build a feedback loop for cases that don’t work
Enable construction of simple workflows
multiple Grid services may be needed for a query
merging results from different services
E-science Microsoft Workshop 2008: Semantics Birds of a Feather Session:
5/5/2019