20110614JCDL2011LeidigPosterx - Edward A. Fox

hordeprobableBiotechnology

Oct 4, 2013 (3 years and 8 months ago)

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Ontology Classifications










Acknowledgement





Abstract

Content from simulation systems is useful in defining domain ontologies. We
describe a digital library process to generate and leverage domain ontologies to
support simulation systems tasks. Workflow ontologies may be used to define
compositions of simulation
-
related services. Simulation model ontologies may be
used in customizing collection management systems for tasks such as organization,
interface construction, and metadata record generation.

Improving Simulation Management Systems through Ontology Generation and Utilization

Targeted Simulation Systems












Jonathan P. Leidig, Edward A. Fox, Kevin Hall, Madhav Marathe, Henning Mortveit

Contact:
leidig@vt.edu

Simulation Workflows










Ontology Generation and Technologies




















Model Ontology
-
Utilizing Digital Library Services






This work has been partially supported by NSF SDCI Grant OCI
-
1032677, NSF Nets
Grant CNS
-
062694, CNS
-
0831633, HSD Grant SES
-
0729441, CDC Center of Excellence in
Public Health Informatics Grant 2506055
-
01, NIH
-
NIGMS MIDAS GM070694
-
05/06, and
DTRA CNIMS Grant HDTRA1
-
07
-
C
-
0113.

Related Article:



Jonathan Leidig, Edward Fox, Kevin Hall, Madhav Marathe, Henning Mortveit. SimDL: A Model Ontology Driven Digital
Library for Simulation Systems. ACM/IEEE Joint Conference on Digital Libraries, Ottawa, Canada, June 13
-
17, 2011.

Prototype Implementation & Applications Supported










Swiss Tropical Institute


Malaria models


Dataset analysis


Cyberinfrastructure Network Science


Network simulations


Network analysis


Content staging


Interface presentation of model parameters


Input parameter gathering


Input configuration generation


Input configuration validation


Input, result, and analysis storing and retrieving


Gathering provenance from workflow stages


Model
-
specific indexing


Faceted browsing


Ranked searching

Ontology Formats


XML schema


RDF

Ontology Generation


Human
-
intensive model ontology
generation


Metadata description set generation
software


Harmonization yields context
-
specific
ontologies

Harmonization


RDF descriptions


Software guided human mapping

Ontology Terms


Dublin Core terms


Infrastructure and collection
-
level terms


5S framework terms


Model and context
-
specific terms

Schema

Input

Configuration

Output Result

Dataset

Simulation

Process

Analysis

Analysis

Process

Documentation

Annotation

Experiment

Epidemiology Applications


Malaria models


Influenza models


ODE and agent
-
based models


Models from NIH MIDAS community


Models from Gates Foundation
community

Analysis applications


Network analysis


Model
-
specific analysis


Digital Library Integration


Institutional infrastructure


Network science cyberinfrastructure

Virginia Bioinformatics Institute

Biological domains


Infectious diseases (e.g., H1N1, H5N1)


Biological organs

Infrastructure domains


Transportation systems


Computer and wireless networks

Simulation model ontology

Input
schema

Result
schema

Validation

Compatible

a
nalyses

Language

s
upport

Model
ontology

relationships

(e.g., malaria,

influenza)

Model

ontology

Model

ontology

Model

ontology

Context
-
specific ontology

Context ontology

relationships

(e.g., epidemiology,
network science)

Context

ontology

Context

ontology

Context

ontology

Domain
-
specific meta
-
ontology

Recommending


and Selecting

Model
-
Specific

Ontologies

Model Ontology

Harmonization

Context
-
Specific

Ontologies

Context Ontology

Harmonization

Domain Meta

Ontologies

Sample Content

Input Files

Result


Summaries

Analyses

Result Files

Products

Model
-
Specific

Description Sets

Harmonized

Description Sets

Example Records

(XML, RDF)

DB
Metadata

Schemas (DDL)