building ontologies for algal biomass operations 2012
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monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Building Ontologies forAlgal Biomass Operations
Monika SolankiKnowledge Based Engineering Lab
Birmingham City University, UK
June 13, 2012
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Outline
1 Motivation
2 Minimum Descriptive Language (MDL)
3 Ontology Development for Algal Biomass Production
4 Working Demo
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Outline
1 Motivation
2 Minimum Descriptive Language (MDL)
3 Ontology Development for Algal Biomass Production
4 Working Demo
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Outline
1 Motivation
2 Minimum Descriptive Language (MDL)
3 Ontology Development for Algal Biomass Production
4 Working Demo
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Outline
1 Motivation
2 Minimum Descriptive Language (MDL)
3 Ontology Development for Algal Biomass Production
4 Working Demo
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Algae as a source of food
Microalgae as a food source for humans has beenconsidered for overpopulated countries and for spacetravel since as early as 1961.If algae is grown under proper environmental conditions,the protein yield from it may be quite high.Algae have been collected for more than 4000 years inChina and Japan for use as human food.Spirulina algae is considered to be one of the mostnutritious food on the planet.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Algaculture
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Algaculture
Algal production operations can be quite diverse in the sizeof the plant and the scope of their produce.They vary from small units producing specialty chemicalsand nutraceuticals to large scale farms involved in theproduction of food products and biofuels.This diversity makes a uniform analysis of algalproductivity a challenging endeavour.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
EnAlgae: Energetic Algae
Aims to reduce CO2 emissions and dependency onunsustainable energy sources in North West Europe.4 Year Strategic initiative of Interreg IVb NWE programme.
19 partners and 14 Observers across 7 EU states.
Coordinated set of activities focussing on sharing bestpractice, developing effective stakeholder engagement andencouraging transnational cooperation.
http://www.enalgae.eu/
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
EnAlgae: Some of the objectives
Accelerate development of sustainable technologies forBiomass production.Create a network of pilot scale algal facilities across NWEin order to address the current lack of verifiable informationon algal productivity.Maintain an up to date inventory in which pilots collect andshare data in a standardised manner.Combine information across the entire algal bioenergydelivery chain into a comprehensive and user friendlyDecision Support System for practitioners, policy makersand investors
http://www.enalgae.eu/
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
The problem
Lack of a unified underlying standard that provides a set ofmetrics to facilitate a uniform and accurate assessment ofthe economic and environmental footprint of theoperations.Lack of a shared, accumulative and consistent knowledgebase that can support funding bodies and investmentstakeholders in making decisions.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Algal Supply Chain
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
The Potential for Ontologies across the Algalsupply chain
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Minimum Descriptive Language(MDL)
Standard developed by the Algal Biomass Organisation(ABO),To uniformly capture the footprint of an algal productionoperation.To eliminate the prevailing heterogeneity in the recording ofplant-specific metricsTo facilitate the generation and sharing of a uniform andconsistent knowledge baseTo harmonise the terminology to be used acrossproduction operations and stakeholders.
http://www.algalbiomass.org/
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Minimum Descriptive Language (MDL)
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL
Advantages of building ontologies from standards
Already built-in-consensus on the use of key domainspecific terminologiesMinimal semantic loss as standards informally include therelationships between concepts and ease of knowledgetransfer.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Scope of OntoMDL
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Ontology Development Methodology
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Ontology Lifecycle
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Ontology Lifecycle: Phases
Guided by the Neon project,InceptionKnowledge AcquisitionAssessmentDesignImplementation
http://www.neon-project.org/
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Knowledge Acquisition Phase
An algal production unit can bea newly established plant with no access to knowledgebases from existing plants (Competitive markets can drivethe situation).a newly established plant which has access to and wouldlike to benefit from knowledge bases acquired fromexisting plants.an existing plant which would like to benefit from a wellrecorded history of knowledge bases.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Assessment Phase
Assessment of identified standards, assessing otherontologies identified for reuse.Merging ontologies, reengineering ontologies.Refrain from using NLP techniques in the initial iterations.A detailed perusal of the standards by knowledgeengineers, guided by domain experts, for knowledgeextraction.Iterative evolution of the standards based on the ontologiesdeveloped.
After a few iterations of the standards-ontology mapping, NLPtechniques guided by the lessons learned can be explored.
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL Conceptualisation
Core ConceptsProcessInput
ProcessOutput
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL Conceptualisation
SpecialisationProcess Input
CarbonInputEnergyInputWaterInput
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL Conceptualisation
SpecialisationProcess Output
ConstituentProductIndirectProductLiquidWaste
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL: Additional Conceptualisation
Background KnowledgeAlgalOperationUnit
AlgalOperationProcess
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
OntoMDL
monika.solanki@bcu.ac.uk Semantic Web and Agri-Food, 13th June 2012
Working Demo
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