In this paper we present, LEAPS, a Semantic Web and Linked data framework for searching and visualising datasets from the domain of Algal biomass. LEAPS provides tailored interfaces to explore algal biomass datasets via REST services and a SPARQL endpoint for stakeholders in the domain of algal biomass. The rich suite of datasets include data about potential algal biomass cultivation sites, sources of CO2, the pipelines connecting the cultivation sites to the CO2 sources and a subset of the biological taxonomy of algae derived from the world's largest online information source on algae

Skarka, Johannes

Solanki, Monika

English

Abstract. In this paper we present, LEAPS, a Semantic Web and Linked data framework for searching and visualising datasets from the domain of Algal biomass. LEAPS provides tailored interfaces to explore algal biomass datasets via REST services and a SPARQL endpoint for stakeholders in the domain of algal biomass. The rich suite of datasets include data about potential algal biomass cultivation sites, sources of CO2, the pipelines connecting the cultivation sites to the CO2 sources and a subset of the biological taxonomy of algae derived from the world’s largest online information source on algae. 

Monika Solanki

Johannes Skarka

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LEAPS: A Semantic Web and Linked data framework for the Algal Biomass Domain

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LEAPS: A Semantic Web and Linked dataframework for the Algal Biomass DomainMonika Solanki1 and Johannes Skarka21 Aston University, UKm.solanki@aston.ac.uk2 Karlsruhe Institute of Technology, ITAS, Germanyjohannes.skarka@kit.eduAbstract. In this paper we present, LEAPS , a Semantic Web andLinked data framework for searching and visualising datasets from thedomain of Algal biomass. LEAPS provides tailored interfaces to explorealgal biomass datasets via REST services and a SPARQL endpoint forstakeholders in the domain of algal biomass. The rich suite of datasetsinclude data about potential algal biomass cultivation sites, sources ofCO2, the pipelines connecting the cultivation sites to the CO2 sourcesand a subset of the biological taxonomy of algae derived from the world’slargest online information source on algae.1 MotivationRecently the idea that algae biomass based biofuels could serve as an alternativeto fossil fuels has been embraced by councils across the globe. Major companies,government bodies and dedicated non-profit organisations such as ABO (AlgalBiomass Organisation) 3 and EABA(European Algal Biomass Association)4 havebeen pushing the case for research into clean energy sources including algaebiomass based biofuels.It is quickly evident that because of extensive research being carried out,the domain itself is a very rich source of information. Most of the knowledge ishowever largely buried in various formats of images, spreadsheets, proprietarydata sources and grey literature that are not readily machine accessible/inter-pretable. A critical limitation that has been identified is the lack of a knowledgelevel infrastructure that is equipped with the capabilities to provide semanticgrounding to the datasets for algal biomass so that they can be interlinked,shared and reused within the biomass community.Integrating algal biomass datasets to enable knowledge representation andreasoning requires a technology infrastructure based on formalised and sharedvocabularies. In this paper, we present LEAPS 5, a Semantic Web/Linked dataframework for the representation and visualisation of knowledge in the domain3 http://www.algalbiomass.org/4 http://www.eaba-association.eu/5 http://www.semanticwebservices.org/enalgaeof algal biomass. One of the main goals of LEAPS is to enable the stakeholdersof the algal biomass domain to interactively explore, via linked data, potentialalgal sites and sources of their consumables across NUTS (Nomenclature of Unitsfor Territorial Statistics)6 regions in North-Western Europe.Some of the objectives of LEAPS are,– motivate the use of Semantic Web technologies and LOD for the algal biomassdomain.– laying out a set of ontological requirements for knowledge representationthat support the publication of algal biomass data.– elaborating on how algal biomass datasets are transformed to their corre-sponding RDF model representation.– interlinking the generated RDF datasets along spatial dimensions with otherdatasets on the Web of data.– visualising the linked datasets via an end user LOD REST Web service.– visualising the scientific classification of the algae species as large networkgraphs.2 LEAPS DatasetsThe transformation of the raw datasets to linked data takes place in two steps.The first part of the data processing and the potential calculation are performedin a GIS-based model which was developed for this purpose using ArcGIS 79.3.1. The second step of lifting the data from XML to RDF is carried out usinga bespoke parser that exploits XPath 8 to selectively query the XML datasetsand generate linked data using the ontologies.The transformation process yielded four datasets which were stored in dis-tributed triple store repositories: Biomass production sites, CO2 sources, pipelinesand region potential. We stored the datasets in separate repositories to simulatethe realistic scenario of these datasets being made available by distinct and ded-icated dataset providers in the future. While a linked data representation of theNUTS regions data 9, was already available there was no SPARQL endpoint orservice to query the dataset for region names. We retrieved the dataset dump andcurated it in our local triple store as a separate repository. The NUTS datasetwas required to link the biomass production sites and the CO2 sources to re-gions where they would be located and to the dataset about the region potentialof biomass yields. The transformed datasets interlinked resources defining sites,CO2 sources, pipelines, regions and NUTS data using link predicates defined inthe ontology network.Datasets about algae cultivation can become more meaningful and useful tothe biomass community, if they are integrated with datasets about algal strains.6 http://bit.ly/I7y5st7 http://www.esri.com/software/arcgis/index.html8 http://www.w3.org/TR/xpath/9 http://nuts.geovocab.org/This can help the plant operators in taking judicious decisions about whichstrain to cultivate at a specific geospatial location. Algaebase10 provides thelargest online database of algae information. While Algaebase does not makeRDF versions of the datasets directly available through its website, they canbe programmatically retrieved via their LSIDs (Life Science Identifiers) fromthe LSID Web resolver 11 made available by Biodiversity Information Standards(TDWG)12 working group.We retrieved RDF metadata for 113061 species of algae13 and curated in ourtriple store. We then used the Semantic import plugin with Gephi to visualisethe biological taxonomy of the algae species.3 System DescriptionLEAPS provides an integrated view over multiple heterogeneous datasets of po-tential algal sites and sources of their consumables across NUTS regions in North-Western Europe. Figure 1 illustrates the conceptual architecture of LEAPS . TheFig. 1. Architecture of LEAPSmain components of the application are10 http://www.algaebase.org/about/11 http://lsid.tdwg.org/12 http://www.tdwg.org/13 The retrieval algorithm ran on an Ubuntu server for three days– Parsing modules: As shown in Figure 1, the parsing modules are responsi-ble for lifting the data from their original formats to RDF. The lifting processtakes place in two stages to ensure uniformity in transformation.– Linking engine: The linking engine along with the bespoke XML parseris responsible for producing the linked data representation of the datasets.The linking engine uses ontologies, dataset specific rules and heuristics togenerate interlinking between the five datasets. From the LOD cloud, wecurrently provide outgoing links to DBpedia14 and Geonames15.– Triple store: The linked datasets are stored in a triple store. We useOWLIM SE 5.0 16.– Web services: Several REST Web services have been implemented to pro-vide access to the linked datasets.– Ontologies: A suite of OWL ontologies for the algal biomass domain havebeen designed and made available.– Interfaces: The Web interface provides an interactive way to explore variousfacets of sites, sources, pipelines, regions, ontolgoies and SPARQL endpoints.The map visualisation has been rendered using Google maps. Besides theSPARQL endpoint and the interactive Web interface, a REST client hasbeen implemented for access to the datasets. Query results are available inRDF/XML, JSON, Turtle and XML formats.4 Application accessLEAPS 17 is available on the Web. The interface currently provides visualisationand navigation of the algae cultivation datasets in a way most intuitive for thephycologists. The application has been demonstrated to several stakeholders ofthe community at various algae-related workshops and congresses. They havefound the navigation very useful and made suggestions for future dataset ag-gregation. At the time of this writing, data retrieval is relatively slow for somequeries because of their federated nature, however optimisation work on theretrieval mechanism is in progress to enable faster retrieval of information.AcknowledgmentsThe research described in this paper was partly supported by the Energetic Algaeproject (EnAlgae), a 4 year Strategic Initiative of the INTERREG IVB North WestEurope Programme. It was carried out while the first author was a researcher at BCU,UK.References14 http://dbpedia.org/About15 http://sws.geonames.org/16 http://www.ontotext.com/owlim/editions17 http://www.semanticwebservices.org/enalgae

LEAPS:a semantic web and linked data framework for the Algal biomass domain

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