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A Knowledge-Centric E-Research Platform for Marine Life and Oceanographic Research

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A Knowledge-Centric E-Research Platform for Marine Life and Oceanographic Research A KNOWLEDGE-CENTRIC E-RESEARCH PLATFORM FOR MARINE LIFE AND OCEANOGRAPHIC RESEARCH Ali Daniyal, Samina Abidi, Ashraf AbuSharekh, Mei Kuan Wong and S. S. R. Abidi Department of Computer Science, Dalhousie University, 6050 Univeristy Ave, Halifax, Canada Keywords: e-Research, Knowledge management, Web services, Marine life, Oceanography. Abstract: In this paper we present a knowledge centric e-Research platform to support collaboration between two diverse scientific communities—i.e. Oceanography and Marine Life domains. The Platform for Ocean Knowledge Management (POKM) offers a services oriented framework to facilitate the sharing, discovery and visualization of multi-modal data and scientific models. To establish interoperability between two diverse domain, we have developed a common OWL-based domain ontology that captures and interrelates concepts from the two different domain. POKM also provide semantic descriptions of the functionalities of a range of e-research oriented web services through a OWL-S service ontology that supports dynamic discovery and invocation of services. POKM has been deployed as a web-based prototype system that is capable of fetching, sharing and visualizing marine animal detection and oceanographic data from multiple global data sources. 1 INTRODUCTION (POKM)—that offers a suite of knowledge-centric services for oceanographic researchers to (a) access, To comprehensively understand how changes to the share, integrate and operationalize the data, models ecosystem impact the ocean’s physical and and knowledge resources available at multiple sites; biological parameters (Cummings, 2005) (b) collaborate in joint scientific research oceanographers and marine biologists—termed as experiments by sharing resources, results, expertise the oceanographic research community—are seeking and models; and (c) form a virtual community of more collaboration in terms of sharing domain- researchers, marine resource managers, policy specific data and knowledge (Bos, 2007). makers and climate change specialists. POKM is To support the oceanographic research supported by the CANARIE network (Canada’s high community we have developed a collaborative e- bandwidth network) that enables the rapid collection research platform to enable the timely sharing of (i) and integration of high-volume oceanographic data multi-modal data collected from different and knowledge (in text format) from distributed geographic sites, (ii) complex simulation models sites, and to broadcast the high-dimensional results developed by specialized research teams; (iii) high- to users across the world (Barjak, 2006). dimensional simulation results, generated by The design approach for POKM is to integrate specialized simulation models, reflecting the local Knowledge Management (KM) technologies with dynamics of specific geographic regions; and (iv) Service Oriented Architectures (SOA). In order to textual knowledge resources—i.e. research articles, meet the abovementioned functional capabilities of reports, news and case studies. the e-research platform—i.e. POKM—we pursued a We propose a knowledge management approach high-level abstraction of ocean and marine science to complement observation-based research programs domains to establish a high-level conceptual with high-level knowledge-based models to assist interoperability between the two domains. This is researchers in establishing the causal, associative achieved by developing a rich domain ontology that and taxonomic relations between raw data, modelled captures concepts from both domains and observations and published knowledge. interrelates them to establish conceptual, We present an e-research platform termed terminological and data interoperability. To define Platform for Ocean Knowledge Management the functional aspects of the e-research services we Daniyal A., Abidi S., AbuSharekh A., Kuan Wong M. and S. R. Abidi S.. 363 A KNOWLEDGE-CENTRIC E-RESEARCH PLATFORM FOR MARINE LIFE AND OCEANOGRAPHIC RESEARCH. DOI: 10.5220/0003101703630366 In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2010), pages 363-366 ISBN: 978-989-8425-30-0 Copyright c 2010 SCITEPRESS (Science and Technology Publications, Lda.) KMIS 2010 - International Conference on Knowledge Management and Information Sharing have developed a services ontology that provides a classes: ALGAE and SEAGRASSES. Plankton has three semantic description of knowledge-centric e- sub-classes representing three functional groups of research services. These semantic descriptions of the planktons: BACTERIOPLANKTON, PHYTOPLANKTON e-research services are used to both establish and ZOOPLANKTON. correlations between domain and functional ANIMALDETAIL represents all the necessary concepts that are the basis for data and knowledge information to build a marine animal profile. It has sharing, cataloguing and visualization. five main sub-classes: AGE, LIFESTAGE, In this paper, we present the knowledge MOVEMENTBEHAVIOR, SEX, TAGID. AGE represents management functionalities achieved through the the age of the animal. LIFESTAGE represents the definition of the domain and service ontologies. current stage of the animal in life, e.g. adult, juvenile, sub-adult etc. MOVEMENTBEHAVIOR represents various movement behaviors of marine 2 KNOWLEDGE RESOURCE animal that are captured by its sub-classes: BEHAVIORALSWITCHING, DISPERSAL, DIVING, LAYER DRIFT, FORAGING, MIGRATING and MOVEMENTPATTERN. The knowledge resource layer constitutes: TAXONOMY represents nine main taxonomic • Data repositories for ocean data, marine life data ranks used to categorize marine organisms as and simulated data generated through various follows: CLASS, FAMILY, GENUS, KINGDOM, ORDER, simulations. PHYLUM, SCIENTIFICNAME, • Domain-specific knowledge represented as SCIENTIFICNAMEAUTHOR and SPECIES. research papers and technical reports. TAXONID describes an organism in terms of the • Domain-specific information represented as above mentioned nine taxonomic ranks. images, movies, audio and posters. MARINELIFEDATA represents various aspects of • Simulation models shared by the researchers. the data about the marine organisms. These include temporal data represented by sub-classes: 2.1 Ontological Modeling of the DAYCOLLECTED, MONTHCOLLECTED, Domain YEARCOLLECTED, DATELASTMODIFIED and TIMESTAMPCOLLECTED, which has two sub-classes The domain ontology in POKM serves as the formal of its own: ENDTIMESTAMPCOLLECTED and semantic description of the concepts and STARTTIMESTAMPCOLLECTED. The class relationships pertaining to the Marine Biology and MARINELIFEDATA is also used to represent concepts the Oceanography domain. POKM provides a core related to the cache of the marine data that is ontology that contains concepts necessary for represented using sub-classes such as CACHEID, modelling Marine Animal Detection Data (MADD), RECORDLASTCACHED, BASISOFRECORD and Oceanography Data, data transformations and RESOURCEID. interfaces of the web services in POKM. MARINELIFEDATACOLLECTION is a class the The taxonomic hierarchy of the domain ontology properties of which are used to capture all the data constitutes 20 highest level classes.; 15 of these represented by class MARINELIFEDATA. classes are further decomposed into sub-classes at the lower levels of hierarchy. 2.3 Modeling Ocean Sciences 2.2 Modelling Marine Sciences The classes to model ocean sciences include: OCEANREGION, OCEANPARAMETER, There are six upper level classes related to marine SATELLITEINFORMATION, INSTRUMENT, MEASURE, sciences—i.e. MARINEORGANISM, ANIMALDETAIL, MOVEMENTMODEL, MODELATTRIBUTE, FILETYPE, TAXONOMY, TAXONID, MARINELIFEDATA, OCEANREGION represents all ocean regions MARINELIFEDATACOLLECTION, DATASOURCE, categorized by five main sub-classes: DATAFORMAT. ARCTICOCEAN, ATLANTICOCEAN, INDIANOCEAN, MARINEORGANISM represents all marine PACIFICOCEAN and SOUTHERNOCEAN. Each of these animals, plants and plankton via classes classes are further sub-divided into sub-classes MARINEANIMAL, MARINEPLANT and PLANKTON representing sub regions of the each ocean region. respectively. There are four main subclasses of OCEANPARAMETER represents all the MARINEANIMAL: FISH, MARINEMAMMAL, REPTILE geophysical parameters used to describe an ocean and SEABIRD. MARINEPLANT has two main sub- 364 A KNOWLEDGE-CENTRIC E-RESEARCH PLATFORM FOR MARINE LIFE AND OCEANOGRAPHIC RESEARCH environment. These are modeled as sub-classes of SPATIALRESOLUTIONUNIT, SPATIALUNIT, this class and include parameters about: TEMPERATUREUNIT, TIMEUNIT, VELOCITYUNIT. • Air, such as: AIRTEMPERATURE, • Wind, such as: WINDGUST, WINDSPEED, 2.4 Relationships Between Classes EASTWARDWIND, NORTHWARDWIND, UPWARDWIND and WINDFROMDIRECTION In addition to providing semantics for modelling • Water, such as: WATERDEPTH, different resources on the POKM system, the WATERTEMPERATURE, SALINITY and DENSITY, purpose of the domain ontology is to inter-relate the • Current, such as: CURRENTTODIRECTION, domains of Marine Sciences and Ocean Sciences. EASTWORDCURRENT, NORTHWARDCURRENT, There are seventy seven object properties and six FLOWVELOCITY and UPWARDCURRENT datatype properties. We describe only the salient • Sea Layers, such as: SEASURFACEELEVATION, properties are described in this section. SEASURFACETEMPERATURE and THERMOCLINE The class MARINEANIMAL (sub-class of SATELLITEINFORMATION represents the satellite MARINEORGANISM) is related to respective sub- used to monitor the oceans, represented in terms of classes of the class MARINELIFEDATA through
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