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A knowledge base system for multidisciplinary model-based water management

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A knowledge base system for multidisciplinary model-based water management
    A knowledge base system for multidisciplinary model-basedwater management Ayalew Kassahun a and Huub Scholten   a  Information Technology Group, Department of Social Sciences, Wageningen University, The Netherlands(ayalew.kassahun@wur.nl) Abstract: To improve the quality of multidisciplinary model-based water management studies and provideguidance on best practices, a user-friendly guidance and quality assurance knowledge-based system hasbeen built within the EU funded HarmoniQuA project. The knowledge base system provides experts andexperienced persons in model-based water management studies a web-based software tool for developingknowledge base for processes related to managing model-based water management studies. The knowledgebase is used in the Modelling Support Tool, a tool developed within the HarmoniQuA project, to providemultidisciplinary team members targeted and actionable information. MoST also uses the knowledge base as aprocess specification in managing model-based study projects. In the HarmoniQuA project, quality assuranceprocedures has been developed with the help of this system and currently we are extending our KBS todevelop a water stress mitigation process for the EU funded AquaStress project. The knowledge base systemis based on ontological formalisation that consists of knowledge models for specifying process definitionsand knowledge models for the execution of the process. This paper focuses on the knowledge models and aweb-based software system we developed to edit and manage the knowledge base. The knowledge models aredeveloped by a team of experts and experienced persons in model-based water management studies and ateam of knowledge and software engineers. In a separate paper, we look at how these knowledge models areused in managing multidisciplinary model-based water management projects. Keywords : process knowledge base, knowledge acquisition, quality assurance procedure 1.   INTRODUCTION The HarmoniQuA (Harmonising Quality Assurancein model based catchments and river basinmanagement) project is an EU funded project withthe objective of providing a user-friendly qualityassurance (QA) framework. This qualityassurance framework includes: (1) a scientificallybased methodology for generic and domainspecific QA procedures and (2) software tools fororganising knowledge in a structured database tosupport modellers and water managers throughoutthe QA process [Scholten and Osinga, 2002,HarmoniQuA, 2006].Problems related to methodology in model-basedwater resources management that the HarmoniQuAproject set out to address include, among others,lack of mutual understanding due to ambiguousterminology, insufficient consideration of socio-economic, institutional and political issues, andlack of documentation and transparency[Refsgaard and Henriksen, 2004, Refsgaard et al .,2005, Scholten et al ., 2006]. To solve theseproblems a QA procedure and software tools weredevelopedIn the HarmoniQuA project, first a number of state-of-the-art modelling guidelines and procedureswere evaluated. These include Good ModellingPractise [Van Waveren, et el ., 1999], Bay-Deltawater and environmental modelling protocols[BDMF, 2000] and Murray-Darling basin’scommission groundwater flow modelling guideline[Middlemis, 2000]. Then a new QA procedure wasdeveloped based on the existing ones and newexperiences and insights gained in recent years.Most of those QA procedures evaluated and thenew HarmoniQuA procedures use a process-oriented approach in specifying QA procedures.The process approach is based on the belief thatthe desired goal is achieved more efficiently whenactivities are managed as process [ISO 9000, 2004].In fact, organizations that wished to be certified for  attaining the ISO quality standard must identifyand manage the processes that make up theirquality management systems [ISO 9001:2000, 2001].We developed a knowledge-based system thatsupports the development of QA procedures. Wehave since then extended the system to supportany processes in model-based study projects. Inthe context of the HarmoniQuA project, theknowledge base system allows experts to organiseexpert knowledge on the QA procedures requiredto guarantee the quality of model-based studies.The HarmoniQuA Modelling Support Tool(MoST), on the other hand, serves other types of users, namely users of the expert knowledge. Thetool serves these group of users by guiding themin there work and managing their activities byallowing them to record their activities andgenerating customizable reports [Kassahun et al. ,2004].The knowledge base system is a general-purposeprocess knowledge base tool that has successfullybeen applied in developing quality assuranceprocedures. Currently we are using the system todevelop the water stress mitigation process for theEU funded AquaStress project. In this paper, weexplain the requirements, design andimplementation of the knowledge base system. Aseparate paper explains in detail how MoSTsupports multidisciplinary model-based watermanagement projects. 2.   PROCESS KNOWLEDGE SYSTEM ANDITS ONTOLOGICALREPRESENTATION There is no commonly accepted definition of knowledge-based systems [Hendriks and Vriens,1999, Gallupe, 2001.] For the purpose of this paper,we define knowledge base as a machine readableand –interpretable collection of information and a knowledge-based system as a software system thatfacilitates acquisition and maintenance of knowledge from experts and makes that knowledgeaccessible to novice users and other experts[Kassahun et al. , 2004.]Ontologies provide means of modelling andrepresenting knowledge in formats that can beeasily understood by humans and interpreted bycomputer programs. One of most widely useddevelopment platforms for ontology-basedsystems is Protégé. Originally developed to reducethe knowledge-acquisition bottleneck, Protégé hasdeveloped into a general-purpose environment forknowledge modelling [Gennari et. al, 2003].We choose Protégé as our base framework for anumber of reasons, among others: it’s modular andextensible architecture, the availability of severalready made extensions called plug-ins and the factthat it is an ‘open source’ project backed by a largecommunity of active users and developers.Our process knowledge system is a web-basedapplication that uses Protégé inside a serverapplication. The server application provides anumber of functionalities that were required byusers but that are on available in Protégé. 2.1.   Requirements to the system At the beginning of the HarmoniQuA project, agroup of experts in the field of water management,software and knowledge engineers defined thestructure and the knowledge items to be collected.We started knowledge acquisition usingspreadsheets and manually processing thespreadsheets to create a common understanding of the system that is going to be implemented[Scholten, et. al. , 2006]. This step has been vital inmaking it clear to software and knowledgeengineers what the needs and expectations of thedomain experts are. In addition, domain expertswere also asked to specify their needs and specifyrequirements on how the system should work. Atthe end of this stage, we identified a number of requirements; the most important were:-   The process knowledge system should besimple and user-friendly. Domain experts arenot trained in the use of general-purposeknowledge-based systems and may not befamiliar with concepts that are specific togeneral purpose knowledge-based systems.Thus, a new interface should be built thatdirectly supports their work.-   In the HarmoniQuA project, as well as in otherprojects, domain experts are located indifferent geographical locations. Therefore, thesystem should be accessible remotely andallow users to work collaboratively.-   Access to the system should be managed. Anauthorisation and authentication mechanism isrequired. Moreover, experts should be able toedit knowledge items only in their field of expertise.-   The system must be adaptable as newinformation and insights become available.Based on the above requirements, it was decided tobuild a web-based interface to the Protégéknowledge-based framework. The web-basedinterface should shield users from the intricacies of working with Protégé. The system should providefunctionalities that are essential but missing inProtégé such as authentication and authorisationand collaborative development. 2.2.   Process ontologies Two sets of generic ontologies have beenconstructed as part of the process knowledge  models (Figure 1). These are the task  and the dedication aspect  ontologies [Kassahun et al .,2004]. Terms of the task  ontology are conceptsrelated to actions done, such as tasks, activities,methods and users. Terms of the dedication aspect   ontology are qualifiers of instances from the task   ontology. Dedication aspects are used in theauthorisation module of the knowledge baseauthoring tool to grant or deny editingauthorisation. In MoST, dedication aspects areused to filter instances of knowledge items basedon user roles and preferences. They are also usedin MoST’s project management component toauthorise users in performing tasks. 3.   PROCESS KNOWLEDGE AUTHORING Traditionally knowledge acquisition consists of atedious task of elicitation (via interviews, etc.),analysis, modelling and validation of knowledge.One of the purposes of Protégé is to solve thisknowledge-acquisition bottleneck. Protégé is a“meta-tool” that enables knowledge engineers toconstruct domain-specific knowledge-acquisitionsystems [Musen, et al., 2000, Gennari et. al, 2003].The process knowledge authoring tool usesProtégé internally to manage knowledge items. Wedevelop software components around Protégé thatwill fulfil the requirements pursued. To allowcollaborative knowledge acquisition and analysisthe system should be accessible via Internet. Therequired simplicity means that the system shouldencapsulate the knowledge engineering aspects of Protégé and allow experts to concentrate onentering knowledge items. Unlike relationaldatabases, ontological structures are described inthe same way as the actual data ( instances ).Therefore, one can simply combine multipleontological data sources together. This makesontology-based system easily extensible andadaptive.In the HarmoniQuA project, domain experts wereactively involved in the modelling of theknowledge system at an early stage. Therefore,there was no need of a tedious work of knowledgeelicitation and analysis since the experts enterknowledge item into the system that manages theauthoring process based on the ontology of thespecific process problem domain. 3.1.   Design of the system Figure 2 shows the overall framework of theprocess knowledge system that utilises webtechnology. The command handler  modulehandles communication with the users of thesystem. Users access the system either using aweb-browser or MoST. Standard web browsers areused to edit the knowledge base. MoST downloadsthe knowledge base in XML format and allowsusers to browse the knowledge base offline ormanage projects based on the process knowledgebase both offline and online.Protégé is a single user desktop application withlittle support for collaboration. The authenticationand authorisation module fosters collaboration in anumber of ways:1.   All users of the system are assigneddedication aspects upon registration. In theHarmoniQuA knowledge base, users areassigned to a number of dedication aspects,such as user types (General Public, Modeller, TaskProcess EntityDecisionUser typeDedication aspectDomain typeManagerModellerReviewActivityMethodis aapplicablemethodsapplies toapplies tohasactivitiesUserauthorisedfor is ais a   Figure 1. Part of the process knowledgeontology. Modified after Kassahun et al. (2004).   Process Knowledge Base Server Authenticationandauthorisation MoST Web formsExport moduleCommandhandler Protégé Export process specification / manage collaborative projectEdit processknowledge base MoST Project server htt ://...http://...   Figure 2. Framework for the   implementation of theprocess knowledge system.    Manager, etc) and domain types (Generic,Groundwater, Hydrodynamics, etc).Knowledge items are also tagged withdedication aspects. Users can edit theknowledge base items when their dedicationaspects match with or include the dedicationaspects of the knowledge item.2.   Users can work in the system concurrently.The system has a locking mechanism toovercome authors entering conflictingupdates.3.   Users can attach comments to knowledgeitems.The export  module and the  project server  are usedto export and store the knowledge base in XMLformat. MoST uses the export module to providethe knowledge base offline. 3.2.   Implementation The process authoring tool is built using the Javaprogramming language and the Java EE servlettechnology. The Java servlet application on theserver, therefore, needs to be installed in a servletcontainer. The server application uses the ProtégéAPI to access and manage knowledge bases.HTML and JavaScript is used to generate userinterfaces. The authoring tool can be used by anystandard web browser. In addition, extrafunctionalities are built such as backup-and-recovery, spelling checking and correction facilitiesto give domain experts extra incentive to adopt thesystem. Figure 3. Few screen shots of the user interface of the process knowledge authoring tool.    3.3.   User interaction The process authoring tool generates userinterfaces in HTML and JavaScript so that the onlyrequirement on the users’ computer is a standardweb-browser. Few screen shots of the userinterface are shown in Figure 3.Users must be registered to enter the knowledgebase and will have strict permissions on theoperations they are allowed to perform. Allregistered users have read  and comment   authorisation rights.To edit the knowledge base users must beassigned to a dedication aspect. Dedicationaspects are assigned to users as well as toknowledge items. When assigned to users,dedication aspects function as roles; when   assigned to knowledge items they mean: “this itemis applicable to ...”. When a user, e.g. a domainexpert in groundwater, wants to edit an instance of the task “Describe Problem and Context”, the userneeds to be assigned to all dedication aspects thatthis task  has. In this case, if the task is a modeller’stask for the domain of groundwater, the user needsto be a modeller in the domain of groundwater.The user interface provides a web interface foradministration of users and making backups. 4.   PROCESS KNOWELDGE BASE ANDMoST The Modelling Support Tool, MoST, has thefunctionality to guide users, monitor what they doin their modelling projects, and let them generatereports on the projects. MoST relies on the processknowledge that is collected and organised usingthe process knowledge system. The system keepstrack of the different versions of the processknowledge base and makes that available to MoST.MoST can be used offline by a single user andonline by a users working as a team. When usedonline, MoST accesses projects managed by theknowledge base system and allow users tocollaborate with team members in a project. 5.   CONCLUSION The process knowledge base system andassociated web-based authoring tool weredeveloped for the HarmoniQuA project. Theprocess knowledge base is based on genericknowledge models to describe project processes.The authoring tool is based on web technology. Itis allows experts to collect and organise processknowledge for use in water management incollaborative way. The authoring tool and theassociated support tool have been successfullyapplied in HarmoniQuA. Currently we are using thesystem to the water stress mitigation process forthe EU funded AquaStress project. The processknowledge authoring tool has greatly simplified theknowledge acquisition process that traditionallyrequired substantial amount of work for collectingand analysing knowledge. The knowledge baseauthoring tool in combination of MoST supportsall users involved in model-based watermanagement studies. Experts use the tool toorganise and manage knowledge-based processwhile other experts and novice users use the toolsfor guidance and managing their model-basedstudies. 6.   ACKNOWLEDGEMENT The present work was carried out within the Project‘Harmonising Quality Assurance in model basedcatchments and river basin management(HarmoniQuA)’, which is partly funded by the ECEnergy, Environment and Sustainable Developmentprogramme (Contract EVK2-CT2001-00097). 7.   REFERENCES BDMF (2000). Protocols for Water andEnvironmental Modeling, Bay-DeltaModeling Forum. Ad hoc ModelingProtocols Committee.www.sfei.org/modelingforum/.Gallupe, B. (2001). "Knowledge managementsystems: surveying the landscape."International Journal of ManagementReviews 3 (1): 61-77.Gennari, J. H., Musen, M. A., Fergerson, R. W.,Grosso, W. E., Crubézy, M., Eriksson, H.,Noy, N. F. and Tu, S. W. (2003). "Theevolution of Protégé: an environment forknowledge-based systems development."International Journal of Human-ComputerStudies 58 (1): 89-123.HarmoniQuA (2006). http://harmoniqua.org.Accessed on Februay 11, 2006.Hendriks, P. H. J. and D. J. Vriens. 1999."Knowledge-Based Systems andKnowledge Management: Friends or Foes?"Information and Management 35:113-25.ISO 9000 (2004). Introduction and support package,Guidance on the concept and use of theprocess approach for management systems,International Organisation forStandardization.ISO 9001:2000 (2001). Quality ManagementSystems: Requirements., InternationalOrganisation for Standardization.Kassahun, A., Scholten, H., Zompanakis, G. andGavardinas, C. (2004). Support for model
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