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Naturnet - Redime NEWSLETTER No. 4 November 2006 ContentIntegrated Environmental Impact Assessment as an The Sketch Environment within Garp3e - Learning Module for Sustainable Development Anders Bouwer and Bert BredewegMarkus Jochum, Dipl. Forstwirt (University ofFreiburg), Peter K A Barz, BSc MSc MIEMA CEnv To support users in the early phases during the model-(Environmental Network Limited) building process, the Sketch environment has been implemented as an integrated part of the Garp3Based on the recognition that ecosystems provide the collaborative workbench . It offers a series of sevenbasis for life on Earth, it is the sustainable development editors that allow users to represent their ideas about a(SD) and management of these services that enables domain in increasing levels of detail. …continued human health and welfare. However,prosperity also depends on continued economic Page 8development whereby industrial growth and theexpansion of built-up areas and their associatedinfrastructures often exert negative impact on peopleand their social and natural environment. … Successful Use of Garp3 by Stakeholders Page 2 Bert Bredeweg, Paulo Salles, Anders Bouwer, Elinor Bakker and Jochem LiemSharing and Reuse of Conceptual Models The Garp3 software is developed to be a workbench for stakeholders to advance their conceptual ideas onJochem Liem and Bert Bredeweg cause-effect analysis of systems’ behaviour,One of the goals of the NaturNet-Redime project is to particularly concerning phenomena related toempower stakeholders with means to manipulate sustainable development. By using this workbenchcause-effect models. Being able to easily inspect the users can investigate the logical consequences of theircontents of models, take parts of those models as common sense ideas and use expert knowledge toneeded, and assemble them into a new model context improve their own understanding of phenomena. …are among those goals. Hence, there is a desire to Page 10share and reuse (parts of) qualitative models, as thecommunity building qualitative models is growing. … Page 4 Events of interestThe Qualitative Reasoning and Modelling Portal Page 12Elinor Bakker, Jochem Liem and Bert Bredeweg ContactThe Qualitative Reasoning & Modelling (QRM) portal(http://www.garp3.org) is the central place on the web Page 13where information about the Garp3 workbench andrelated theoretical and practical issues is presented. … Page 7 České centrum pro vědu a společnost, Radlická 28/263, 150 00 Praha 5, Czech Republic www.naturnet.org www.ccss.cz ISSN 1801-6480 <META NAME="DC.Identifier" CONTENT="(SCHEME=ISSN) 18016480">
Integrated Environmental Impact Assessment as an e-Learning Module for Sustainable Development Markus Jochum, Dipl. Forstwirt (University of Freiburg), Peter K A Barz, BSc MSc MIEMA CEnv (Environmental Network Limited)Based on the recognition that ecosystems provide the illustrate the complexity involved in achieving its aims,basis for life on Earth, it is the sustainable development the NaturNet-Redime (NNR) project seeks to(SD) and management of these services that enables demonstrate the role and interaction of some of thesecontinued human health and welfare. However, interests and parameters that are so important for SDprosperity also depends on continued economic through the example of the integrated Environmentaldevelopment whereby industrial growth and the Impact Assessment (iEIA) methodology.expansion of built-up areas and their associatedinfrastructures often exert negative impact on people This educational objective will be achieved with the helpand their social and natural environment. of an e-learning module for SD that deals with the topical example of the construction and assessment of theTo be sustainable, development needs to balance the potential impacts caused by a wind generator. The userenvironmental, social and economic interests and will be able to select and interpret a variety of data,expectations of societies. This is a complex, multi- and perform simple analyses of the impacts thecross-disciplinary process which is based on many environmental, social and economic parameters aredeterminants rendering the understanding and therefore exposed to and enter the results in the correspondingacceptance of SD a difficult task for most people. conflict matrices. These impacts can be judged “Zero”, “Low”, “Medium” or “High”– see examples in Figures 1-3.In order to make the ordinary person aware of some ofthe issues that need to be considered in SD and to Fig. 1: Example conflict matrix with environmental parameters Fig. 2: Example conflict matrix with social parameters 2
Fig. 3: Example conflict matrix with economic parametersThis module is specifically designed for Internet users through the newly-developed distributed web services ofsuch as ordinary citizens, pupils or students and is using the NNR Internet Portal and the analysis of thisstandardised e-learning software. Based on a broad geographical data may be carried out as part of theintroduction into SD, this practical e-learning module will learning activity online, demonstrating the application ofprovide focussed tasks for the user investigating and geographic information in sustainable development inassessing examples of related environmental, social and Europe. The potential for the provision of facilities for theeconomic parameters – whereby the assembly and use of mobile devices in an outdoor environment isinteractions of these parameters represent the approach being discussed at present enabling the verificationthat conforms with the concept of SD. Opportunities are and/or adding of actual data to the iEIA database.also provided for additional investigation by those userswho wish to develop their interest in SD in more depth. An example of the application of such geographic information is the analysis of the visual impact of a windThis SD e-learning module will guide the user through a generator with a height of 100 m as shown in Figure 4.simplified iEIA process, whereby s/he will be able to The analysis is conducted by calculating visibility basedgather information on the context and detail of the on elevation data and overlaying this information with aenvironmental, social and economic parameters that further geographic layer containing the adjacent urbanform the background of the proposed infrastructure area. As a result, the user can interpret the visibility ofdevelopment. The user will be supported by pertinent the wind generator in respect to the area it coversmulti-media information - such as environmental, socio- (highlighted in blue). The user will be able to interpretcultural and economic data, which is presented as text, the selected data, perform a simple analysis of thelinks, photographs, movies, sound, etc. Relevant impacts the multiple parameters are exposed to andgeographical information will be provided by one of the enter the results in a conflict matrix. These impacts canregional administrations that is participating in the NNR be judged “Zero”, “Low”, “Medium” or “High”.Project. This information will be made accessible Fig. 4: Visibility analysis for a wind generator with the height of 100m 3
The result indicates that due to topographic conditions “Landscape & Visibility” and depending on thethe vast majority of the citizens of Jihlava cannot see the importance s/he attributes to the resulting impact, thewind generator and allows a conclusion as to the level of correspondent rating is entered into the conflict matricesimpact this causes. On the basis of the preceding study as shown in the example of Figure 5, below.made by the user of the issue of the parameter Fig. 5: Environmental conflict matrix showing impact rating enteredThe combined impact ratings selected by the user for all totality represents a particular state of SD. As thesethe parameters contained in the environmental, social possible outcomes directly relate to the particularand economic conflict matrices will provide an overview preferences selected by the user they will be highlyof the overall impact of the assumed development and instructive as to the status of SD envisaged.present one of a series of possible outcomes which in its Sharing and Reuse of Conceptual Models Jochem Liem and Bert BredewegOne of the goals of the NaturNet-Redime project is to http://hcs.science.uva.nl/QRM/models/repository/) .empower stakeholders with means to manipulate Users can upload qualitative models in a Webcause-effect models. Being able to easily inspect the Ontology Language (OWL) format. Based on thecontents of models, take parts of those models as contents of these OWL files, an index is created of allneeded, and assemble them into a new model the model ingredients in all models. This index iscontext are among those goals. Hence, there is used to create a search engine, which shows all thea desire to share and reuse (parts of) qualitative ingredients in all the models. Selecting an ingredientmodels, as the community building qualitative models from this list refines the amount of matching models,is growing. Within the NaturNet-Redime project, which in turn reduces the items within the modelmultiple river ecologists are performing case studies ingredient list to only the model ingredients in theabout how factors influencing certain rivers affect matching models. This allows users to refine theirsustainable development. It is important for them to search, and find only those models that arebe able to reuse parts of each other’s models, and of potentially interesting for them. Selecting a modelother existing modelling efforts. There is also the shows the meta-data belonging to that model (author,wish to be able to evaluate the relevance of models title, abstract, etc.) and allows users to download thewithout having to download and open them in the model. Users can also rate models, and getworkbench first. overviews of the top downloaded and top ratedTo address issues such as these, we are developing models.a qualitative model repository ( see Figure 1 , 4
Figure 1: Online qualitative model repositoryTo formalise qualitative models in OWL we Garp3 workbench to allow users to copy/paste modelformalised the QR vocabulary (and the usage definitions, or even complete aggregates of modelrestrictions of these model ingredients) in OWL [3,4]. ingredients between models. The software takes careBased on this vocabulary a template for qualitative that all the interdependencies between modelmodels was created, which was evaluated using ingredients are properly maintained, which meansOWL editors and inference engines. In addition, that if an aggregate is copied to another model, thefunctionality was added to the Garp3 workbench software also copies the model ingredient definitions(http://www.garp3.org) to export and import models that this aggregate uses. To implement this. Each of the exported models refers to concepts functionality the architecture of Garp3 had to bedefined in the vocabulary, which allows models changed to allow users to open multiple models atuploaded to the qualitative model repository to be the same time (see Figure 2). The model repository,properly indexed. OWL, multiple model and copy/paste functionality  allows users to share, search for, and re-use (partsThe OWL functionality and the repository address the of) qualitative models to support them in articulatingneed of community for sharing and searching. To and constructing conceptual knowledge.further enable re-use, functionality was added to the 5
Figure 2: Garp3 workbench with multiple modelsReferences1. J. Liem, B. Bredeweg, and A. Bouwer, 2006. Jochem Liem and Bert Bredeweg. OWL andQR model-fragment library standard Redime, qualitatative reasoning models. In 29th annualNaturnet-Redime, STREP project co-funded by the German Conference on Artificial IntelligenceEuropean Commission within the Sixth Framework (KI2006), 2006. Lecture Notes on ArtificialProgramme (2002-2006), Project no. 004074, Project Intelligence. Springer, 2006. (To appear).Deliverable Report D126.96.36.199. B. Bredeweg, A. Bouwer, J. Jellema, D.Bertels, F. Linnebank, and J. Liem. Garp3 - A newWorkbench for Qualitative Reasoning and Modelling.20th International Workshop on QualitativeReasoning (QR-06), C. Bailey-Kellogg and B. Kuipers(eds), pages 21-28, Hanover, New Hampshire, USA,10-12 July 2006. 6
The Qualitative Reasoning and Modelling Portal Elinor Bakker, Jochem Liem and Bert BredewegThe Qualitative Reasoning & Modelling (QRM) portal In the Models section, several well-documented(http://www.garp3.org) is the central place on the web example models can be found. A model repositorywhere information about the Garp3 workbench and has been added as an online feature to supportrelated theoretical and practical issues is presented. collaboration between model builders. TheThe website has been active and online since collaborative version of the Garp3 workbench,October 2005 and has recently been extended to released in September 2006, makes it possible toinclude several new features and an improvement of save and load model files in a Web Ontologythe internal structure and overall layout. Language (OWL) format. To create a platform for sharing these files between model builders, the model repositoryThe portal includes documentation about the (http://hcs.science.uva.nl/QRM/models/repository/) isdevelopment and usage of the single user and added to the portal under the Models section. Thecollaborative version of the Garp3 workbench and model repository makes it possible to upload,also has a section where the software can be download and search models and also offers thedownloaded. In addition to this, the portal offers possibility to rate available models and look into theaccess to published deliverables of the NNR project metadata that has been provided by the modelwhich describe best practices when building models builder.and a curriculum for learning about QR. Figure 1: The QRM Portal, with improved structure and layout. 7
In the Community section, information can be found this section. Answers to common problems can beabout subscribing to the QRM mailing list. On this list found in the FAQ section and explanations of QRquestions can be asked about model building issues concepts are available in the Glossary. The onlineand the software. Also, there is an explanation of bug reporting system has recently been added to theSkype and VNC, two frequently used platforms to portal. Since the Garp3 workbench has recentlysupport communication between people over the come out of development status and is still beinginternet, which are used to facilitate communication improved, bugs may occur while working with it.within the QR community. These discovered bugs can now be brought together in the open source Mantis bug tracking system byThe Support section focuses on giving ‘help’ to users anyone who finds them, which will support the solvingworking with the Garp3 workbench. The Frequently of these problems. To complete the portal the LinksAsked Questions (FAQ), Glossary and Bug reports section provides web references to related pages andsections can be accessed from here, and in the near the About section provides information about thefuture the Garp3 online help pages will be added to partners of this project. The Sketch Environment within Garp3 Anders Bouwer and Bert BredewegTo support users in the early phases during the • In the Causal model editor, users can draw amodel-building process, the Sketch environment has graph with quantities as nodes, andbeen implemented as an integrated part of the Garp3 influences and proportionalities as directedcollaborative workbench . It offers a series of connections between them, to describe theseven editors that allow users to represent their ideas causal dependencies in the system.about a domain in increasing levels of detail: • In the Scenarios editor, users can specify different scenarios to be considered, each of • In the Concept map editor, users can which is described in terms of the entities, represent what they think are the important agents and external influences involved, the concepts in a domain, and the relationships quantities involved, the initial values and between them. (in-)equality statements, and relevant • In the Structure editor, users can be more assumptions. specific about what are the entities, agents, • In the Behaviour graph editor, users can and assumptions of the system of interest, draw a directed state-transition graph of the leading to a structure model. expected behaviour of the system, in which • In the Process definitions editor, users can each state is characterized by typical quantity specify the important aspects for each of the values, or (in-)equality statements. processes that may cause changes to the state of the system, such as the entities involved, the quantities involved, the start conditions under which the process applies, Working through this set of editors structures the the effects, the stop conditions, and relevant model building process (following the framework for assumptions. structured modelling ), and the resulting sketches • In the Agents and external influences can be shared as intermediate modelling results. This definitions editor, users can specify the helps to establish a common understanding of the important aspects for each of the agents and domain between modellers, before building a final external influences that may influence the simulation model. system from outside, in a similar fashion as for the Process definitions. 8
Figure 1. Screenshots from the different editors in the Sketch environment.During the Krimulda workshop in September 2006,  J. Liem, A. Bouwer, and B. Bredeweg, 2006.six project participants (in work package 4 and 6) Collaborative QR model building and simulationhave tested the basic Sketch environment workbench, Naturnet-Redime, STREP project co-functionality by using it to represent knowledge about funded by the European Commission within the Sixththeir river ecology case studies. The participants Framework Programme (2002-2006), Project no.welcomed the addition of the Sketch functionality and 004074, Project Deliverable Report D4.3.provided useful comments for further improvements.Current work concentrates on functionality forimporting information from one sketch to another,which will further facilitate creating sketches that forma consistent and coherent set of representationsabout the domain. In conclusion, the Sketch  B. Bredeweg, Salles, P., Bouwer, A., and Liem L,environment explicitly structures the model building 2005. Framework for conceptual QR description ofprocess, and will support users in the model building case studies, Naturnet-Redime, STREP project co-process by refining initial ideas into detailed funded by the European Commission within the Sixthrepresentations of expert knowledge. Visit Framework Programme (2002-2006), Project no.http://garp3.org for further details and for 004074, Project Deliverable Report D6.1.downloading the Sketch software (Garp3 version1.3.1). 9
Successful Use of Garp3 by Stakeholders Bert Bredeweg, Paulo Salles, Anders Bouwer, Elinor Bakker and Jochem LiemThe Garp3 software is developed to be a workbench As domain knowledge we focussed on the Millenniumfor stakeholders to advance their conceptual ideas on Development Goals (MDG) as defined by the Unitedcause-effect analysis of systems’ behaviour, Nations (see e.g.http://www.un.org/millenniumgoals/).particularly concerning phenomena related to More specifically, the knowledge dealt with the notionsustainable development. By using this workbench of deforestation in the context of the MDG number 7,users can investigate the logical consequences of which is concerned with ‘ensuring environmentaltheir common sense ideas and use expert knowledge sustainability’ (cf. Salles et al., 2005). A model wasto improve their own understanding of phenomena. created in Garp3 that captures some of the key ideas relevant to deforestation. The causal model resultingBut how useful is the Garp3 software actually for from that is shown in Figure 1 and the accompanyingsuch purposes? Recently the Garp3 workbench was value history in Figure 2. Summarising, at the start ofpresented to two groups of Latvian students from the the cause-effect chain is the deforestation rate, whichUniversity of Latvia and from the Vidzeme Regional reduces the land with vegetation, which in turnUniversity. These students were Bachelors (final causes the biodiversity to decrease and consequentlyyear) and Masters (first year) and had no prior reduces the chances of finding new food andknowledge of the Garp3 Qualitative Reasoning (QR) medicines. It also causes erosion to increase, whichtechnology. These students were therefore well leads to less agricultural production and less watersuited to investigate the usability of the software with contained in reservoirs. Ultimately, all these factorsreal novice stakeholders, which was the main goal of come together in the gross domestic product (GDP),the event. reflecting the human wealth, which decreases (whenThe software has many features that can be used to deforestation is active).design potentially interesting and useful knowledge For the experiment the full model was rearranged intodiscovery events. Participants may build their own six sub-models, ranging from simple (addressing onlymodel from scratch, individually or collaboratively wood cutting and land with vegetation) to complexinteract with existing models, make sketches of initial (including all details as shown in Figure 1). Theideas, discuss a causal model within a group, and students who used the software during themany more. For the interaction with the Latvian experiment interacted with each of these modelsstudents we opted for a traditional experimental while working through a set of assignments (withsetting that investigates whether the software can be questions such as: Which quantity is influencedused effectively to learn something in the first place. negatively by deforestation? If land with vegetationAfter all, due to its many options the Garp3 software decreases, what will happen to biodiversity? What ismay appear complex and testing all functionality in the value of biodiversity in state 1 and 4? Whichone experiment is infeasible. quantity is increasing?) Figure 1: Causal model generated by Garp3 for the deforestation model 10
Figure 2: Value history of the quantities in the deforestation modelIn the experiment a group of 24 subjects was treatment condition worked through the models (asassigned to the treatment condition and a group of described above) and the students in the controlthe 22 subjects was assigned to the control condition group attended a lecture on the use of computers for(Table 1). To assess the pre-knowledge of the education. Both of these lasted approximately onesubjects a questionnaire was administered consisting hour, after which a post-test was administered to bothof 36 questions about issues captured in the model groups. The post-test was in principle similar to theon deforestation as discussed above. The pre-test, but consisted of a different set of questionsquestionnaire contained different kinds of questions, on the same subject matter. Finally, the experimentsuch as True/False questions (e.g., IF agricultural was closed by briefly explaining the overall goal andproduction decreases, THEN GDP, wealth, organisation of the event. In the control group this ofdecreases), questions that required students to fill out course required some additional effort in order tothe missing word (increasing or decreasing) (e.g., IF ensure that they would also appreciate theerosion increases, THEN agricultural production experience (e.g., interested students were given……?), etc. After this pre-test the students in the a brief overview of the Garp3 software and related research issues). Table 1: Experimental set-up 15 min 15 min 60 min 15 min 15 min Treatment Introduction Pre-test Working with Garp3 Post-test Closing Control Introduction Pre-test Lecture on ICT Post-test Closing 11
The results of the experiment turned out to be veryencouraging. Students in the treatment group could Acknowledgementeasily operate the software, that is open the models, We are grateful to the students who participated inrun them, and inspect the simulations. Apparently the the experiment, and to Maris Alberts, Una Bike,interface of the Garp3 software behaves in a way that Peteris Bruns and their co-workers for providing usis intuitive for this generation of students. The the opportunity to work with Latvian students to testtreatment was also effective in creating a significant our ideas and software.learning effect. Particularly, after removing thesubjects who scored very high on the pre-test (≥ 30correct), the subjects in the treatment group (N=16)scored an average of 26.95 points on the post-test Literature(with 23.25 points on the pre-test), while the subjects • Salles, P., Bredeweg, B., and Nuttle, T. (2005)in the control group (N=21) scored an average of Qualitative Models of Indicators of Environmental21.05 points on the post-test (with 20.24 points on Sustainability of the Millennium Developmentthe pre-test). This turned out to be a statistically Goals. 2nd MONET Workshop on Model-Basedsignificant difference using a t-test (P<0.001). Being Systems (MONET 05) at the 19th Internationalable to achieve this result within the short duration of Joint Conference on Artificial Intelligence (IJCAI-the experiment creates promises for the impact the 05), Picardi, C., Salles, P. and Wotawa, F. (eds.),Garp3 software may deliver when it is used pages 66-72, Edinburgh, Scotland, 30 July.systematically on a variety of topics in an educationalcontext. Events of interestNATURNET - REDIME workshop - Tools And International European 1st EAAE Forum onMethods For Raisining Awareness of Sustainable Innovation and System Dynamics in FoodDevelopment Networks thBruxelles, 29 November 2006, INTEREL, Avenue 15-17 February 2007 INNSBRUCK - IGLS – Austria.de Tervuren 402, Brussels, 1150 Belgium. Organized The objective of this Forum is to provide anby The Vysocina Region (CZ) & the NaturNet- interdisciplinary discussion environment that supportsRedime Team creativity and exchange to foster the development of new ideas for innovative and interdisciplinaryContact: firstname.lastname@example.org research in the agri-food sector. Contact: Melanie FRITZ Email: m.fritz(a)uni-bonn.de http://www.uf.uni-bonn.de/innovation2007/ 15 th Conference in Agricultural Labour Science 5th International Conference on Ecological 5 – 6 March 2007 ViennaInformatics ISEI5 The conference is organised by Max-Eyth-Society for Agricultural Engineering of the VDI and the UniversityDecember 4th-6th, 2006 Santa Barbara, CA, USA. of Natural Resources and Applied Life Sciences inNovel Computational Techniques for Improved Vienna.Management, Understanding and Forecasting ofComplex Ecological Data Contact: Prof.Dr.J.BOXBERGER E-mail: josef.boxberger(a)boku.ac.athttp://www.isei5-conference.elsevier.com/ http://www.nas.boku.ac.at/akal-seminar.html 12
SIXTH FRAMEWORK PROGRAMME Educational programmes on social, economic, and environmental tools for the implementation of the EU Strategy on Sustainable Development at both EU and international levels NATURNET-REDIME New Education and Decision Support Model for Active Behaviour in Sustainable Development Based on Innovative Web Services and Qualitative Reasoning Project no. 004074 Instrument: SPECIFIC TARGETED RESEARCH PROJECT Thematic Priority: SUSTDEV-2004-3.VIII.2.e Start date of project: 1st March 2005 Duration : 30 months Web : http ://www.naturnet.org Project officer Daniel Deybe Daniel.DEYBE@cec.eu.intProject co-funded by the European Commission within the Sixth Framework Programme (2002-2006)Co-odinator Contact person Country E-mailCzech Centre for Science and Society Karel Charvat CZ email@example.comPartner Contact person Country E-mailEnvironmental Network Ltd Peter Barz UK firstname.lastname@example.org://www.env-net.com/Albert-Ludwigs University of Freiburg Barbara Koch DE email@example.com://portal.uni-freiburg.de/felis/Municipality of Francavilla di Sicilia Nino Paterno IT firstname.lastname@example.org://www.stepim.it/Gymnazium Bozeny Nemcove Jan Sterba CZ email@example.com://www.gybon.cz/INNOVATION. Grenzüberschreitendes Netzwerk e.V Frank Hoffmann DE firstname.lastname@example.org://www.IGN-SN.deInstitute of Mathematics and Comp. Science, Univ. of Latvia Maris Alberts LV email@example.com://www.lumii.lv/Joanneum Research Alexander Almer AT firstname.lastname@example.org://dib.joanneum.at/KRIMULDA - Municipality Juris Salmins LV email@example.comAPIF MOVIQUITY SA Wendy Moreno ES firstname.lastname@example.org://www.moviquity.com/Mission TIC de la Collectivité Territoriale de Corse Jerome Granados FR email@example.com://www.mitic.corse.frRegion Vysocina Jiri Hiess CZ Hiess.J@kr-vysocina.czUniversity of Jena, Institute of Ecology Tim Nuttle DE Tim.Nuttle@uni-jena.dehttp://www.uni-jena.de/ecology.html Michael Neumann firstname.lastname@example.orgHuman Computer Studies Laboratory, Inform atics Institute, Bert Bredeweg NL http://hcs.science.uva.nl/~bredewegFaculty of Science, University of Amsterdamhttp://hcs.science.uva.nl/projects/NNR/Bulgarian Academy of Sciences, Central Laboratory of Yordan Uzunov BG email@example.comGeneral Ecology (CLGE)Danube Delta National Instit. for Research and Developm ent Eugenia Cioaca RO firstname.lastname@example.org://www.indd.tim.ro/University of Brasilia, Institute of Biological Sciences Paulo Salles BR email@example.comUniversity of Hull, International Fisheries Institute Ian Cowx UK firstname.lastname@example.orgUniversity of Natural Resources and Applied Life Sciences, Stefan Schmutz AT email@example.comDepartment of Hydrobiology, Fisheries and Aquaculture 13