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Journal of Environmental Management xxx (2008) 1–14

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Journal of Environmental Management

journal homepage: www.elsevier .com/locate/ jenvman

Towards a SOLAP-based public participation GIS

Rosemarie McHugh a,b,*, Stephane Roche a, Yvan Bedard a,b

a Centre for Research in Geomatics, Laval University, Pavillon Casault, G1K 7P4, Quebec (Qc), Canadab Canada NSERC Industrial Research Chair in Spatial Databases for Decision-Support, Laval University, Pavillon Casault, G1K 7P4, Quebec (Qc), Canada

a r t i c l e i n f o

Article history:Received 18 October 2007Received in revised form 20 November 2007Accepted 24 January 2008Available online xxx

Keywords:PPGISSpatial OLAPBusiness intelligence

* Corresponding author. Tel.: þ1 418 656 2530; faxE-mail addresses: [email protected] (R

scg.ulaval.ca (S. Roche), [email protected] (Y.

0301-4797/$ – see front matter � 2008 Elsevier Ltd.doi:10.1016/j.jenvman.2008.01.020

Please cite this article in press as: McHugh,(2008), doi:10.1016/j.jenvman.2008.01.020

a b s t r a c t

In this paper, we describe how spatial on-line analytical processing (SOLAP), a specific category ofbusiness intelligence technology especially adapted to geospatial data, can help to improve thetechnological side of public participation GIS applications. Based on two simulated cases of realisticscenarios of a public audience, this paper aims at demonstrating the relevance of this SOLAP technologyto support and improve the interactive access and analysis of multi-scale, multi-epoch geospatialinformation (and indirectly public involvement) for an environmental management PPGIS application.

� 2008 Elsevier Ltd. All rights reserved.

Introduction: PPGIS and environmental management

The concept of a public participation geographic informationsystem (PPGIS) was developed in the context of the informationsociety, especially from the critical GIS trend, in order to boostpublic participation and foster the empowerment of localcommunities (Sheppard et al., 1999). Indeed, in our economicallydeveloped countries, the current context of environmentalmanagement is characterised by a double challenge. On the onehand, the legal and organisational standards of land planning andenvironmental management require various levels of governmentto justify and explain their decisions while involving the public ina more systematic way. On the other hand, to respond to thesenew constraints, it is advantageous to integrate information fromvarious sources and use information technologies (in particulargeospatial technologies) to create solutions acceptable by manylocal and national governments and agencies.

In this context, methods, approaches and tools have beendeveloped under the concept of PPGIS, qualified by some of theresearchers involved as a new PPGI science (Sieber, 2004).Practically, a PPGIS could be defined as the ’embedded’ integrationof geospatial technologies with participatory mechanisms that arepartly developed by (and for) the public (individuals, local groupsor communities .) (Craig et al., 2002). One of the main purposesof PPGIS is to combine local and technical knowledge for GISproduction and use, in order to support collaborative land

: þ 1 418 656 7411.. McHugh), stephane.roche@Bedard).

All rights reserved.

R., et al., Towards a SOLAP-ba

planning processes and spatial decision-making (Onsrud andCraglia, 2003).

Problems at stake: PPGIS weaknesses

The capability of a PPGIS to support and stimulate publicinvolvement is limited by several major contextual factors (so-cial, political, cultural), and a lot of research has been conductedon those topics over the last decade (Roche, 2003; Sieber, 2006;Craig et al., 2002). Most of the efforts made by practitioners andresearchers aimed at improving PPGIS applications and focusedon the participative process (Roche and Caron, 2004). At thesame time, PPGISs still rely on classical GIS technologies(including web and wireless flavours of GIS) and do not benefitfrom the major improvements brought by the business in-telligence (BI) technologies. This lack of technological innovationappears as another limiting factor for PPGIS applications since BItechnologies are specifically aimed at supporting decision-making (Carver, 2003).

Still today, PPGIS applications developed in western countrieshave difficulties in reaching their main objectives because of thefollowing weaknesses. (1) GIS user interfaces are too complexfor non-experts (Carver, 2001). (2) GIS functions and operatorsfocus on quantitative methods whereas the integration, analysisand representation of local knowledge need qualitative methods(al-Kodmany, 2001). (3) GIS lacks the high level of interactivityrequired to efficiently support collaborative and participativeprocesses (Jankowski and Nyerges, 2001). (4) Last but not least,the level of complexity of GIS technologies is too high (Laurini,2001) to allow users to do on-the-fly, and without the useof complex query languages, the cross-tabulations of data,

sed public participation GIS, Journal of Environmental Management

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Fig. 1. Ladder of citizen participation (Arnstein, 1969).

sameplace

sametime

differentplace

differenttime

e.g. publicdebate

e.g. on-lineforum

/ webGIS

e.g. classicalconsultation

(poster,newspaper)

e.g. forum /group-ware,

redlining

Fig. 2. Spatio-temporal contexts of PPGIS applications.

R. McHugh et al. / Journal of Environmental Management xxx (2008) 1–142

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spatio-temporal evolution analyses of phenomena, interactiveexploration of data from different perspectives or from differentlevels of abstraction, etc. Most PPGIS applications are based onGIS technologies that are not interactive enough, or rich enough,from the informational perspective to support collaborativework and decision-making, especially when non-expert partic-ipants are included (Balram and Dragicevic, 2006; Jankowskiand Nyerges, 2001). Today’s PPGIS technologies typically rely ontransactional technologies (DBMS, GIS, web servers) and do notbenefit from the strengths of analytical BI technologies (e.g.multi-dimensional data warehousing, on-line analyticalprocessing (OLAP), spatial OLAP, data mining, datacube-baseddashboards).

Objectives and proposed solution

In this research, we propose to describe how a specific categoryof BI technology especially adapted to spatial data, referred to asspatial on-line analytical processing (SOLAP), which can help toimprove the technological side of PPGIS applications. Morespecifically, the goal of this paper is to demonstrate the relevance ofSOLAP technology to support and improve the interactive accessand analysis of multi-scale, multi-epoch geospatial information,and indirectly public involvement, in a particular type of PPGISapplication (e.g. public debate).

OLAP technologies have existed for a decade and allow easynavigation and interactive exploration of data without any expertassistance. Well-known products include Cognos Powerplay,Business Objects OLAP Intelligence and ProClarity to name a few.SOLAP has been developed from OLAP technologies withinuniversity labs and has now reached the commercial level ofmaturity (Rivest et al., 2005). SOLAP is a technology that allowseasier and faster navigation of geospatial databases. It relies onseveral levels of information granularity, cross-tabulated data,explicit space–time integration and more tightly integrated modesof visualisation that are synchronised at will (maps, tables,diagrams), than classical GIS technology (Bedard et al., 2001).Operations such as drill-down, roll-up, drill-across and slice allowusers to navigate freely in the so-called spatial datacubes withoutrequiring the use of a query language and always providing ananswer within Newell’s cognitive band of 10 s (cf. Newell, 1990).More recently, SOLAP has been enriched with hypermedia andannotation (red-lining) functionalities (Bedard et al., 2006).

Methods, approach and paper organisation

The research presented in this paper aims to demonstrate thefunctionality of SOLAP technology that can be used to aid public

Please cite this article in press as: McHugh, R., et al., Towards a SOLAP-ba(2008), doi:10.1016/j.jenvman.2008.01.020

participation during a public debate. We have built two prototypesof SOLAP applications, as a proof of concept, and tested them ina simulated project of environmental management that is based onan actual situation with real stakes and data.

The main objectives of the first SOLAP application are to in-form citizens during a public debate on a specific environmentalissue (in this case related to coastal erosion), to give them all theinformation they need to understand this stake, and to improvetheir involvement in the discussions. The developed applicationintegrates data about human, environmental, and physicalcharacteristics of a coastal land in Gaspesie, Quebec. It allowscitizens, with the support of expert users, to explore the data atdifferent levels of abstraction, to develop ad hoc queries and toget immediate answers to their specific questions. From discus-sions and comments provided by the use of this first application,we have built a second one, which provides the opportunity toidentify the priorities of intervention to protect the coast fromerosion. According to the experts who collaborated on theprototype, the level of priority can be indicated by a summationof the weights given to the different characteristics (environ-ment, physical, human), even if it is not the best method. Themain objective of this second application is to help in buildinga consensus regarding the priorities of intervention.

This paper is organised around three complementarysections. Section 2 is dedicated to a formal comparisonbetween the needs of a PPGIS application (in terms of dataexploration, navigation, interactivity, level of participation, etc.)and capabilities of SOLAP technology in terms of functionality.Section 3 is based on the ‘‘simulated case’’ mentioned belowand aims to illustrate and highlight the relevance of the SOLAP-based PPGIS concept. This ‘‘simulated case’’ is built on realisticscenarios of a public debate where most of the human–computer interactions and problems of participation (hetero-geneous groups decision-making) are taken into account(dynamic interaction with geospatial information at differentlevels of granularity, access to hypermedia information, verbal,textual and cartographical on-the-fly annotations (red-lining),access to spatial analysis operators, etc.). This ‘‘simulated case’’finally allows us to illustrate concretely the potential of theSOLAP technology to improve PPGIS applications and to makethem more efficient.

Potential and opportunities of SOLAP tosupport public participation

Participatory contexts: constraints and specific needs

A few particular elements shape the contextual framework inwhich PPGIS applications are developed, and determine their


Fig. 3. Examples of interactive exploration of multi-scale, multi-resolution, multi-epoch cross-tabulated spatial data with the help of different views created with a few mouse clickswithin a few seconds.

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specific constraints and needs. The context of participation,especially the level of participation and the nature of the publicinvolved, are particularly influential on the nature of theinteractions between participants and geospatial information.


Those interactions are characterised by, for example, free dataexploration, level of interactivity, comparisons between places,epochs, themes and scenarios, different levels of details, integrationof local knowledge, integration of new comments or reactions ..


Fig. 4. Position of the two SOLAP examples in this paper on Arnstein’s participationladder.


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Level of participationThe level of participation is a crucial component of this context.

Since the publication of Arnstein’s participation ladder (Arnstein,1969) (see Fig. 1), participation has been understood as a way toimprove the empowerment of citizens. According to the level ofparticipation required by a PPGIS application, the nature of theinformation and the technological needs vary considerably. In thespecific context of environmental management and regionalplanning, the legal and institutional frameworks generally requirePPGIS applications to achieve, at a minimum, levels 3–6 on theladder. Consequently, in addition to adapting the form and thecontent of information to better fit levels 3–6, it is necessary toselect the technologies having the appropriate nature with regardto these levels of participation.

Levels 3 (Informing) and 4 (Consultation) show progressionwithin levels of ‘‘tokenism’’ and are respectively characterised bya ‘‘have-nots to hear’’ position and a ‘‘to have a voice’’ position(Arnstein, 1969). When participation is limited to these two levels,there is no guarantee for the public involved to see their point ofview really considered for the final decision. From a geospatialinformation technology point of view, Level 3 requires capabilitiesof presenting information in a simple, affordable and versatile way.Such capabilities are especially required in order to reach the needsof experts and/or non-experts from governmental agencies who areworking with members of the public. On the other hand, Level 4requires storage and integratation of the results of consultation invarious forms (text, images, sketches .). Level 5 (Placation) isa higher level of tokenism. It is a sort of dialogue level where thecapability of the citizens to influence decisions is related to thepower they hold. At Level 6 (Partnership), citizens can enter intoa sort of partnership that enables them to negotiate and engage intrade-offs with traditional power holders (Arnstein, 1969). At these

Fig. 5. Global portrayal of the situation showing the total length of coastal land, the total leparcels).


latter two levels, geospatial information and technologies have tosupport the possibility to add new information on-line (red-liningfor instance) and to support a very high level of interactivity toobtain the desired information on-demand for collaborative works,including the choice of medium (maps, tables, charts) (Carver andPeng, 2001).

Who participates?The question of ‘‘who’’ participates is another major challenge

(Rambaldi, 2005). Concepts of Public and Citizens refer to a multi-tude of potential participants, whose form, level of organisation,motivations, power, and also legitimacy are extremely variable(neighbours, representatives of associations, neighbourhoodassociations, professionals, etc.). The participants’ skills are alsoextremely variable in terms of map reading capabilities, techno-logical proximity, and analytical way of thinking. This variety ofparticipants requires that the PPGIS application is versatile enoughto properly take into account such different users profiles and skills.PPGIS applications must provide flexible, user-friendly geospatialfunctionalities (Balram and Dragicevic, 2006).

Where and when does the participation take place?Last but not least, the ‘‘where’’ and ‘‘when’’ questions are also

really important to adapt a PPGIS solution for a specific context.Indeed, PPGIS applications could have to support synchronous orasynchronous processes. They could also have to supportprocesses taking place at the same location or at distantlocations (Jankowski and Nyerges, 2001). According to thesespatio-temporal combinations, the relevant informational andtechnological solutions will be different as illustrated (withexamples) in Fig. 2.

Actually, PPGIS cannot be limited to their technologicalcomponents. They must be considered as a series of processes thatmobilise geospatial data, technologies and participants to supportpublic participation in certain decision processes such as in the fieldof territorial and environmental management (Craig and Elwood,1998; McCall, 2003). To achieve this, PPGIS need to increase theaccessibility to data and technologies in the broadest sense, notonly providing direct physical accessibility to the technology butalso making accessible the knowledge and expertise required tounderstand the problems at stake and use properly the technologythat provides the required information. So an efficient PPGISsolution has to:

allow citizens to interactively navigate datasets to obtain thedesired information (themselves or with a supporting personaccording to the spatio-temporal context of participation)(Jankowski and Nyerges, 2001);

ngth of works and the proportion of coastal land affected by works (i.e. the total for all


Fig. 6. Table showing the result of a drill-down operation on ‘‘all parcels’’ to analyse the same information but at the ‘‘municipality’’ level (i.e. the next level of detail).


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offer past, present and planned/projected information whenappropriate (Craig and Elwood, 1998);offer the possibility to compare and validate scenarios(Jankowski and Nyerges, 2001);allow citizens to visualise data about potential impacts (what,where, when, how much) (Craig and Elwood, 1998);be available, accessible and understandable by all the partici-pants whatever their knowledge and expertise (al-Kodmany,2001);provide explicit information about data lineage, their internalquality and their external quality with regard to the usage beingdone (fitness for use), in other words provide metadata andinformed contextual warnings when appropriate (Batty, 2001);give users the capability to add comments, extra photographs ordocuments, voice recordings and other multimedia informationwhen needed to better share information or comments (Balramand Dragicevic, 2006);give users the capability to represent geospatial data in differentways (maps, charts, sketches, tables, photos) (al-Kodmany,2001).

Why SOLAP could be a relevant solution?

Spatial on-line analytical processing, or SOLAP, is a new categoryof software that does not aim to replace GIS but that rather aims toprovide new capabilities to users of geospatial data. SOLAP is basedon the OLAP paradigm that was defined by Codd et al. (1993), thepioneer of relational systems. This new paradigm was developed inan attempt to support analytical processes better than the

Fig. 7. Table showing the result of a drill-down operation on the ‘‘m


well-known on-line transactional processing (OLTP) paradigm. Infact, when Codd et al. coined the acronym OLAP, it was to highlightthe ‘‘A’’ (analytical) capabilities of a new category of software asopposed to the ‘‘T’’ (transaction) capabilities of typical DBMS.

‘‘OLTP databases are built in a way that make the data difficultto exploit by managers and analysts who need aggregated andsummarised information, rapid comparisons in space and time,syntheses over millions of occurrences, trends discovery and othercomplex operations to support their tactical and strategicdecision-making processes’’ (Rivest et al., 2005). Still today, the Aand T capabilities cannot be combined in a unique database ifa large set of data is involved: either the developed database isgood for transactions such as the storage and retrieval of smallchunks of data, the checking of their integrity, their simple butsimultaneous querying by a large number of users, and similartransactions, or the database is good for the analysis of trends,comparisons, cross-tabulations, summarised information, andother types of decision-oriented information. Accordingly, theOLAP Council (1995) defined OLAP as ‘‘a category of softwaretechnology that enables analysts, managers and executives to gaininsight into data through fast, consistent, interactive access toa wide variety of possible views of information that has beentransformed from raw data to reflect the real dimensionality ofthe enterprise as understood by the user’’. Thus, it was toovercome the limitations inherent in transactional systems thatOLAP was invented and positioned as a key element of a largemarket known as ‘‘business intelligence’’ (BI).

Analytical and transactional technologies do not competeagainst each other, rather they complement each other and are

unicipality’’ level to get the information for each ‘‘erosion site’’.


Fig. 8. Table showing the number of buildings affected per municipality synchronised with a map helping to illustrate the density of buildings affected per municipality.


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usually implemented to go hand-in-hand within organisations.Typically, OLAP data are copies of a subset of transactionalsystems or data warehouses, and they have been restructured tobecome an application-specific datacube that can be exploredinteractively.

SOLAP is thus a new category of software that supports the in-teractive exploration of spatial databases containing several levelsof information granularity, many themes and many epochs thanksto the use of operators such as spatial drill-down, roll-up, drill-across, slice, pivot, etc. (see Fig. 3 and following for illustration ofthese SOLAP functionalities). SOLAP also supports many views thatmay be synchronised during the exploration of data: maps, tablesand diagrams (see Fig. 3). Such a multi-dimensional approach ofanalysis is said in the BI industry to be more in agreement with theend user’s mental model of the data.

With regard to today’s PPGIS solutions, it is necessary torecognise that the typical type of processing offered by the GIStechnology is of the OLTP type. Consequently, PPGIS typicallysuffer from the same limitations. On the other hand, SOLAP isoptimised to facilitate complex analysis and to improve the

Fig. 9. Table showing the length of land affected by protection works in


performance of spatial database queries involving thousands ormore occurrences. It is meant to better fulfil the need foraggregated information, spatio-temporal comparisons, cross-tabulation of spatially-referenced data, and multi-scale in-teractive data exploration. As shown in the Fig. 3, SOLAP supportsthe iterative nature of analytical processes because it allows usersto explore and navigate across different themes at different levelsof aggregation and to rapidly visualise the results withoutrequiring mastery of a query language. Data can be visualised onmaps, tables or statistical charts which can be synchronised atwill. It typically requires only a few mouse clicks and less than10 s to obtain the information, whatever the level of aggregationand complexity of the query. Such performance is necessary toremain within the cognitive band identified by Newell (1990) foradequate interactivity. Although it is well beyond the goal of thispaper to present the underlying concepts and challenges that arespecific to spatial OLAP, the next paragraphs highlight thecapabilities that we found to be of interest in the context ofpublic participation, even though SOLAP was not built with thispurpose in mind.

relation to land use in the municipalities of Maria and Bonaventure.


Fig. 10. Graph of the length of land affected by protection works in relation to land use in the municipalities of Maria and Bonaventure.


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Towards a SOLAP-based PPGIS: simulated case

Context specifications

This simulated case stems from the first project of the mainauthor (Bilodeau and McHugh, 2006) and has been designed to first-test some hypothesis regarding SOLAP usage in a PPGIS situation. Forthis simulation, we supposed that the provincial government ofQuebec recently established a new law, aimed at protecting thecoastal environment from human activity. This law implies thatcoastal municipalities are forced to maintain or to return theircoastal regions to their natural state. Many local governments areaffected by this new law because of a high concentration ofpopulation established along the St Lawrence River. The situation iscritical in the Gaspesie region where natural erosion strongly affectsthe coasts and municipalities must often build structures in order to

Fig. 11. Table showing the length of land affected by protection works in relatio


protect coastal roads from erosion. Consequently, a high percentageof the St Lawrence shore is affected by man-made structures, knownas ‘‘protection work’’, such as riprap, breakwaters, wood walls, andother similar structures. For this particular reason, the provincialgovernment allowed the municipalities of Gaspesie to keepprotecting their coast from erosion with structures, but only up to40% of the total coastline in their jurisdiction.

If we look at the situation in more detail in the municipalitiesof Maria, Saint-Simeon and Bonaventure, we can see that manydecisions need to be taken. For instance, 85% of Maria’s coastalroads are actually protected by man-made infrastructures whilethe situation in Bonaventure and Saint-Simeon is less dramaticwith 56% and 39%, respectively, of their coasts being in the samesituation. To meet the new legal requirements, these 3 munici-palities have to decide ‘‘where’’ they will act in order to respectthe proportion authorised.

n to environmental issues in the municipalities of Maria and Bonaventure.


Fig. 12. Table showing the length of protection works per land use in Maria in relation to the distance between the road and the shore.


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Going back to Arnstein’s (1969) ladder of citizen participation,we present in the next sections two examples of SOLAP applica-tions. The first SOLAP application fits between the information (3)and the consultation (4) levels of participation. (Fig. 4) In the sec-ond SOLAP application, citizens’ opinions are taken into accountbut they are not directly involved in the final decision-making, thuswe may position this SOLAP application between the consultation(4) and dialogue (placation; 5) levels. The examples and figuresprovided will help to present some capabilities of the SOLAP tech-nology which are of particular interest for such PPGIS applicationsand which cannot be achieved with conventional GIS.

First SOLAP application

As mentioned earlier, the first application basically aims atinforming citizens about the local situation and giving them theopportunity to compare and share their opinions about differentscenarios of intervention. In order to represent and characterise therisk of erosion along the costal roads in the municipalities of Maria,Saint-Simeon and Bonaventure, the land located between the roadand the water line is divided into 40-m wide parcels (measuredalong the road). Each parcel is then characterised with thefollowing data that are necessary to evaluate the risk of erosion:

physical characteristics of the parcels: shore type (beach, cliff .),average slope (from DTM), average height, and the distancebetween the road and the water line;description of potential environmental issues for each parcel:for example, the presence of a bird nesting area;

Fig. 13. Table showing the result of a drill-down operatio


description of potential human issues: specific land use (urban,tourist, rural .).

Depending on data availability, this application gives theopportunity to measure the length of all coastal land within an area,the length of the coastal land that is affected by protection work,the ratio of land affected by protection works, the number ofbuildings affected, and the total cost ($) needed to delete theprotection works. In addition to these measures, we build up twopossible scenarios of intervention which specify ‘‘where’’ theintervention should take place, based on different weighting of theparameters used. The results provided are in terms of a new ratio ofcoastal land affected by protection works and the money ($) neededto perform the work. These scenarios are two different possibilitiesthat can then be compared and discussed through the differentfunctionalities of the SOLAP application. For the purpose of thispaper, we simulate two use-cases involving the two levels ofinteraction previously identified (cf. Section 3.1), and describethrough these use-cases how SOLAP is used to follow a series ofsimulated actions that one could find during public participation.The simulated actions of the two use-cases are presented in thefollowing sections as well as the real SOLAP manipulations, numberof mouse clicks and answer times for the users.

Simulated actions for use-case 1

Task 1. Determine the length of coastline (total and protected)and the proportion protected (Fig. 5).If we want to see the distri-bution of these measures by municipality, we drill-down on the

n to get the specific distances between 0 and 10 m.


Fig. 14. Table showing the proportion of land affected by protection works for each proposed scenario and for the actual situation.


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‘‘toutes les parcelles [all parcels]’’ line title with a single click andimmediately obtain the lengths per municipality (Fig. 6).

We can then drill-down on this ‘‘municipality’’ level to obtaineven more detailed information, that is, the lengths for eachspecific region under supervision, called ‘‘erosion sites’’ (Fig. 7).

As far as interactivity is involved, it took a total of 4 s and 7 clicksto execute these manipulations. Three measures (the three lengthdata in the three columns) were observed at three different levelsof abstraction (for all parcels, for each municipality, for each erosionsite) and could easily support comparisons and immediatediscussion.

Task 2. We want to know the total number of buildingsaffected in each municipality.

We select the right measure (number of buildings affected), thusdeselect the three previous measures at the same time (length ofcoastal land, length of works, proportion of coastal land affected byworks). Then, from the ‘‘erosion sites’’, we roll-up (drill-up) to the

Fig. 15. Synchronised sets of maps


level of ‘‘municipalities’’ and display the result on a map. We maycreate a collection with the two existing views (i.e. the table and themap), enabling their synchronisation so that any operation done inone view will be automatically reflected in the other one (Fig. 8). Inthis particular example, we can see by the table that both Maria(left greyed polygon) and Saint-Simeon (centre greyed polygon)have the same number of buildings affected (256). However, themap brings complementary information as it shows that the den-sity in Saint-Simeon (number of buildings affected/length of shore)is higher than the density in Maria (left greyed polygon).

The important aspect here is that it took a total of 14 clicks and10 s to both generate the results and create the collection, onceagain supporting the discussion as it takes place or when actionsare performed.

Task 3. We want to compare the municipality of Maria andBonaventure in order to understand how the protection worksare distributed relative to land use type (urban, rural, tourist,natural .).

and tables per municipality.


Fig. 16. Table showing the 2 scenarios in terms of costs ($) per municipality.


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We first select the right measure (length of works), we thenmake a pivot operation to place the ‘‘municipalities’’ on thecolumns (above the measure), and add the ‘‘land use’’ dimension onthe rows (Fig. 9). With this comparison we can see that in themunicipality of Maria (right column), the protection works areconcentrated in rural areas (3495 m/5414 m), while they are con-centrated in an urban area (1749 m/2791 m) in the municipality ofBonaventure (left column).

We can illustrate the same results on a graph by selecting thechart view (Fig. 10).

Once again, the SOLAP application gives the opportunity toillustrate the desired information using different formats (tables,graphs and maps, single or combined, synchronised or not) asrequested. For the last action, it took a total of 7 clicks and 4 s togenerate the requested table and one more click to obtain thestatistical chart. The results were instantaneous.

Task 4. Same comparison, i.e. the length of coastal land affectedby protection works in the municipalities of Maria and Bona-venture, but now with regard to the different environmental issues.

After changing the ‘‘land use’’ dimension for the ‘‘environment’’dimension and coming back to the table view (Fig. 11), we can seethat in the municipality of Maria (right column), more than half ofthe protection works are in spawning ground areas (3417 m/5414 m), compared to the municipality of Bonaventure (left column)where most of the protection works are in fishing areas (2120 m/2791 m). This information was obtained after 4 clicks and 3 s.

Task 5. We want to know, in relation to the distance between theroad and the shore, how the protection works are distributed foreach type of land use in the municipality of Maria.

Fig. 17. Table showing the scenarios in terms of both costs ($, columns 2 and 4) and


After selecting only the Municipality of ‘‘Maria’’, adding the‘‘land use’’ dimension to the columns and replacing the ‘‘environ-ment’’ dimension by the ‘‘road–shore distance’’ dimension, weobtain the desired table (Fig. 12). From there, if we are particularlyinterested in the distances between the road and the shore that areless than 10 m, we can drill-down on the group of distancesbetween 0 and 10 m (first row) and see the distribution as a func-tion of the specific distances (Fig. 13).

All this information was obtained with 9 clicks in 3 s, plus onemore click to drill-down to the more precise distances between0 and 10 m. In this query, three types of data were cross-tabulatedfor two different levels of granularity.

Task 6. We want to compare the scenarios of interventionproposed in terms of costs and the resulting new proportionsaffected by protection works for each municipality.

A new comparison table and a new map are created usinga pivot (for the parcels) and introducing three new measures (ratioof coastal land presently affected by works, affected according toscenario 1, affected according to scenario 2) (Fig. 14). We can alsocompare both scenarios at the same time by creating a new map,a new table, creating two collections (of 1 map and 1 table) ofsynchronised views and selecting only one measure (i.e. onescenario) for each set of views (Fig. 15). We can also select one tableand change the measure for two new measures, i.e. the cost of eachscenario, in order to compare them in the same table per munici-pality (Fig. 16). Furthermore, we can add the proportion of affectedcoastal land in the same table (Fig. 17).

It took a total of 14 clicks to execute these queries and a total of60 s. To these statistics, we have to add the time it took tosynchronise the views which is about 1 min and 30 s.

proportion affected by protection works (columns 1 and 3), per municipality.


Fig. 18. Table showing the effects of the first scenario on the different types of land occupation.


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Task 7. We want to explore one of the scenarios in detail.

We select the municipality ‘‘Maria’’ and the measures ‘‘ratio ofcoastal land presently affected by works’’ and ‘‘ratio of coastal landaffected according to scenario 1’’ while we add the ‘‘land use’’dimension on the other axis. In the resulting table, we can see thatfor the municipality of Maria, the focus is on the rural land use.Presently, 92% of this type of land occupation is affected byprotection works and if this scenario is accepted, only 12% willremain affected.Fig. 18

If we focus on the rural area and add the data about theenvironmental issues, we can find that the regions where theintervention may take place are spawning ground areas (2% vs.100%), which means that we want to focus on these regions andgive them back a natural aspect (Fig. 19).

By changing the view to a map, it is possible to explore in detailthe exact sites where scenario 1 will act (Fig. 20). The utilisation oforthorectified aerial photographs in the background enablesviewers to localise themselves more easily.

For the latter manipulations, it took 2 min and 30 clicks toexecute these required queries. Three dimensions were cross-tabulated and three levels of abstraction were explored, from theglobal level to the detailed level.

Overall, for all the actions of use-case 1, it took a total of 5 min ofcomputer processing and 86 mouse clicks to perform all multi-scaleexplorations, cross-tabulations, synchronisations and viewsdesired during the analysis scenario. Similar tasks have been donewith traditional GIS software (ESRI ArcGIS 9.2). The requested times

Fig. 19. Table showing the effects of the first scenario for the rural zones on the different enMaria.


to compute such tasks with GIS technology were generally 8 timeslonger than with SOLAP. This is due to the fact that using GISrequires making SQL queries (instead of simple mouse clicks) and,to the fact that performing aggregate tasks using a GIS is notstraightforward compared to the use of a drill-up operator. To ourknowledge, no GIS-based public participation system couldperform such a task on-the-fly like this SOLAP prototype was ableto do. In other words, only the SOLAP could adequately support thepublic participation process described in the last use-case.

Second SOLAP application

The second application is similar to the first one in terms ofthemes of analysis. However, in this case we demonstrate how newmeasures can be calculated on-the-fly to help reassess interventionpriorities. The formulas are essentially summations of weightsgiven to the different characteristics (environment, physical,human). By immediately seeing the results, citizens can thencomment on the weights given to the characteristics and give theirown suggestions of a formula for new measure calculations. Themain objective of such application is to build a consensus related tothe priority of intervention.

Simulated actions for use-case 2

Task 1. We want to propose a formula of priority of inter-vention.The first formula proposed gives a weight of 10 for the

vironmental issues and comparison with the present situation for the municipality of


Fig. 20. Map showing a detailed view of the situation.


ARTICLE IN PRESS

areas where the distance between the road and the shore is higherthan 10 m, a weight of 30 for the rural or natural type of landoccupation, a weight of 20 for the spawning ground areas, andfinally a weigh of 50t for the embankment type of shore. Once thisformula is entered in the SOLAP as a derived measure, we canimmediately explore the data interactively as we did in the firstuse-case. For example, Fig. 21 shows a table displaying a newcalculated measure (priority proposal 2) obtained by dragging thisnew measure on the column axis and the municipalities on the rowaxis. Because these weights are not totally objective it could(ideally) reflect a user’s perspective or interests and differentresults would be generated with different weights.

Then, as shown in Fig. 22, drilling-down to the ‘‘erosion sites’’level of abstraction shows that the region of Maria Ouest is theregion to be prioritised.

By drilling-down again we can explore in detail the erosion siteof Maria Ouest and see where exactly the interventions need to beprioritised according to the formula proposed.(Fig. 23)

Fig. 21. Table showing the global priority


For this example, it took 1 min to create the on-the-fly formula,7 clicks to see the results and 5 s to display all three views (tablesand map). Then, one may continue interactively to perform similaractions, build new priority formulas and display the results at thedesired level of abstraction, cross-tab the data with other themes,compare the results of different priority formulas, discuss theresults, add comments (e.g. red-lining), and so on. In other words,the expert-user manipulating the SOLAP application caninteractively support the questioning of the participants andsimulate new use-cases as long as the required base data are in-cluded a priori in the data structure (datacube).

Discussion and conclusion

Through these two use-cases of simulated actions, we had theopportunity to illustrate some functionality of the SOLAP technol-ogy and demonstrate its potential to support more efficient PPGISapplications. SOLAP applications do not require a high level of

of intervention for each municipality.


Fig. 22. Table showing the result of a drill-down operation to obtain the erosion sites.


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technical skills to be used properly and they can help boost publicparticipation by offering increased responsiveness to ad hocqueries, either about details, global views or comparisons (Allenand Goers, 2002). We can easily and rapidly extract all theinformation we need and it is easy to navigate through the differentlevels of abstraction simply using drill-down and drill-up tools. Weare able to see on maps, tables and graphs the results of anyselection, separately or simultaneously, as well as to change theselection and observe the impact of such a change instantaneouslyon all these views in a synchronised way. Such capabilities help tojustify and explain decisions, compare scenarios and assess theirimpacts. Due to a well-constructed database and the use of a visu-alisation tool, it was possible to get an answer to all the actions ina total of 97 clicks and 6 min. All the answers were practicallyinstantaneous, meaning that the public did not have to wait to seethe results of their interrogations or to renounce asking questions

Fig. 23. Map showing a detai


because it would have taken too much time to obtain a result or itcould not be done.

Furthermore, it was possible to try suggestions from the publicabout the priorities of action, see the impacts, and performcomparisons and cross-tabulations of data at any level of abstrac-tion. It was also possible to easily use the different views availableto better convey the information. The weaknesses of traditionalPPGIS that were identified in Section 1.1 are mostly overcome witha SOLAP-based public participation system: (1) the user interface iseasier than that of a GIS since no query language is required,nevertheless it still requires some technical skills (typically halfa day of training); (2) the aggregation of data found in SOLAPtypically leads to quantitative measures that refer to qualitativeinformation organised into hierarchical themes defined by theusers; (3) the level of interactivity provided efficientlysupports collaborative and participative processes, and (4) queries,

led view of the situation.



ARTICLE IN PRESS

cross-tabulations of data, spatio-temporal analysis and multi-scaleexploration of data can be realised on-the-fly.

Finally, although we have not done it in the applications, it iseasy to add red-lining with public comments and to tag multimediadocuments as in any GIS application. In other words, levels 3–6 ofthe participation ladder were made possible with SOLAPtechnology.

Could all of these queries have been done using SQL languageand a classical GIS system to support public participation in such aninteractive way? The answer is no, unless one spent several monthspreparing such applications (as opposed to a development periodof a day to half a week for such SOLAP applications if the raw dataare clean, as was the case in this project). Of course, SOLAP iscertainly not the magic and universal solution to solve all theproblems related to the development and use of PPGIS applications(one size never fits all). However, since SOLAP was developedspecifically to support the interactive exploration of spatial data inthe context of geographic knowledge discovery and for decisionsupport, it seemed natural to see its unique potential to bettersupport public participation in a PPGIS. Thus, it appears to us that,at least from a technological perspective and according to thespatio-temporal context of participation (cf. Fig. 2) in which it cansuccessfully take place, SOLAP is a powerful and useful solution tomake PPGIS better achieve its goals.

Acknowledgements

The authors wish to acknowledge the financial support ofCanada NSERC Industrial Research Chair in Geospatial Databases forDecision Support (Hydro-Quebec, Defence Canada, NaturalResources Canada, Transport Quebec, Intelec, KHEOPS, Holonics,Syntell, DVP, Laval University) and of the Social Sciences andHumanities Research Council (Canada SSHRC).

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