A Conceptual Model for AnalyzingContribution Patterns in the Contextof VGI

Karl Rehrl, Simon Gröechenig, Hartwig Hochmair, Sven Leitinger,Renate Steinmann and Andreas Wagner

Abstract The chapter proposes a conceptual model as foundation for analyzing usercontributions in the context of VGI. The conceptual model is based on a set of actionand domain concepts, which are combined to a task-model describing typical tasks ofvolunteered geographic information contribution. As a proof-of-concept, the modelis applied to two sample data sets that are extracted from the OpenStreetMap (OSM)change history. OSM data samples provide a proof-of-concept concerningthe applicability of the model for crowd activity analysis. The resulting ‘‘contri-bution graph’’, which is a graph-like structure of linked editing actions, can be usedas foundation for analyzing complex contribution patterns.

Keywords VGI � Crowd activity � Contribution analysis � Editing patterns �Conceptual model

K. Rehrl (&) � S. Leitinger � R. Steinmann � A. WagnerSalzburg Research, Jakob Haringer-Straße 5 5020 Salzburg, Austriae-mail: karl.rehrl@salzburgresearch.at

S. Leitingere-mail: sven.leitinger@salzburgresearch.at

R. Steinmanne-mail: renate.steinmann@salzburgresearch.at

A. Wagnere-mail: andreas.wagner@salzburgresearch.at

S. GröechenigCarinthia University of Applied Science, Europastraße 4 9524 Villach, Austriae-mail: simon.groechenig@edu.fh-kaernten.ac.at

H. HochmairFort Lauderdale Research and Education Center, University of Florida,3205 College Avenue, Fort Lauderdale, FL 33314–7799, USAe-mail: hhhochmair@ufl.edu

J. M. Krisp (ed.), Progress in Location-Based Services,Lecture Notes in Geoinformation and Cartography, DOI: 10.1007/978-3-642-34203-5_21,� Springer-Verlag Berlin Heidelberg 2013

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1 Introduction

The term Volunteered Geographic Information (VGI) denotes geographic infor-mation, which is collectively contributed by a heterogeneous crowd of voluntarypeople. Over the last years, VGI has gained increasing interest in the GI researchcommunity (Goodchild 2007). VGI is considered as a serious source forgeographic information (Goodchild 2007; Kuhn 2007), even more triggering achange in information production while challenging science as well as businesses(Budhathoki et al. 2010). While most of the research methods from GI sciencecould be applied to VGI as well (Kuhn 2007), new research strands such as VGIdigital spatial data exchange, collaborative planning through VGI, or societalimpacts of VGI (Elwood 2008) are opened. Budhathoki et al. (2010) propose athree-tiered conceptual framework for VGI, which provides a good referenceframe for classifying VGI-related research. The framework is composed of thethree arenas ‘‘Motivation’’, ‘‘Action and Interaction’’ and ‘‘Outcome’’. Most of theVGI-related research so far can be classified in one of the three arenas. Recentwork addresses questions about the motivation of VGI contributors (Budhathokiet al. 2010; Coleman and Georgiadou 2009; Coleman 2010), different interactionpatterns (Mooney and Corcoran 2012a) and the quality of the outcome (Neis et al.2011). In addition to the three arenas, Budhathoki et al. detail the arenas with sub-arenas. For example, in the context of the arena ‘‘Action and Interaction’’ theconceptual framework defines the three sub-arenas ‘‘Structure’’, ‘‘Action’’,‘‘Norms/Rules-in-use’’. The sub-arena ‘‘Norms/Rules-in-use’’ addresses ruleswithin the community, e.g. what contributors of VGI projects should do or not do.‘‘Structure’’ is the result of applying rules. ‘‘Action’’ addresses questions of howpeople actually contribute within the constraints of structure. While the proposedarenas and sub-arenas provide a good overall frame, more detailed conceptualmodels for analyzing one of the sub-arenas are still missing.

This work proposes such a conceptual frame for the sub-arena ‘‘Action’’, whichsubsumes all kinds of user interaction with the emphasis on information contri-bution. The remainder of the chapter is structured as follows: The next sectionintroduces related work on editing actions in the context of VGI. The followingsection proposes a set of action and domain concepts as foundation of editingpatterns. In the subsequent section action and domain concepts are combined toediting actions representing typical editing patterns. The section afterwards showsa proof-of-concept with sample data from the OpenStreetMap project, which isfollowed by conclusions and an outlook on future work.

2 Related Work

Currently there are two different research strands to analyze action and interactionin the context of VGI: One is a user-centric strand and the other is a data-centricstrand. User-centric means that the analysis starts from the motivation of

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individual users (Budhathoki’s ‘‘Motivation’’ arena) and their activities(Budhathoki’s ‘‘Action & Interaction’’ arena) and generalizes contributionbehavior over specific user groups. Typical research questions are ‘‘How do userscontribute?’’, ‘‘Which roles can be attributed to users or user groups?’’ or ‘‘Is itpossible to identify different interaction styles based on individual user contribu-tions?’’. The other strand is a data-centric one, putting the collective outcome andnot the individual user in focus (‘‘Outcome’’ arena). Typical research questions are‘‘Which features are in the dataset?’’or ‘‘Which updates happened to a feature?’’ or‘‘Which features are missing?’’. The main goal of this research strand is to identifyfeature-related activity patterns.

One of the newer approaches to investigate action and interaction in the contextof VGI is to analyze editing histories of datasets. Some of the VGI projects store acomplete history of all dataset updates, e.g. the most prominent VGI projectOpenStreetMap (Haklay and Weber 2008), which could be used to analyze editingbehavior of the crowd. But even without a complete change history crowd activitymay be reconstructed with regular database snapshots. Over the last years, someauthors have started to analyze crowd activity of VGI projects, specifically usingthe OpenStreetMap history dump. Recently, Mooney and Corcoran followed theuser-centric strand with investigations on social interactions in the OSM Londondataset (Mooney and Corcoran 2012a). Their research addressed the questionwhether editing profiles could be extracted from the contribution history. Haklayet al. (2009) tackled the question of how many users it takes to map an area well.Mooney and Corcoran (2012b) also followed the data-centric strand. The authorsanalyzed the distribution of users contributing to edits in heavily edited features inOpenStreetMap. The authors also proposed an algorithm to access the Open-StreetMap history dump (Mooney and Corcoran 2011).

van Exel et al. (2010) state that both strands are intertwined since data-centricediting patterns are closely related to user-centric ones (because any editing actionis bound to a user). Nevertheless, the question of action in VGI projects is tackledfrom different perspectives and thus a conceptual model could help to integrateboth strands.

3 Towards a Conceptual Model for Editing Actionsin the Context of VGI

One of the first questions related to a conceptual model of user actions is: ‘‘Whatare typical user activities in the context of VGI?’’. Related work distinguishes atleast four different action and interaction activities (Budhathoki et al. 2010; Rammand Topf 2010): (1) contributing geographic information (e.g. creating and editingfeatures), (2) building community structures (e.g. organizing mapping parties,operating mailing lists), (3) working on norms and rules (e.g. contributing todefinitions in the OSM Wiki) and (4) working on community tools (e.g.

A Conceptual Model for Analyzing Contribution Patterns 375

contributing to editors like JOSM). The last activity is not explicitly mentioned inrelated work, but is a necessity of VGI projects, too. Each of the identified useractivities can be further detailed into concrete action and interaction patterns. Forexample, the user activity ‘‘contributing geographic information’’ can be furtherdetailed in the following sub-activities: (1) collecting information (e.g. GPS traces,street names, speed limits), (2) editing features (e.g. drawing features, addingattributes, changing attributes and attribute values, deleting features) and (3)submitting edits to the database. Sub-activities are considered a good starting pointfor a conceptualization process. While sub-activities could be identified for any ofthe aforementioned activities, in this work we focus only on the activity‘‘contributing geographic information’’. We assume that any activity related togeographic information contribution directly affects the dataset and thus can bederived from the change history. According to Guarino (1998), a conceptualizationis ‘‘the formal structure of reality as perceived and organized by an agent, inde-pendently of the vocabulary used or the actual occurrence of a specific situation’’.In order to conceptualize user actions in the context of volunteered geographicinformation contribution, we have to conceptualize actions (‘‘How do userscontribute?’’) and geographic information (‘‘What is the result of actions?’’).

3.1 Action Concepts

One of the approaches for conceptualizing user actions (task modeling) is to buildon the conceptual frameworks of activity theory (Kuuttii 1996). The principle ofactivity theory is to define a ‘‘minimal meaningful context’’ for individual actions.Activity theory structures user activities with the following hierarchical layers:

Activity: A sequence of actions following a certain ‘‘motive’’. Typically anactivity follows a certain strategy.Action: A sequence of operations for reaching a certain ‘‘goal’’. Actions have acognitive component.Operation: The most granular level. Operations are atomic and represent ‘‘well-defined habitual routines’’.

As Kuhn (2001), states activity and action layers may contain several hierar-chical sub-structures. Timpf (2001) proposes four different approaches for derivinggeographic task-models: (1) task analysis, (2) information on past task-analyses,(3) analysis of GIS products and (4) applying knowledge from knowledge engi-neering. In our conceptualization we combine different approaches. We build oninformation from previous task-analyses (e.g. information from related work), weanalyze typical tasks of VGI contributors (e.g. by means of self-experiments aswell as community workshops) and we analyze tools, especially those available asopen source in the context of OpenStreetMap. Building on these informationsources we define the following VGI specific layers for structuring user activity:

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VGI Activity: A sequence of consecutive actions (information contribution) by asingle volunteering user or a group of volunteering users. Activities could bestructured in different dimensions: (1) by users (all actions by one user or a groupof users), (2) by location (all actions in a certain geographic region), (3) by actiontype (all actions belonging to the same or a similar type, e.g. create, edit, delete),(4) by information category (all actions contributing to the same informationcategory, e.g. streets, land use, buildings) and (5) by time.VGI Action: A sequence of consecutive operations by a single volunteering userwithin a timespan. A typical user action is a certain manipulation of a singlegeographic feature.VGI Operation: An atomic operation on a single geographic feature, e.g. creatingthe geometry, modifying the geometry or adding an attribute.

3.1.1 A Basic Set of VGI Operations

If we assume that geographic information is stored in a database, the four basicoperations for persistent data storage (CREATE, READ, UPDATE, DELETE, alsocalled CRUD) are at the heart of any conceptual model (James 1983). Followingthese basic operations, any contribution to a VGI dataset by a volunteered usermay be drilled down to one of the aforementioned operations: CREATE, UPDATEand DELETE (READ could also be considered as a concept, however, since itmakes no changes to the dataset, it is not relevant for contributions). It is worth tomention that each operation has to be uniquely attached to a single user and atimestamp. The resulting conceptual model for VGI operations and their rela-tionships to action and activity concepts is shown in Fig. 1. We further assume thatthe aforementioned database operations may be executed on different informationitems, depending on the geographic information domain. For example, if theoperation CREATE is executed on a geographic feature, it could be detailed to theoperation CREATE FEATURE. In order to further detail operations, a conceptualmodel for the geographic information domain has to be defined. We call theconcepts representing information items ‘‘domain concepts’’. The conceptualmodel for action and activity layers is proposed in a later section, by combiningaction and domain concepts.

3.2 Domain Concepts

Domain concepts are considered as conceptualizations of real-world phenomena inthe geographic domain (Mark et al. 2001). In related work serveral conceptual-izations of geographic phenomena have been proposed (Goodchild 2010). Most ofthe current GIS are based on object-based conceptualizations of real-worldphenomena (Câmara et al. 2009). One such commonly used model is the OpenGISAbstract Specification, Topic 5: Features (Kottman and Reed 2009) specified by

A Conceptual Model for Analyzing Contribution Patterns 377

the Open Geospatial Consortium (OGC). Instead of developing a new conceptualmodel, our approach builds on the OGC specification and adapts this specificationto the requirements of VGI. The OGC specification introduces the concept of ageographic feature as representation of a geographic phenomenon. Each feature iscomposed of a geometry, which is bound to a spatial reference system and afeature type. A feature type defines a set of attributes which is used to describe thefeature. Features have a flat structure (e.g. other features may not be part of afeature). In addition to the feature specification the OpenGIS Abstract Specifica-tion, Topic 8: Relationships between Features (Kottman 1999) adds the notion ofrelationships. Relationships are necessary to structure feature groups and featurehierarchies.

Since the OpenGIS Abstract Specification is a generic approach for modelinggeographic phenomena it is considered a good conceptual foundation for modelingVGI, too. However, VGI projects typically do not build on OGC specifications dueto various reasons (e.g. complexity, missing freedom) and come with their own,community-driven models. Despite of a number of differences, we also foundsimilarities such as the notion of a map feature as digital representation ofgeographic phenomena in OpenStreetMap.1 However, the description of featuresdoes not follow strict rules like feature types in the OGC model, but is community-defined. In many VGI projects the minimal necessity for the definition of a geo-graphic feature is a geometry (at least a pair of coordinates). Meaning is attachedto geometries with a set of optional key-value pairs (so-called tags). In order tobuild a VGI database like OpenStreetMap any community has to agree on a set ofrules for sucessful collaboration (e.g. OpenStreetMap relies on a minimal datamodel and a community-driven Wiki describing domain concepts). The definitionof useful attribute sets is an ongoing community process documented in the OSMWiki. There are always several proposals how to tag features and it typically takessome time until the community agrees on one of the proposals (e.g. see ProposedFeatures in the OSM Wiki). In OpenStreetMap exists a well-established conceptcalled primary feature, which comes near to the notion of a feature type, but it isnot strongly typed. Since there is no strict validation in the data submissionprocess, it is possible to submit a feature geometry to the OpenStreetMap databasewhile omitting tags.

Fig. 1 Relationships between operation, action and activity concepts

1 http://wiki.openstreetmap.org/wiki/Map_Features

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Having these differences in mind, our approach for a conceptual domain modelbuilds on some of the concepts of existing models, but adds adaptations accordingto the needs of VGI. At least the model has to be capable of missing feature typesas well as feature types with differing attribute sets (tag sets). We assume thatattributes or attribute values do not follow strict rules and any attribute as well asany attribute value may be committed to the database. Although these findings aremainly based on VGI in the context of OpenStreetMap, we consider Open-StreetMap as being prototypical for similar VGI projects. It is worth to mentionthat the model is based on an object-based conceptualization of geographicphenomena and we assume that the spatial reference is described as vector in a2-dimensional geometrical space. The model does not fully cope with othernotions of VGI such as geo-tagged multimedia content (e.g. geo-tagged photo-graphs at Flicker or geo-tagged Twitter messages). We further assume that theneed for a relaxed conceptual domain model can be attributed to the aspect‘‘volunteered’’ in VGI, providing the community with a high degree of flexibilityand freedom. Ramm and Topf state ‘‘The intention of the OpenStreetMap projectalways was to implement the simplest thing that could possibly work.’’ (Rammand Topf 2010). This statement could be possibly taken as synonym for theflexibility and freedom of VGI projects.

In order to avoid any confusion between our conceptual domain model for VGIand the OpenGIS Abstract Specification, we call our domain model VolunteeredFeature Specification (VFS). At the heart of the specification is the notion of aVolunteered Feature (VF), which is conceptually similar to the OpenGIS FeatureSpecification, but adds the following relaxations for being compatible to VGIdataset instances:

A Volunteered Feature (VF) is bound to a Volunteered Geometry (VG), but mayexist without a Volunteered Feature Type (VFT) and thus a VF is considered notstrongly typed.

The specification of a Volunteered Geometry (VG) is based on the geometrytypes in the OGC OpenGIS Object Model, but adds simplifications (Fig. 2).

A Volunteered Feature Type (VFT) is composed of a primary volunteeredattribute, which defines the VFT. Volunteered Attributes (VATT) may be freelyattached to VFs without following a strict scheme. The definition of VATTs andtheir values does not follow a strict scheme, but allows for arbitrary values.Schemes for VFTs and rules for attaching VATTs to VFs are community-defined.A typical medium for specifying the rules is a community Wiki.

A Volunteered Relation (VR) defines relationships between arbitrary VFs. Asproposed in the OpenGIS Abstract Specification, Topic 8, Relationships betweenFeatures, VFs may have different VGs (e.g. points and polygons) and VFTs (e.g.features composing a public transport station). VRs may be recursive, meaningthat VRs may include other VRs.

Figure 2 illustrates the proposed model of domain concepts as UML classdiagram.

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4 Combining Action and Domain Concepts

By now we have defined the conceptual basis for modeling actions (task-centricview) and the domain of geographic information (domain-centric view). A com-bination of both would facilitate a conceptual model being capable of dealing witharbitrary editing actions.

The first step towards a combined conceptual model is to define, which oper-ation may be executed on which type of volunteered feature. As foundation foraction concepts we defined a set of three atomic operations: CREATE, UPDATE,DELETE. In combination with the domain concepts Volunteered Feature (VF) andVolunteered Relation (VR) the following combined operations could be derived:CREATE VF, UPDATE VF, DELETE VF, CREATE VR, UPDATE VR andDELETE VR. From the domain model we assume that a VF is always created witha VG (volunteered geometry). If the VF gets deleted, also the VG is deleted. Fromthe domain model we further derive that if a VF exists, it may be updated in thefollowing ways: ADD VFT, ADD VATT, REMOVE VFT, REMOVE VATT,MODIFY VG, MODIFY VATT and MODIFY VFT. Thus, the action model has tobe extended with the following operations ADD, REMOVE and MODIFY, whichfurther detail the operation UPDATE. Table 1 lists possible combinations ofoperations and VFs/VRs.

The resulting set of operations already considers the previously defined relax-ation rules for VFs. For example, the scheme allows to CREATE a VF without

Fig. 2 Class diagram for modeling volunteered features

Table 1 Conceptual scheme for combining action and domain concepts

Operation Volunteered feature (VF) Volunteered relation (VR)

CREATE VF (VG) VRDELETE VF (VG) VRADD ATT, VFT VFT, VATT, VF, VRREMOVE ATT, VFT VFT, VATT, VF, VRMODIFY ATT, VG VFT, VATT

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specifying the VFT or it is possible to ADD arbitrary VATTs without relying on astrict scheme of feature types. For simplicity we call combinations of operationand domain concepts ‘‘domain operations’’.

In addition to the overall scheme for domain operations, Table 2 further detailsthe conceptual scheme with possible relationships between operations andOpenGIS Simple Geometry Types.

4.1 Towards Actions: Rule-Based Aggregations of DomainOperations

Based on action and domain concepts, the model can now be extended to theaction and the activity layers. In contrast to operations, actions have to fulfill thefollowing requirements: (1) the action can be fully described with a sequence ofone or more domain operations, (2) each operation has to be executed by the samesingle user, (3) each operation has to be executed at a single moment in time andthe timestamps of sequent operations have to be consecutive, meaning that noother operation of the same user has been executed in between and (4) the actionfulfills a goal-oriented manipulation of a VF or VR. As an example we describe aninstance of the action concept ‘‘contribution of a feature’’, which can be defined asa sequence of the following domain operations: (1) CREATE VF, (2) ADD VFT(optional), (3) ADD VATT (optional) and (4) ADD VATT (optional). If necessary,the action could be further detailed with more specific actions like ‘‘create pointfeature’’ or ‘‘create line feature’’. It is important to mention that the concept of anaction is inherently seen as a ‘‘rule-based aggregation over domain operations’’.Thus, by adding aggregation rules for domain operations, as many actions asnecessary could be defined. In order to demonstrate the applicability of theapproach, we define a set of possible actions for VGI contributions (Table 3). Theproposed action set is derived from typical user-tasks in the context of Open-StreetMap, but could be most likely applied to other VGI projects as well.

4.2 Towards Activities: Rule-Based Filtering of Action Sets

According to activity theory, user activities are based on concrete motives. In thecontext of VGI typical motives are: users strive towards fully mapping their local

Table 2 Operations in relationship to OpenGIS simple geometry types

Operation Point Line Linear ring Polygon

CREATE X X X XDELETE X X X XADD Point Point Linear ringREMOVE Point Point PointMODIFY VG, VATT VATT, VG VATT, VG VATT, VG

A Conceptual Model for Analyzing Contribution Patterns 381

surrounds, users strive at getting the number one in the (local) community or usersstrive towards a high level of positional accuracy of their contributions. Thus, itmakes sense to define an activity as ‘‘a group of actions following specificmotives’’. Thus, in order to group actions to activities, actions have to be filtered byone or more criteria derived from one or more motives. Table 4 proposes possiblefilter rules for action sets.

5 Proof-of-Concept: Applying the Model on a Real-WorldDataset

In order to prove the concept we apply the model on the OpenStreetMap changehistory. OpenStreetMap is one of the most relevant VGI projects and thus con-sidered a good example for a proof-of-concept. On the one hand, due to the openlicense, the OSM dataset is of high value for the research community. On the otherhand, the OSM community explicitly specifies the structure for interactions with

Table 3 Proposed action set for describing VGI contribution tasks

Action Description

Create point VF A point feature with a point geometry is createdUpdate point VF The spatial reference of a point VF is modifiedDelete point VF A point VF is deletedCreate line/polygon VF A VF with a line or polygon geometry is created and

a VFT is addedUpdate line/polygon VF The spatial references of a line or polygon geometry

are modifiedDelete line/polygon VF A VF with a line or polygon geometry is deletedAdd points line/polygon VF One or more additional point VFs are added to a line

or polygon VFRemove points line/polygon VF One or more point VFs are removed from a line

or polygon VFSplit line/polygon VF A line or polygon VF is split into two VFsMerge line/polygon VF Two line or polygon VFs are merged to one VFCreate VR A relation is createdDelete VR A relation is deletedAdd member VR One or more VFs are added as members to a VRUpdate member VR The role of one or more members is modifiedRemove member VR One or more VFs are removed from a VRAdd VFT VF/VR A primary attribute is added to a VF or VRUpdate VFT VF/VR The primary attribute of a VF or VR is modifiedRemove VFT VF/VR The primary attribute of a VF or VR is removedAdd attributes VF/VR One or more attributes are added to a VF or VRUpdate attributes VF/VR An attribute value of one or more attributes is modifiedRemove attributes VF/VR One or more attributes are removed from a VF or VR

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the OSM database in the OSM Wiki.2 For deriving action and operations conceptswe analyzed the OSM Wiki, especially the part on the OSM API,3 related literature(Ramm and Topf 2010) as well as editing tools such as JOSM.4 Operationconcepts in OpenStreetMap are widely based on the CRUD paradigm. Domainconcepts are specified in the OSM Wiki. The conceptual data model is rathersimple and based on the concept of VFs. In OSM a VF could be a node or a way,depending on the VG. Linear Rings are modeled as a specific form of ways withthe same start and end node. Polygons are either modeled as Linear Ring or asrelation. The concept of VATT is called tag and the concept of a VFT is repre-sented by the notion of a primary tag. In addition to VFs, the OSM data model alsointroduces the concept of relations, which is defined in analogy to the afore-mentioned VR concept. Table 3 instances the previously defined VolunteeredFeature Specification (VFS) with the OpenStreetMap data model.

5.1 Building Model Instances from the OSM Change History

We test the conceptual model with sample data from the OSM change history. TheOSM history includes all changes back to October 2007 (although the project wasstarted in 2004, due to a change in the API the history is only accessible back to2007). The basic algorithm for accessing the data has been previously described(Mooney and Corcoran 2011). For extracting the data using the OSM API wedeveloped a standardized process (Fig. 3). This process is capable of building agraph-like representation of domain operations and action aggregates for arbitraryfeatures or feature sets (within a configurable bounding box).

We conducted a preliminary test of the model with OSM data for differentgeographic regions in Europe and the US. In order to get first results concerningcrowd activity we applied the extraction process on sample data from two Austrian

Table 4 Proposed activity groups and filter rules for action sets

Activity criteria Filter rules for action sets

By users All actions of a single user or a specific user group, e.g. female usersBy location All actions in a certain region, e.g. in UKBy action type All actions of a certain type, e.g. creations of point featuresBy information

categoryAll actions manipulating features of a certain feature type, e.g. land use,

streets, buildingsBy time All actions within a certain timespan, e.g. during a monthMixed criteria Filter rules with different criteria, e.g. all creation actions of point features

of female users in London

2 http://wiki.openstreetmap.org/wiki/Main_Page3 http://wiki.openstreetmap.org/wiki/API_v0.64 http://josm.openstreetmap.de/

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cities (Linz and Villach) for the years 2010 and 2011. Figure 4 shows two maps ofthe inner city districts and the bounding boxes (195,488 and 212,891 m2) we usedfor data extraction.

Fig. 3 UML activity diagram showing the data extraction and model building process for OSM

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Table 5 lists some contribution indicators. All indicators are calculated from thechange history data within the bounding boxes.

A first comparison of editing activity in both cities shows that OSM mappers inLinz are by far more active compared to mappers in Villach (Fig. 5a). While therewas a significant increase in editing actions (per user and year) in Linz from 2010to 2011, this value remained nearly equal in Villach (although the number ofmappers doubled in Villach and reached the number of mappers in Linz). Also theaverage number of editing actions per feature is lower in Villach, although therehas been a significant increase from 2010 to 2011 (Fig. 5b). The mapper/inhabitantratio (number of mappers per 1,000 inhabitants) reveals that there is an equal orbetter established OSM community in Villach compared to Linz. We consider thefirst results as good proof of the conceptual model as well as the extractionprocess. But we are also aware that the proposed approach can only be thefoundation for a punch of analysis in the context of more detailed investigations oncrowd activity.

Fig. 4 Bounding boxes for sample data extraction from the cities of Linz and Villach in Austria

Table 5 Contribution indicators for the years 2010 and 2011 extracted from the OSM changehistory

Linz (2010) Linz (2011) Villach (2010) Villach (2011)

Active mappers 32 24 11 24Mappers/inhab. (91000) 0.17 0.13 0.18 0.40Number of operations 4,644 8,757 206 1,194Number of actions 1,222 2,262 132 408Average. op./user/year 145.13 364.86 18.72 49.75Average actions/user/year 38.19 94.25 12 17Average op./feature 11.24 9.63 1.25 4.81Average actions/feature 2.96 2.49 0.8 1.65

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6 Conclusions and Outlook

Analyzing patterns of user contributions in the context of VGI has gained con-siderable attention over the last years. VGI projects such as OpenStreetMap fosterthis research strand by offering access to the full history of changes. Althoughsome authors have already analyzed minor parts of the dataset, the question of howto conceptually deal with the data still remains. The paper proposes a conceptualmodel as a foundation for a uniform and standardized process for analyzing usercontributions. Although the paper only proves the concept of the proposed modelwith one VGI project (OpenStreetMap), we assume that instances of theconceptual model could be adapted to other VGI projects as well. The proposedconceptual model has to be adapted in the following way: (1) define a new instance

Fig. 5 Comparison of mapper activity over 2 years in two Austrian cities

Table 6 OSM domain operation concepts as instances of the conceptual model

Node, way (VF) Relation (VR)

Operation Node(point)

Way(line)

Closed way(linear ring)

Relation (polygon, multipoint,multiline, multipolygon)

CREATE X X X XDELETE X X X XMODIFY X X X XADD Tag Tag, node Tag, node Type, member (node, way,

closed way, relation), tagREMOVE Tag Tag, node Tag, node Type, member (node, way,

closed way, relation), tagUPDATE Coordinates, tag Tag, node,

startEndTag, node,

startEndType, tag

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of the model (similar to the instance we propose for OSM in Table 6), (2) adaptaction concepts and aggregation rules and (3) adapt the process for accessingcontribution data (Fig. 3). The proposed approach closes the gap between usercontribution data and a conceptual model laying the foundation for comparableanalysis of contribution patterns. It is worth mentioning that the proposedapproach is only applicable to a VGI project if data about user contributions isaccessible. This is the case for some VGI projects (e.g. OpenStreetMap), but notfor others (e.g. Google Map Maker).5

The proposed conceptual model is considered as a first step towards morecomplex analyzes of crowd activity. At the end of the proposed extraction processwe store operations and actions as a graph-like structure which we call ‘‘contri-bution graph’’ (e.g. a graph database like Neo4j6 could be used). We expect acontribution graph to be a universal basis for complex analysis, especially forhaving a closer look at different kinds of crowd activities. One of the possiblefuture research directions is to find ‘‘prototypical contribution patterns’’ leading togood or bad data quality. Identifying such patterns is considered a necessary stepin the definition of quality indicators for VGI.

References

Budhathoki NR, Nedovic-Budic Z, Bertram B (2010) An interdisciplinary frame forunderstanding volunteered geographic information. Geomatica 64(1):313–320

Coleman DJ (2010) The potential and early limitations of volunteered geographic information.Geomatica 64(2):209–219

Coleman DJ, Georgiadou Y (2009) Volunteered geographic information: the nature andmotivation of producers. Int J Spat Data Infrastruct Res (Special issue GSDI-11)

Câmara G, Vinhas L, Clodoveu D, Fonseca F, Carneiro T (2009) Geographical informationengineering in the 21st century. In: Research trends in geographic information science,Springer, Berlin

Elwood S (2008) Volunteered geographic information: key questions, concepts and methods toguide emerging research and practice. GeoJournal 72(3–4):133–135

Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal69(4):211–221

Goodchild MF (2010) 20 years of progress: GIScience in 2010. J Spat Inf Sci 1:3–20Guarino N (1998) Formal ontology and information systems. In: Using ontologies for integrated

geographic information systems, IOS Press, Amsterdam, pp 3–15Haklay M, Basiouka S, Antoniou V, Ather A (2009) How many volunteers does it take to map an

area well? the validity of Linus’ law to volunteered geographic information. Geog J47(4):1–13

Haklay M, Weber P (2008) OpenStreetMap: user-generated street maps. IEEE Pervasive Comput7(4):12–18

James M (1983) Managing the data-based environment. Prentice Hall, New JerseyKottman C (1999) The OpenGIS abstract specification, topic 8: relationships between features

5 http://www.google.com/mapmaker?hl=de6 http://neo4j.org/

A Conceptual Model for Analyzing Contribution Patterns 387

Kottman C, Reed C (2009) The OpenGIS abstract specification, topic 5: featuresKuhn W (2001) Ontologies in support of activities in geographical space. Int J Geogr Inf Sci

15(7):613–631Kuhn W (2007) Volunteered geographic information and GIScience. NCGIA UC Santa Barbara,

pp 13–14Kuuttii K (1996) Activity theory as a potential framework for human computer interaction

research. In: Nardi BA (ed) Context and consciousness: activity theory and human-computerinteraction. The MIT Press, Cambridge, pp 17–44

Mark DM, Skupin A, Smith B (2001) Features, objects, and other things: ontological distinctionsin the geographic domain. In: Montello DR (ed) Spatial information theory, proceedings ofCOSIT 2001, Springer, Berlin, vol 2205. pp 489–502

Mooney P, Corcoran P (2011) Accessing the history of objects in openstreetmap. In: ProceedingsAGILE 2011: the 14 th AGILE international conference on geographic information science,Springer, Utrecht, p 155

Mooney P, Corcoran P (2012a) How social is openstreetmap? In: Proceedings of AGILE 2012Mooney P, Corcoran P (2012b) Characteristics of heavily edited objects in openstreetmap. Future

Internet 4(1):285–305Neis P, Zielstra D, Zipf A (2011) The street network evolution of crowd sourced maps:

openstreetmap in Germany 2007–2011. Future Internet 4(1):1–21Ramm F, Topf J (2010) OpenStreetMap, 3rd edn. Lehmanns media, BerlinTimpf S (2001) Geographic task models for geographic information processing. In: Meeting on

fundamental questions in geographic information science, Manchester, UK, pp 217–229van Exel M, Dias E, Fruijtier S (2010) The impact of crowdsourcing on spatial data quality

indicators. In: Proceedings of the 6th GIScience international conference on geographicinformation science, pp 213

388 K. Rehrl et al.