The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses
2. Materials and Methods
2.1. OpenStreetMap Dataset and Ecosystem
2.2. Conceptual Model and Measurement Framework
- Engagement and Skill
- describes the knowledge a user has about the project, how experienced she is, and how willing she is to contribute. It can be assumed that skill rises with engagement as stated by Hacar et al. .
- Physical Location
- Digital Location
- is made up of two parts: the “data area” a user contributes to and, in case of VGI, the respective “geographic space” (compare physical location). The data area describes the digital data space around the contribution. Through their semantic or (geo)spatial proximity, these objects are related and therefore influence each other. Among others, this could be abstracted by attributes like the amount and type of (geo)data already present at a virtual (geo)location at the time of a contribution (see Figure 2).In contrast, in VGI, the “geographic space” digitally (or virtually) visited fundamentally influences data production, e.g., through aspects like landscape appearance. It can be distant from the physical one (remote mapping) and therefore have different attributes. A mapper may be located in a coastal European area while editing data describing features in a mountain range in Asia (see Eckle and de Albuquerque ).
- Community Involvement
- is the interaction of a mapper with the community at a mappers physical and digital location. It is a vital part of any contribution that has among others been identified by Mooney and Corcoran .
- Personal Influences
- are a supplementary “soft” layer of influences. These affect users in a number of different ways from the motivation or goal a user has during participation up to the personal interest, gender, psychological condition, etc. Some of these aspects have already been analysed (see for example Coleman et al. , Budhathoki and Haythornthwaite , Gardner et al. ).
2.3. User Metrics
- Engagement and Skill
- covers the users activeness and mapping style. The activeness was seen as the number of contributions to the OSM database; her editing style was described by the proportion of creations, tag and geometry changes as well as the diversity of edit types and the complexity of edits. The diversity was calculated using the Shannon Index of biodiversity, framing each edit type as one species (e.g., creation, deletion, etc.) . The complexity on the other hand was measured on a six step ordinal scale from a deletion being the least complex action up to the creation of a very complex multipolygon. In addition, the quality of her edits were calculated based on the conformity with the JOSM validation tool. JOSM is one of the most used and sophisticated editing software available for the OSM database. It is shipped with an extensive rule set for automatic quality assurance that can be run against the data. It will report errors and warnings, where the requirements of the static rule set are not met .
- Physical Location
- defines an approximation of the permanent residence of a mapper (home location). It was derived from the location of the event assuming mappers would participate in events near their residence ( See Mooney et al.  or Danziger  for two edge cases where this assumption may be challenged). This information was available as the time and venue of an event are the minimum information required in event announcement texts. For the Control Group (CG) (see Section 2.4) the area with most edits throughout the users mapping career was used as home location, following one of the procedures suggested by Neis and Zipf . The physical location was seen as a static attribute for each mapper assuming that far distance changes of residence are very rare. It also seems extremely unlikely that a mapper relocates as an effect of event attendance. Accordingly, this metric was excluded from the analyses.
- Digital Location
- was defined by the digital region surrounding the edit issued. The digital locations or ”data areas” were between 0.02 to 25 km depending on the edits’ extent. It was described by the element, tag and mapper density defined by the number of distinct elements and tags that were currently present in the area and the number of distinct mappers that edited the area in the past. In addition, the diversity of present OSM map features (see OpenStreetMap Wiki Contributors ) was calculated. Analogous to the contribution diversity the Shannon Index was used, this time grasping each map feature as one species. In addition, a set of distance (i.e., similarity) measures was computed to respect the fact that mapping in an area with similar attributes to the user’s home area is easier than mapping in a completely foreign area. These measures were based on dividing the world into areas of equal attributes across the economic, cultural, population density and biome dimensions (see more details in Section 2.4). The implementation calculated the percentage of edits located in areas with different attributes than the home region (see physical location). For each mapper and each dimension, the world was thus separated in “regions that are similar to the home region” and “regions that are distinct to the home region”, and the share of edits in the latter regions out of all edits was calculated. The definition of a “remote mapper” therefore changes from its solely geographical or spatial perspective to an attribute perspective here. A mapper was considered a remote mapper if she contributed to areas with different attributes in terms of economic potential, cultural groups, population density or landscape appearance compared to her home region.
- Community Involvement
- refers to the community integration or community work of a mapper and was measured in terms of supplementary project activity (i.e., non mapping activity). Users allocating time to the OSM project in addition to the actual mapping were seen as more integrated into the community. This dimension was captured calculating the length of changeset comments, changeset discussions as well as OSM map notes and notes discussions issued by a user. The length was defined as the number of distinct words used per comment. These features are of large importance for the OSM community but not mandatory in order to contribute to the database. The more information is provided through these channels, the higher the transparency and possible community interaction outside physical meetings or direct messages.
- Personal Influences
- is a dimension whose measurement in a quantitative manner proved to be a complex task as it has not yet been done in the literature. We therefore omit this dimension but acknowledge its importance and strongly encourage future research in this field.
2.4. Data Sources
2.5. Experimental Setup
- Engagement and Skill.
- Generally, CFM attendees showed similar behaviour to CG mappers. CRM mappers on the other hand presented unique behaviours, making more contributions (83, CFM: 16, CG: 9, Figure 6a), focusing on creations (86% of edits vs. 33%, 47% for CG and CFM, respectively, Figure 6c) more than on tagging (2% vs. 23%, 28%, Figure 6b), and showing lower diversity (0.77 vs 1.17, 1.23) and more complexity in contributions (average of 2.14 vs. 1.34, 1.84). The edit diversity was generally low among all three groups (maximum measured: 3.53, maximum possible: 8.30). One area in which CFMs were different from the CG was the quality of data, with CFMs producing on average 0.04 errors per contribution, while the CG produced 0.11 errors (CRMs were the least accurate with 0.33 errors per edit).
- Digital Location.
- As the name indicates, CRMs mapped abroad with a mean of around 98% of edits in foreign economies, cultures and physical geographies and 84% in areas with different population densities compared to their home region. Both other groups rather tended to map “at home” with around 84% to maximum 98% of mean edits in regions of similar nature compared to their home region.As mentioned in Section 2.5 the digital area analysis was only available in monthly resolution and is therefore not analysed for the short time interval during the event as well as the time interval of one month after the event.
- Community Involvement.
- The community measures applied showed that the CG users had longer changeset comments (mean of 3.44 unique words per changeset) while CFMs had only 0.07 words more per changeset compared to CRMs (CFM: 1.56, CRM: 1.49). No distinction could be found for the discussion size while notes were more actively used by the CG (mean 0.85 unique words) and CFM users (0.28) but not at all by CRM users.
3.1. Effects on Newcomers
- Engagement and Skill.
- Although the quantity of data produced one month after both event types was ten to 14 edits higher in median than for the CG, the mean values were for both types lower. This high median quantity could not be maintained on the long term with more than 50% of the mappers not contributing after one month. Field happenings tended to have a much lower mean mapping activity volume among their participants than the CG in the one year time interval, meaning six to twelve months after the event (see Figure 7a). Individuals’ activity sparked within the different time intervals with only a handful of mappers continuously contributing over multiple intervals.Those CFM mappers who stayed active had a distinct style of contributing with a higher share of geometry changes and a higher diversity of edits. Remote mappers stayed active in creating data and doing complex edits (see Figure 7c). These effects survived for most of the analyses time period. The same applied for the tag changes share that stayed very low compared to the CG (see Figure 7b). The geometry changes share for CRM mappers alternated around the CG in mean but stayed slightly higher in median for the one and six months interval. The quality of data produced by CRM mappers was at best equal to the other groups.
- Digital Location.
- The data area edited did, in some time intervals, differ when users had attended a happening. The element density, meaning the number of elements per area surrounding the edit issued, was lower within the period of one to six months after the event with only 67 (CFM) and 90 (CRM) elements per km (CG: 670), but the groups then started to blend in with the CG. The tag density on the other hand was lower only for CRMs in the one to six months and one to two years periods after the event with only 1.4 tags per element for the six months period (1.1 for the two years period, CG: 2.3 in both intervals). The mapper density did not differ between the groups.The regional distance on the other hand stayed strongly influenced by events. CRM newcomers stayed remote mappers through the analysed time frame, and field mappers mapped exclusively at home and were indistinguishable from the CG which also mapped mostly at home.
- Community Involvement.
- The community integration of newcomers that took part in events was mostly equal to the CG. Medians and means alternated between 1 and 5 unique words per changeset. Changeset discussions and notes were nearly unused by newcomers in general. Insignificant spikes existed where single users used these features.
3.2. Effects on Advanced Mappers
- Engagement and Skill.
- Advanced happening mappers displayed an increase in mapping in the one month period issuing 294% (CFM) to 476% (CRM) more edits in mean than before the event while the CG had an increase of only 2%. Median values for the CG and remote mappers were 0% and for field mappers 100% due to the large number of non-recurring contributors (see Figure 8a). The mapping type of advanced event attendees did not shift at all. All groups slightly decreased their creations share by around 0.01 to 0.04 (see Figure 8b) while tag changes and geometry changes alternated around 0. The edit complexity did not differ among groups while the edit diversity seemed to generally decrease in all time intervals.
- Digital Location.
- The preferred digital area was only in one case affected by events, when participants after one year turned more towards areas with less users then the CG (CG: −0.01 mean editors per element; CRM: −0.68; CFM: −0.49). Generally, the mapped data area became more and more dense in all time intervals with all groups having mostly positive mean values of up to +274 elements per km. The regional distance was mostly not affected by happenings.
- Community Involvement.
- No effect on the community involvement could be observerd for advanced mappers.
- A group of skilled users mapping rural areas close to their home region, editing the local data or creating new data as necessary but concentrating on quality rather than on OSM community interaction.
- A group of new and advanced users digitising buildings and highways all over the world in large amounts with lower quality but higher complexity.
- The general OSM mapper mapping mostly at home but sometimes abroad and having a balanced creation to change ratio and a medium quality of contribution describing well what she is doing.
5. Conclusions and Outlook
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
- OpenStreetMap History Data Base converted extract of the OSM data base: http://downloads.ohsome.org/ (accessed on 2 September 2019).
- Note and changeset data taken from https://planet.openstreetmap.org/ (accessed on 2 September 2019).
- Global Human Settlement Population Grid by : https://data.jrc.ec.europa.eu/dataset/jrc-ghsl-ghs_pop_gpw4_globe_r2015a (accessed on 2 September 2019).
- The terrestrial ecoregions of the world data set : https://www.worldwildlife.org/publications/terrestrial-ecoregions-of-the-world (accessed on 2 September 2019).
Conflicts of Interest
|CFM||Community Field Mapping.|
|CRM||Community Remote Mapping.|
|GPS||Global Positioning System.|
|HOT||Humanitarian OpenStreetMap Team.|
|JOSM||Java OpenStreetMap Editor.|
|VGI||Volunteered Geographic Information.|
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|Contribution Setting||Field Mapping||Remote Mapping||Bulk Import|
|Community Happening||Community Field Mapping||Community Remote Mapping||Community Bulk Import|
|Digital Platform||Platform Mapping||General Bulk Import|
|Group||Variable Name||Description||Source Involved a|
|Engagement and Skill||Quantity||Change rate of contributions||OSM (Nd, W)|
|Creations share||Difference in share of creations||OSM (Nd, W)|
|Tag-changes share||Difference in share of tag-changes||OSM (Nd, W)|
|Geometry-changes share||Difference in share of geometry-changes||OSM (Nd, W)|
|Edit diversity||Difference in the Shannon Index over abstract edits||OSM (Nd, W, R)|
|Edit complexity||Difference median edit complexity||OSM (Nd, W, R)|
|Quality||Difference in JOSM error delta||OSM (Nd, W)|
|Digital Location||Element density||Difference in element density in mapped areas||OSM (Nd, W)|
|Tag density||Difference in tag density in mapped areas||OSM (Nd, W, R)|
|User density||Difference in unique users per element in mapped areas||OSM (Nd, W, R)|
|Area diversity||Difference in the Shannon Index on map features in mapped areas||OSM (Nd, W, R)|
|Economic distance||Difference in the share of mapped regions of different economic status than the home region’s status||NE, OSM (Nd, W)|
|“Cultural” distance||Difference in the share of mapped regions of different ”culture” than the home region’s “culture”||HU, OSM (Nd, W)|
|Population density distance||Difference in the share of mapped regions of different population density class than the home region’s class||EU, OSM (Nd, W)|
|Physical geography distance||Difference in the share of mapped regions of different population density class than the home region’s class||WWF, OSM (Nd, W)|
|Community Involvement||Comment size||Difference in unique words per changeset comment used||OSM (C)|
|Discussion size||Difference in unique words per changeset discussion used||OSM (C)|
|Notes size||Difference in unique words per note action used||OSM (Nt)|
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Schott, M.; Grinberger, A.Y.; Lautenbach, S.; Zipf, A. The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses. ISPRS Int. J. Geo-Inf. 2021, 10, 164. https://doi.org/10.3390/ijgi10030164
Schott M, Grinberger AY, Lautenbach S, Zipf A. The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses. ISPRS International Journal of Geo-Information. 2021; 10(3):164. https://doi.org/10.3390/ijgi10030164Chicago/Turabian Style
Schott, Moritz, Asher Yair Grinberger, Sven Lautenbach, and Alexander Zipf. 2021. "The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses" ISPRS International Journal of Geo-Information 10, no. 3: 164. https://doi.org/10.3390/ijgi10030164