- freely available
ISPRS Int. J. Geo-Inf. 2016, 5(11), 217; doi:10.3390/ijgi5110217
- A generic protocol has been developed which can be applied by new or existing VGI projects. It can also be used retrospectively on existing data and information in current VGI projects or it can be the starting point for case-specific protocols.
- The protocol aims to be inclusive of all participants to VGI projects from new to experienced VGI contributors. Speilman  (p. 123) argues that systems for VGI and user-generated maps should be designed to “foster conditions known to produce collective intelligence rather than privileging particular contributions/contributors”. The protocol only assumes a basic working knowledge of geographic information science with basic file and data handling skills from information technology.
- The protocol has been developed in a bidirectional fashion. We have carefully studied mapping practices in bottom-up approaches (VGI for example) and top-down approaches (NMAs). In this way, we feel that this protocol is positioned in an intersection of the space between these two opposing approaches to the generation and collection of geographic information.
2. Assessing the Benefits of a VGI Vector Data Protocol
2.2. Protocols in Geomatics and Citizen Science
2.3. Consequences of Lack of Protocols
2.3.1. The Lack of Protocol from the Perspective of the Layman Contributor
2.3.2. The Lack of Protocol from the Perspective of Experts
3. Description of the Vector Data Protocol
3.1. Goals and Qualities of the VGI Vector Data Protocol
- Align the vision, mission, and plans of a particular VGI project to policies and procedures for collecting geographic vector data. The protocol should be acceptable to both the VGI project community and the members of the project board or steering committee.
- When possible, satisfy current geospatial standards whilst using methods which have already worked successfully in previous and existing VGI projects.
- The protocol should be structured and managed efficiently, so that an objective review, control and integrity check both from the managers of the project and external subjects are possible at any time. It should also be easily changed and adapted to changes or advances in geospatial technology or in the mission and vision of the applied VGI project, while at the same time allow compatibility with datasets already created.
- Outline how to collect accurate VGI vector data.
- Be effective and available to all the contributors or volunteers of the VGI project.
- Attempt to promote efficient data collection.
- Be reliable by providing information and supporting documentation which are relevant and aligned to the overall objectives of the VGI project.
- Where necessary, include an emphasis on the value of collecting metadata and attribute information about VGI objects created.
- Be accessible by avoiding excessive use of jargon and unnecessary technical, mathematical and scientific detail. Where possible and appropriate, the protocol should be translated into multiple languages. The protocol should be made openly available in a wide range of open formats.
- Include data collection methods that are transparent and clear. The protocol should be easy to adopt by ordinary people, i.e., require the use of well-known or well-understandable procedures to be performed with ordinary devices and tools.
- Be timely by emphasizing the need to ensure that data collection is done in a timely manner. There should not be an unnecessarily long gap between collection and submission to the VGI project.
- Outline data collection procedures ensuring that the volunteers act with due respect and regard for local laws and by-laws, personal health and safety, conservation and respect of natural environment.
3.2. Content of the VGI Vector Data Protocol
- Data model: The expected thematic layers of the VGI project are introduced to make the contributor familiar with the topic and to increase the awareness of what to collect.
- Data collection methods: The contributor is informed about the available data collection methods.
- Vector data characteristics: The contributor is introduced to a number of data characteristics according to the VGI project goal. The above issues are discussed in detail in the following subsections.
3.2.1. Data Model
- Geometry: A unique geometry such as (multi) point, (multi) line or (multi) polygon or a composed geometry allowing multi-scale data collection—e.g., city as a point (small scale) or as a polygon (big scale)—are proposed for each thematic layer. Geometrical issues such as whether a river is captured as an area or a line should be clarified.
- Attributes: Attributes capturing the core descriptive characteristics of each thematic layer are proposed. For example, the “roads” thematic layer captures attributes like name, type, number of lanes, etc. Although the list of attributes can be updated by the users, contributors should be aware of the attributes used by other contributors and the values used to instantiate the attributes. Any legitimate value can be recorded to the attributes but contributors’ taxonomies are encouraged.
- Mapping rules to ensure homogeneity: Rules describing how a real world object should be mapped, e.g., the middle axis is mapped for roads, entrance is mapped for buildings represented by points, the maximum footprint is mapped for buildings represented by polygons, etc.
3.2.2. Data Collection Methods
- The audience of the data collection presentation should be taken into account.
- Lists of “dos and don’ts”, demos, examples, podcasts, videos, etc. are good ways of communication.
- Additional information should be available for the eager user, e.g., hyperlinks to scientific documents.
- Source type: A georeferenced map/photo or an orthorectified image should be used.
- Tool: The use of an optical mouse instead of a touchpad is highly recommended.
- Grid: When a big area or many objects need to be manually digitized, the map/image can be spatially divided into smaller areas in grid. Thus, the identification of the area is facilitated by zooming in/out and exhaustive coverage is succeeded.
- Scale: The scale should ensure a good precision and allow the capture of appropriate details. The scale should be maintained constant over the collection process of a specific thematic layer to assure homogeneous resolution in data capture. Working at the maximum zoom is not always the best practice since it will produce very detailed geometries that will be time consuming and not necessarily fit for use.
- Device settings: Set up GNSS settings to get the best performance of the equipment used.
- Control points: Use a known or standard data set as control points for ensuring high accuracy.
- On field practice: Position of the GNSS antenna for best satellite reception.
- Environmental effects: Understand the influence of the environment on quality, e.g., in the wide open high accuracy is succeeded with low cost devices, whereas multi-constellation tracking and multipath filtering is needed to achieve that level of accuracy in shaded areas.
- License and private issues: Data for import must be appropriately licensed for use in the VGI framework. For this reason, the issues of data license and privacy should be clearly explained.
- Coordinate Reference System (CRS) transformation: imports may need to transform data into the VGI project CRS.
- Schema and data matching: To avoid redundant information and to prevent conflicts, a schema matching needs to be processed followed by a data matching.
- Transformation: Other transformations such as conversion of data format (e.g., KML to shapefile), geometry change (e.g., polygons to points) or generalization (e.g., very detailed roads in less detailed roads) may be needed to ensure quality of the integration process.
3.2.3. Vector Data Characteristics
- CRS: The protocol should clearly state the CRS adopted by the project (e.g., WGS 84). The contributor must always report the CRS used and possible transformations performed. In the case that data are transformed to the CRS of the VGI project from another, one must ensure that the cartographic projection and the datum transformation are performed as expected. Control points should be used to prove that the transformation is correct. If an error measure of this transformation (e.g., RMSE) is known, then it should be reported as metadata.
- Topology and topological rules: The protocol should encourage data integrity provided by topology. This can be accomplished by adopting specific data collection tactics and using GIS tools that ensure correct topology. For example, most data digitization platforms provide tools that permit snapping to the nearest vertex and segment of a line or polygon. A number of GIS tools can also be used to check for topological correctness after data collection. Since topological rules and their implementation are rather complex to understand, expected topological relations should be explained to the contributors through practical examples, e.g., when a road and a railway intersect there must be a common intersection point; adjacent polygons must share the same border; and points of interest (POIs) situated in buildings must be positioned inside the building polygons. The protocol should include topologically correct examples for each thematic layer, documented e.g., with the vector data collected, photos and aerial/satellite imagery.
- Level of detail/scale: The protocol should raise the notion of level of detail or reference scale expected by the data based on the project goal. The level of detail should be maintained over the collection process. This can be accomplished by providing guidance regarding the geometry: minimum details for lines and polygons, minimum dimensions, smallest object size (e.g., building bigger than 20 m2 area, and building bigger than cottage), distance between vertices along a line, or the degree of detail in the classification (e.g., number of categories for land use, etc.). The expected level of detail is related to the data model of the VGI project. The scale issue differs in relation to the data collection method, as stated in Table 1.
- Metadata: The protocol should emphasize the importance of metadata without forcing contributors to enter metadata. Many contributors are not interested/motivated enough to fill up forms of metadata. Only minimal contribution from contributors should be expected. A middle ground between automatic metadata and manual metadata should be considered as a goal. Tools automatically encoding metadata (e.g., zoom level, minimum dimension, resolution, and timestamp) are most appropriate. Metadata may differ according to the collection method (see Table 1). Attributes intended to make comments, to express unexpected or conflict situations, which allow to a better data quality assessment or data integration/analysis, should be recommended to contributors to provide. Table 2 provides an overview of desired metadata for each data collection method.
- Data quality: Elements of spatial data quality such as currency and completeness that have not been covered in the data model, level of detail/scale and topology should be explained to the contributor with the help of examples. Contributors should be urged to give an estimate of the data quality or at least to give a warning if there is a quality problem (bad position signal, low visibility in manual digitizing, etc.).
4. Vector VGI Protocol Implementation
4.2. Stages of Protocol Implementation
- Familiarize with the project by exploring its goals, aims and needs. Understand existing best practices and project specifications, which will facilitate to understand the tasks expected by the project’s contributors and the outcome sought.
- Decide on/pick a proper device for the task. This can range from a simple web browser for on-screen digitizing to more specialised sensors for on-field collection. The device you choose might not be the best possible one, but it should produce data of a suitable quality for the specific purpose of the VGI project you are contributing to.
- Familiarise with the device. This helps novice or inexperienced contributors to avoid creating errors that will propagate to the final datasets. Furthermore, some sensors might need to be correctly parameterized.
- Test collection process. Starting by investing some time in a small demo project will shed light in the entire chain of processes needed. On the one hand, it will help questions to form and answered before real contribution starts. On the other hand, contributors will develop self-confidence or realise that the project is not what they expected. It would be useful to provide some form of “sandbox” development environment where new contributors can simulate the entire chain of processes involved. They can work within the sandbox environment without being concerned with creating problems with the “live” system.
- Ask yourself if the data thereby collectable can be suitable (and therefore useful) for the VGI project in terms of both content and overall quality. If yes, you are ready to start with the real data collection. If not, you may think to choose a different device (starting back from Step 2) and/or to better test the collection process (starting back from Step 4).
4.2.2. Data Collection
- Carefully plan the data collection process according to the considerations made during the previous initialisation stage. Identify the best portion(s) of your time you want to spend in data collection: ideally, this should be large enough to ensure the success of the process even in unfavourable conditions or in case errors occur. If possible, concentrate the amount of time you have chosen to spend into one (or few) long stage(s) rather than into many, short stages, as this usually translates into higher-quality output data. Try to avoid other distractions during the whole data collection process.
- Make sure you have the right device with you and prepare it to be fully working during the data collection process (e.g., in terms of battery power and Internet connection).
- Make sure you can have a real-time access to the VGI project specifications during data collection. This will be very useful in case you do not remember what you should do and/or you find yourself in a situation when you are not sure on how to proceed.
- Perform data collection according to the VGI project recommendations. During the process, report any technical (software/hardware) issue you may experience (which is not caused by a bad choice of the device) as well as any anomalous/problematic situation you may encounter which was not explicitly outlined by the project specifications.
4.2.3. Self-Assessment and Quality Control
- If technically possible, before submitting the collected data to the VGI project server, carefully revise them to check that they are of a suitable quality (in terms of both their geometrical and metadata content) according to the project specifications. In other words, make sure the data you are about to submit can be fully used by the community for the peculiar purpose of the VGI project you are contributing to.
- In case you find errors (in terms of inaccuracy, incorrectness or incompleteness) in your data, fix them by editing/adding the wrong/missing information; if this cannot be done (because you do not know how to correct the data or because the software implementation does not allow you to do so), delete/discard the data; if this is also not technically possible, before submitting your data clearly state that they are wrong or incomplete.
4.2.4. Data Submission
- Once all the necessary checks have been made, submit the collected data to the VGI project server. You will require an active Internet connection to perform this step.
- Make sure the upload operation ends successfully.
4.2.5. Post Data Submission Check
- Your data are now officially available within the VGI project; perhaps the whole community can already find and use them. Before ending the data collection process, give a final check to the data you have just submitted. This is a different kind of check compared to the previous self-assessment/quality control, as you can now check the quality of your data in terms of—roughly speaking—coherence with the project’s context, i.e., together with the data contributed from all the other volunteers. If available, an automatic validation (of both geometry and metadata) can raise errors and/or warnings about the submitted data.
- In case errors are detected (both from you and the automatic validator), edit/add or delete/discard the data as explained in the Self-Assessment and Quality Control stage. This operation applies to both the data you have collected and data uploaded by other contributors. Despite the fact that this protocol is meant to guide the data collection process, the same rules are also valid for updating and deleting incorrect/low quality data which are already present in the VGI project.
4.2.6. Feedback to the Community
- In the same way as the VGI data, also the whole VGI project improves as more and more users contribute to it. Therefore, the recommended final stage of the data collection process is to provide feedback about the experience you have made. Use the available channels provided by the project (forums, mailing lists, social networks, etc.) to express your comments and remarks. Explain whether (and why) the data collection process was easy or problematic, describe any issue you had (e.g., technical problems or unexpected situations) and suggest possible improvements or changes based on your experience. Be precise in your description so that the problem(s) can be easily understood and fixed.
- As VGI is all about people, spread the word about the project to attract new users. The more participants a VGI project has, the more it can become rich in terms of data and data quality.
4.3. Software Implementations of the Protocol
5. Discussion and Future Work
- Spatial Data Experts: Propose guidelines for the creation and the application of a protocol for vector data collection in the VGI project.
- VGI project community/initiators: Create the protocol for vector data collection in the VGI project based on the guidelines and the project special characteristics.
- IT Experts: Implement software interfaces and environments that facilitate the implementation and application of the protocol. We believe that these IT Experts will require the ability to use popular and well known open source (or proprietary) tools for working with geospatial data such as the tools available from OSGeo. We acknowledge and understand that the requirements for the IT implementation of this protocol will be significant and should be examined in more detail at a later stage.
- Users/Contributors: Collect VGI data following the protocol and provide feedback about the process and the protocol itself.
5.2. Future Work and Future Directions
Conflicts of Interest
Appendix A. VGI Creation from Manual Vectorisation
Appendix B. VGI Creation from Field Survey
Appendix C. VGI Creation from Bulk Import
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|Manual Vectorisation||Field Survey||Bulk Import|
|Use a predefined range of zoom levels recommended by the protocol for specific thematic layers and objects.||- When possible, report or define the device survey sampling rate.|
- Provide free text comments on the environmental conditions, weather, non-visibility of satellites, etc.
|- Consider the level of detail and scale of the data and whether the data are appropriate for import into the VGI project.|
- Generalisation may be applied prior to the import.
|Manual Vectorisation||Field Survey||Bulk Import|
|- Information about the background layer or imagery source: resolution, date, etc.|
- Information about the data capture process such as zoom level(s), scale, date/time of digitization, software/environment used, etc.
- Free text comments on the visual quality of the imagery such as cloud cover, tree cover, shadows, etc.
- Original CRS and transformation applied.
|- Device details: GNNS device mark/model, smart phone mark/model.|
- Software used.
- Timestamp/date of collection.
- Type of locomotion such as walking, going by car, etc.
- Free text report about the conditions encountered while sampling such as signal quality, weather, environmental etc.
- Upload of the DOP.
- Original CRS and transformation applied.
|- Existing metadata about the data: date, CRS, scale, license, currency, etc.|
- Additional metadata from both the structured and unstructured metadata (if available).
- Record of the import process such as software, schema transformation (ontologies, geometries, attributes), CRS transformation, etc.
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