Towards a Protocol for the Collection of VGI Vector Data

A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for on-going development and refinement of the protocol

Considerations of Privacy, Ethics and Legal Issues in Volunteered Geographic Information

International audienceToday almost any kind of User Generated Content (UGC) can be situated within a geographic context. Volunteered Geographic Information (VGI) can include many types of UGC, such as georeferenced photographs, social media and text, geographic data themselves, etc. There are legal, privacy and ethical issues raised by VGI, and at present these are not very well studied or understood despite the rise in popularity of VGI. This chapter will discuss, investigate and define some 120 Mapping and the Citizen Sensor of the most prominent issues related to the legal, privacy and ethics topic within VGI. The chapter argues that these issues are not well understood by all of the actors in VGI, and in particular by the producers of this information as well as the users or consumers of this new data source. Creating a better understanding of these issues will be very important in the future development and evolution of VGI in society

Mapping and the Citizen Sensor

Maps are a fundamental resource in a diverse array of applications ranging from everyday activities, such as route planning through the legal demarcation of space to scientific studies, such as those seeking to understand biodiversity and inform the design of nature reserves for species conservation. For a map to have value, it should provide an accurate and timely representation of the phenomenon depicted and this can be a challenge in a dynamic world. Fortunately, mapping activities have benefitted greatly from recent advances in geoinformation technologies. Satellite remote sensing, for example, now offers unparalleled data acquisition and authoritative mapping agencies have developed systems for the routine production of maps in accordance with strict standards. Until recently, much mapping activity was in the exclusive realm of authoritative agencies but technological development has also allowed the rise of the amateur mapping community. The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping presently benefits from vast amounts of spatial data as well as people able to provide observations of geographic phenomena, which can inform map production, revision and evaluation. The great potential of these developments is, however, often limited by concerns. The latter span issues from the nature of the citizens through the way data are collected and shared to the quality and trustworthiness of the data. This book reports on some of the key issues connected with the use of citizen sensors in mapping. It arises from a European Co-operation in Science and Technology (COST) Action, which explored issues linked to topics ranging from citizen motivation, data acquisition, data quality and the use of citizen derived data in the production of maps that rival, and sometimes surpass, maps arising from authoritative agencies

Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data

Individuals share increasing amounts of personal data online. This data often involves–or at least has privacy implications for–data subjects other than the individuals who shares it (e.g., photos, genomic data) and the data is shared without their consent. A sadly popular example, with dramatic consequences, is revenge pornography. In this paper, we propose ConsenShare, a system for sharing, in a consensual (wrt the data subjects) and privacy-preserving (wrt both service providers and other individuals) way, data involving subjects other than the uploader. We describe a complete design and implementation of ConsenShare for photos, which relies on image processing and cryptographic techniques, as well as on a two-tier architecture (one entity for detecting the data subjects and contacting them; one entity for hosting the data and for collecting consent). We benchmark the performance (CPU and bandwidth) of ConsenShare by using a dataset of 20k photos from Flickr. We also conduct a survey targeted at Facebook users (N = 321). Our results are quite encouraging: The experimental results demonstrate the feasibility of our approach (i.e., acceptable overheads) and the survey results demonstrate a potential interest from the users

The (Co-)Location Sharing Game: Benefits and Privacy Implications of (Co)-Location Sharing with Interdependences

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends who view them. Yet, they also represent a severe threat to the users' privacy, as co-location information introduces interdependences between users. We propose the first game-theoretic framework for analyzing the strategic behaviors, in terms of information sharing, of users of OSNs. To design parametric utility functions that are representative of the users' actual preferences, we also conduct a survey of 250 Facebook users and use conjoint analysis to quantify the users' benefits of sharing vs. viewing (co)-location information and their preference for privacy vs. benefits. Our survey findings expose the fact that, among the users, there is a large variation, in terms of these preferences. We extensively evaluate our framework through data-driven numerical simulations. We study how users' individual preferences influence each other's decisions, we identify several factors that significantly affect these decisions (among which, the mobility data of the users), and we determine situations where dangerous patterns can emerge (e.g., a vicious circle of sharing, or an incentive to over-share)--even when the users share similar preferences

Supporting the Multi-Criteria Decision Aiding process: R and the MCDA package

Reaching a decision when multiple, possibly conflicting, criteria are taken into account is often a difficult task. This normally requires the intervention of an analyst to aid the decision maker in following a clear methodology with respect to the steps that need to be taken, as well as the use of different algorithms and software tools. Most of these tools focus on one or a small number of algorithms, some are difficult to adapt and interface with other tools, while only a few belong to dynamic communities of contributors allowing them to expand in use and functionality. In this paper, we address these issues by proposing to use the R statistical environment and the MCDA package of decision aiding algorithms and tools. This package is meant to provide a wide range of MCDA algorithms that may be used by an analyst to tailor a decision aiding process to their needs, while the choice of R takes advantage of the yet poorly explored opportunity to interface data analysis and decision aiding. We additionally demonstrate the use of this tool on a practical application following a well-defined decision aiding process

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

VGI quality control

This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i.e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject