The tasks of the crowd : a typology of tasks in geographic information crowdsourcing and a case study in humanitarian mapping

In the past few years, volunteers have produced geographic information of different kinds, using a variety of different crowdsourcing platforms, within a broad range of contexts. However, there is still a lack of clarity about the specific types of tasks that volunteers can perform for deriving geographic information from remotely sensed imagery, and how the quality of the produced information can be assessed for particular task types. To fill this gap, we analyse the existing literature and propose a typology of tasks in geographic information crowdsourcing, which distinguishes between classification, digitisation and conflation tasks. We then present a case study related to the “Missing Maps” project aimed at crowdsourced classification to support humanitarian aid. We use our typology to distinguish between the different types of crowdsourced tasks in the project and choose classification tasks related to identifying roads and settlements for an evaluation of the crowdsourced classification. This evaluation shows that the volunteers achieved a satisfactory overall performance (accuracy: 89%; sensitivity: 73%; and precision: 89%). We also analyse different factors that could influence the performance, concluding that volunteers were more likely to incorrectly classify tasks with small objects. Furthermore, agreement among volunteers was shown to be a very good predictor of the reliability of crowdsourced classification: tasks with the highest agreement level were 41 times more probable to be correctly classified by volunteers. The results thus show that the crowdsourced classification of remotely sensed imagery is able to generate geographic information about human settlements with a high level of quality. This study also makes clear the different sophistication levels of tasks that can be performed by volunteers and reveals some factors that may have an impact on their performance

Being specific about geographic information crowdsourcing : a typology and analysis of the Missing Maps project in South Kivu

Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kiv

A grounding-based ontology of data quality measures

Data quality and fitness for purpose can be assessed by data quality measures. Existing ontologies of data quality dimensions reflect, among others, which aspects of data quality are assessed and the mechanisms that lead to poor data quality. An understanding of which source of information is used to judge about data quality and fitness for purpose is, however, lacking. This article introduces an ontology of data quality measures by their grounding, that is, the source of information to which the data is compared to in order to assess their quality. The ontology is exemplified with several examples of volunteered geographic information (VGI), while also applying to other geographical data and data in general. An evaluation of the ontology in the context of data quality measures for OpenStreetMap (OSM) data, a well-known example of VGI, provides insights about which types of quality measures for OSM data have and which have not yet been considered in literature

Crowdsourcing geographic information for disaster management and improving urban resilience: an overview of recent developments and lessons learned

In the past few years, crowdsourced geographic information (also called volunteered geographic information) has emerged as a promising information source for improving urban resilience by managing risks and coping with the consequences of disasters triggered by natural hazards. This chapter presents a typology of sources and usages of crowdsourced geographic information for disaster management, as well as summarises recent research results and present lessons learned for future research and practice in this field

Leveraging OpenStreetMap to support flood risk management in municipalities : a prototype decision support system

Floods are considered the most common and devastating type of disasters world-wide. Therefore, flood management is a crucial task for municipalities- a task that requires dependable information to evaluate risks and to react accordingly in a disaster scenario. Acquiring and maintaining this information using official data however is not always feasible, especially for smaller municipalities. This issue could be approached by integrating the collaborative maps of OpenStreetMap (OSM). The OSM data is openly accessible, adaptable and continuously updated. Nonetheless, to make use of this data for effective decision support, the OSM data must be first adapted to the needs of decision makers. In the pursuit of this goal, this paper presents the OpenFloodRiskMap (OFRM)- a prototype for a OSM based spatial decision-support system. OFRM builds an intuitive and practical interface upon existing OSM data and services to enable decision makers to utilize the open data for emergency planning and response

Endosomal MR1 Trafficking Plays a Key Role in Presentation of Mycobacterium tuberculosis Ligands to MAIT Cells

Mucosal-Associated Invariant T (MAIT) cells, present in high frequency in airway and other mucosal tissues, have Th1 effector capacity positioning them to play a critical role in the early immune response to intracellular pathogens, including Mycobacterium tuberculosis (Mtb). MR1 is a highly conserved Class I-like molecule that presents vitamin B metabolites to MAIT cells. The mechanisms for loading these ubiquitous small molecules are likely to be tightly regulated to prevent inappropriate MAIT cell activation. To define the intracellular localization of MR1, we analyzed the distribution of an MR1-GFP fusion protein in antigen presenting cells. We found that MR1 localized to endosomes and was translocated to the cell surface upon addition of 6-formyl pterin (6-FP). To understand the mechanisms by which MR1 antigens are presented, we used a lentiviral shRNA screen to identify trafficking molecules that are required for the presentation of Mtb antigen to HLA-diverse T cells. We identified Stx18, VAMP4, and Rab6 as trafficking molecules regulating MR1-dependent MAIT cell recognition of Mtb-infected cells. Stx18 but not VAMP4 or Rab6 knockdown also resulted in decreased 6-FP-dependent surface translocation of MR1 suggesting distinct pathways for loading of exogenous ligands and intracellular mycobacterially-derived ligands. We postulate that endosome-mediated trafficking of MR1 allows for selective sampling of the intracellular environment.Career Development Award: (#IK2 CX000538); U.S. Department of Veterans Affairs Clinical Sciences Research and Development Program (MJH); U.S.Department of Veterans Affairs Biomedical Laboratory Research and Development Program (DML) Merit Award: (#I01 BX000533); American Lung Association: (RT-350058)

Being Specific About Geographic Information Crowdsourcing: a Typology and analysis of the Missing Maps project in South Kivu

Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kivu

Crowdsourcing geographic information for disaster management and improving urban resilience: an overview of recent developments and lessons learned

In the past few years, crowdsourced geographic information (also called volunteered geographic information) has emerged as a promising information source for improving urban resilience by managing risks and coping with the consequences of disasters triggered by natural hazards. This chapter presents a typology of sources and usages of crowdsourced geographic information for disaster management, as well as summarises recent research results and present lessons learned for future research and practice in this field

Volunteered Geographic Information for Disaster Risk Reduction—The Missing Maps Approach and Its Potential within the Red Cross and Red Crescent Movement

For the last few years, the increasing need for humanitarian support has led to increasing demand and responsibilities for the international humanitarian system. This trend raises questions regarding the use of alternative and complementary data sources and potential additional actors and communities that could be involved in support efforts and cover some of the tasks of humanitarian organizations. The article provides an overview of the Red Cross and Red Crescent movement, their practices and activities as well as current needs and challenges. The article illustrates the potential of OpenStreetMap and digital volunteers for humanitarian activities, with a particular focus on disaster risk reduction in the scope of the Missing Maps project. The background and objective of the collaborative project as well as its potential and impact for the Red Cross and Red Crescent movement are elucidated. The conclusion and outlook section presents future plans and visions to make further use of the potential of the Missing Maps approach in additional sectors and contexts