Open Data for Environment Sensing: Crowdsourcing Geolocation Data

A Conceptual Building-Block and Practical OpenStreetMap-Interface for Sharing References to Hydrologic Features, 2017

Disaster related scientific data is multidisciplinary by nature, and comprises data entities from observations, experiments, surveys, simulations, models, and higher-order assemblies, along with the associated information to describe and interpret the data. One of the essential elements of life on this planet is freshwater. Sustainable development with disaster preparedness therefore demands sustainable management of the world's limited freshwater resources. However, water resources cannot be properly managed unless we know where they are, in what quantity and quality, and how variable they are likely to be in the foreseeable future. The present work with AGORA's SDI-NODE focuses on connecting dispersed disaster-relevant data to enable easier and faster discovery and access of disaster-related data. The technical framework of environmental data aggregation and unified data sharing method is explored for distributed data integration with a " LOD-enabled SDI-node " .

International journal of health geographics, 2011

Wikification of GIS by the masses' is a phrase-term first coined by Kamel Boulos in 2005, two years earlier than Goodchild's term 'Volunteered Geographic Information'. Six years later (2005)(2006)(2007)(2008)(2009)(2010)(2011), OpenStreetMap and Google Earth (GE) are now full-fledged, crowdsourced 'Wikipedias of the Earth' par excellence, with millions of users contributing their own layers to GE, attaching photos, videos, notes and even 3-D (three dimensional) models to locations in GE. From using Twitter in participatory sensing and bicycle-mounted sensors in pervasive environmental sensing, to creating a 100,000-sensor geo-mashup using Semantic Web technology, to the 3-D visualisation of indoor and outdoor surveillance data in real-time and the development of next-generation, collaborative natural user interfaces that will power the spatially-enabled public health and emergency situation rooms of the future, where sensor data and citizen reports can be triaged and acted upon in real-time by distributed teams of professionals, this paper offers a comprehensive state-of-the-art review of the overlapping domains of the Sensor Web, citizen sensing and 'human-in-the-loop sensing' in the era of the Mobile and Social Web, and the roles these domains can play in environmental and public health surveillance and crisis/disaster informatics. We provide an in-depth review of the key issues and trends in these areas, the challenges faced when reasoning and making decisions with real-time crowdsourced data (such as issues of information overload, "noise", misinformation, bias and trust), the core technologies and Open Geospatial Consortium (OGC) standards involved (Sensor Web Enablement and Open GeoSMS), as well as a few outstanding project implementation examples from around the world.

International Journal of Geographical Information Science, 2013

The Commission on Geoinformation Infrastructures and Standards of the International Cartographic Association (ICA) is working on defining models of spatial data infrastructures (SDI). SDI models from the enterprise and information viewpoints of the Reference Model for Open Distributed Processing (RM-ODP) have already been presented. Our model from the computational viewpoint identifies the main computational objects of an SDI and their interfaces, which are modelled using Unified Modelling Language (UML) component diagrams. Presented here is the first comprehensive SDI model from the computational viewpoint, which enhances the understanding of the computational objects and their interactions in an SDI. This viewpoint complements the previous two and together, the three viewpoints contribute towards a more holistic interpretation of an SDI, which is independent of specific SDI legislation, technology and implementations. For the computational viewpoint, we identified six computational objects, SDI Registry, SDI Data, SDI Processing, SDI Application, SDI Portrayal and SDI Management, and their provided and required interfaces. We describe the interactions of the computational objects in stakeholder activities and the roles they play in the different processes of SDI development and use, which we identified as Initiation, Creation, Management, Manipulation, Access, Processing, Evaluation and Liaison. Tw o t a b l e s s um m a r i se th e S D I se r v i c e s t h a t a r e p r o v i d e d by computational objects for stakeholder activities and SDI processes.

The SAGE Handbook of GIS and Society, 2011

The main purposes of Sustainability Science include understanding, integrating, and modeling nature and society. Geographic Information Science (GIScience) is important to achieve such goals, since it reviews fundamental subjects in spatially-oriented fields, such as geography and cartography, while incorporating more recent developments in cognitive and information science. This chapter identifies the necessary key research questions in GIScience to support environmental sustainability. GIScience is able to contribute to sustainability research in many of its requirements. First, there is the need to create spatially-oriented environmental models that include humans. Such models, along with large amounts of distributed spatial data, can then be used as a source for the creation of sound and enforceable environmental policies. The impact of policies needs to be measured, compared to established goals, and communicated to the society. We argue that the combination of technologies, people, and policies that defines Spatial Data Infrastructures (SDI) is probably the best approximation we have to solve these problems. The kind of sharing that motivates the creation of SDIs can be extended towards the establishment of communities of practice, in which the central theme or subject is approached in various levels of detail and complexity.

2008

Environmental Information Systems (EIS) play a key role in our understanding of the past, current and future status of the environment. In the last 10-15 years, the design of EIS has undergone fundamental changes following both the requirements of the users and the capabilities of the underlying information technologies (IT). This paper first identifies three major trends that have determined these changes: 1) integration of several thematic domains to support interdisciplinary environmental tasks, 2) distribution of EIS to a wider spectrum of users, and 3) permanent functional enrichment with sophisticated functions such as environmental simulations or geo-processing capabilities. It then deduces from these trends the need and the growing importance of open service platforms based on international geospatial standards for the EIS design and its operation. In particular, the open geospatial service architecture of the European research project ORCHESTRA (Open Architecture and Spatia...

ISPRS International Journal of Geo-Information

A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this local knowledge via sketch maps in the context of flooding. The Sketch Map Tool enables not only the visualization of this local knowledge and analyses of OpenStreetMap data quality but also the communication of the results of these analyses in an understandable way. Since the tool will be open-source and several analyses are made automatically, the tool also offers a method for local governments in areas where historic data or financial means for flood mitigation are limited. Example analyses for two cities in Brazil show the functionalities of the tool and allow the evaluation of its applicability. Results depict that the fitness-for-purpose analysis of the OpenStreetMap data reveals promising results to identify whether the s...

Distributed and Parallel Databases, 2014

Very large amounts of geospatial data are daily generated by many observation processes in different application domains. The amount of produced data is increasing due to the advances in the use of modern automatic sensing devices and also in the facilities available to promote crowdsourcing data collection initiatives. Spatial observation data includes both data of conventional entities and also samplings over multi-dimensional spaces. Existing observation data management solutions lack declarative specification of spatio-temporal analytics. On the other hand, current data management technologies miss observation data semantics and fail to integrate the management of entities and samplings in a single data modeling solution. The present paper presents the design of a framework that enables spatio-temporal declarative analysis over large warehouses of observation data. It integrates the management of entities and samplings within a simple data model based on the well known mathematical concept of function. Observation data semantics are incorporated into the model with appropriate metadata structures.

2011

A spatial data infrastructure (SDI) is an evolving concept for facilitating, coordinating and monitoring the exchange and sharing of geospatial data and services. In earlier work, we developed a formal model for an SDI from the Enterprise, Information and Computational Viewpoints of the Reference Model for Open Distributed Processing (RM-ODP). We identified six stakeholders: Policy Maker, Producer, Provider, Broker, Value-added Reseller and End User. The Internet has spawned the development of virtual communities or virtual social networks, which share data with one another and with the public at large. This user-generated content is most obvious in web sites such as Wikipedia to which the general public, rather than domain experts, contribute information. Similarly, the term volunteered geographic information (VGI) is used for geospatial data contributed to datasets by the general public. Increasing costs of official mapping programmes coupled with the availability of high volumes of quality and up-to-date VGI, have led to the integration of VGI into some SDIs. Therefore it is necessary to rethink our formal model of an SDI to accommodate VGI. We started our rethinking process with the SDI stakeholders in an attempt to establish which changes are required to the stakeholders for including VGI in an SDI. The influence of VGI did not necessitate new stakeholders but rather the specialization of them, by defining a number of subtypes for each.

1997

This paper presents UAPE Â Ða computational environment for modeling and designing environmental geographic applications. UAPE Â is aimed at end-users who are experts in their application domain, but who do not have adequate background in software engineering or database design, and thus are unable to take full advantage of available GIS tools. Its goal is to reduce the impedance between the end-users' view of the world and its implementation in Geographic Information Systems. The environment has been designed and implemented so that it can be considered as an auxiliary layer to be coupled to a GIS. The major features of this layer are: it has an open architecture, being independent of a speci®c GIS, so that it can be coupled to different systems; it allows the user to deal only with the conceptual view of the geographic reality, abstracting the implementation details; it supports a geographic application design methodology, fully integrated with a high-level semantic data model, so there is no impedance mismatch between application design and data modeling.

Recent years have seen new ways of collecting geographic information via the crowd rather than organizations. OpenStreetMap (OSM) is a prime example of this approach and has brought free access to a wealth of geographic informationfor many parts of the world, for the first time. The strong growth in the last few years made more and more people consider it as a potential alternative to commercial or authoritative data. The increasing availability of ever-richer data sets of freely available geographic information led to strong interest of researchers and practitioners in the usability of this data -both its limitations and potential. Both the unconventional way the data is being produced as well as its richness and heterogeneity have led to a range of different research questions on how we can assess, mine, enrich, or just use this data in different domains and for a wide range of applications. While this book cannot present all types of research around OpenStreetMap or even the broader category of User Generated Content (UGC) or Volunteered Geographic Information (VGI), it attempts to provide an overview of the current state of the art by presenting some typical and recent examples of work in GIScience on OSM. This chapter provides an introduction to the scholarly work on OpenStreetMap and its current state and summarizes the contributions to this book.