Open Data Platform Research Articles

MORAL ECONOMIES OF OPEN DATA PLATFORMS

Municipal open data platforms are currently caught in a range of tensions. They rely on an unspecified subject to analyze the data, and yet are surrounded by discourses of "empowerment" and "transparency". They are often most beneficient when approached with data science skills, yet often entail unremunerated digital labor. And they are often engaged by organizations tacking "for Social Good" onto their mandate - the Canada-wide organization Data for Good being a key example. To date, STS research has generated important insights into the political economies of data and platforms that highlight the ways they produce, mediate, circulate, and accumulate surplus and exchange value. Less attention has been devoted to understanding the ways moral values and sentiments are deployed to attract the digital volunteered labor subtending municipal open data platform usage. Those who mobilize these moral economies are deeply situated within capitalist platform economies, and benefit from the free labor of those wishing to improve their communities. In this presentation, we argue that hackathons, datathons, and open data platforms are constituted through moral economies that are entangled within technoscientific capitalist accumulation practices and logics. These moral economies are key ways in which digital labor is procured, and represent a core component of what Boltanski and Chiapello call the "new spirit of capitalism". To substantiate our argument, we draw on an ongoing long-term ethnography into Calgary, Alberta's open data ecosystem. We conclude by politicizing the fissures of these moral economies, to identify the new political strategies that they necessitate.

Health Heatmap of India: An Open Data Platform.

Health Heatmap of India is an open data platform built for bringing together data from diverse sources and facilitating visualization, analysis, and insight building from such data. In this paper, we describe the context and need for such an open data platform and describe the technical aspects of building it. The beta site of the portal is available at https://healthheatmapindia.org.

Integrated machine learning with semantic web for open government data recommendation based on cloud computing

SummaryOpen government data (OGD) is a type of trusted information that can be used to verify the correctness of information on social platforms. Finding interesting OGD to serve personalized needs to facilitate the development of social platforms is a challenging research topic. This study explores how to link the Taiwanese government's open data platform with Facebook and how to recommend related OGD. First, an integrated machine learning with semantic web into cloud computing framework is defined. Next, the linked data query platform (LDQP) is developed to validate its feasibility. The LDQP provides a graphical approach for personal query and links with related Facebook fan pages. LDQP automatically finds highly relevant OGD based on recent topics that users are following on Facebook when users login to Facebook via the LDQP. In this way, the LDQP query result can be dynamically adjusted and graphically displayed according to user's Facebook operations.

Spatial equity of park green space using KD2SFCA and web map API: A case study of zhengzhou, China

In our review of the research on PGS (park green space) spatial equity, little consideration has been given to the impacts of small spatial scales and measurement accuracy on spatial equity assessments. Based on the web map API open data platform (including location and navigation data, etc.), this study established a fine-scaled evaluation framework of spatial equity from the aspects of sensitivity to measurement and the urban micro-perspective. The framework was integrated within the KD2SFCA (kernel density two-step floating catchment area) method, which planners use to accurately locate areas of under or over supply of urban public facilities. Taking Zhengzhou as a case study, we identified 2494 residential areas and 106 PGSs to describe the spatial equity of residents accessing different PGS levels by four travel modes. The results showed that there were significant differences in spatial equity between different PGS levels. Of the three PGS levels, the overall spatial equity for district PGS was the highest, community PGS was second, and municipal PGS was the lowest. We also found that different travel modes had important impacts on PGS spatial equity. One interesting phenomenon was that when residents chose to walk to a higher level PGS, the percentages of the population with “no supply” increased; when residents chose bicycle and private car modes to reach higher level PGS, the percentages of the population with “weak supply” and “over supply” increased. In addition, it is worth noting that community PGS was originally established to meet the needs of residents for short-distance entertainment. However, we found that almost all residents in the study area were in the extreme states of “no supply” or “over supply” when they reached community PGS by walking. These results provide a scientific basis for more reasonable and equitable allocation of urban PGS and the optimization of transportation facilities. This work can also provide a more fine-scaled research perspective and improve the scientific evaluation system for studying urban infrastructure spatial equity.

Motivations of civil society actors to reuse open data. Case study of discrete actors in Lyon

Open data platforms are being widely adapted in cities with a promise to boost the economy and empower citizens. However, researchers have drawn attention to the ineffectiveness of such initiatives, unless they are designed taking into account the local context and ecosystem of actors. Yet, literature review demonstrates a gap in addressing individual motivations of actors and in particular discrete civil society actors to use open data. Building upon studies on individual motivations in open government, we propose a heuristic model of interconnection between societal outcomes of open data and individual motivations of the actors.Analysis of the open data initiative and ecosystem in Lyon is based on interviews and platform analysis. Our findings show that civil society actors in Lyon have the expertise to create knowledge and services from open data, but they fail to appropriate the latter for the lack of communication channels with the platform managers. Consequently, possible modalities of interaction are discussed and further research agenda is proposed to better understand the connection between individual motivations, open data platform design and broader societal outcomes.

Letter to the Editor: Influence of Altitude on the Prevalence and Case Fatality Rate of COVID-19 in Peru

<i>Letter to the Editor:</i> Influence of Altitude on the Prevalence and Case Fatality Rate of COVID-19 in Peru

Reducing Consumer Uncertainty: Towards an Ontology for Geospatial User-Centric Metadata

With the increased use of geospatial datasets across heterogeneous user groups and domains, assessing fitness-for-use is emerging as an essential task. Users are presented with an increasing choice of data from various portals, repositories, and clearinghouses. Consequently, comparing the quality and evaluating fitness-for-use of different datasets presents major challenges for spatial data users. While standardization efforts have significantly improved metadata interoperability, the increasing choice of metadata standards and their focus on data production rather than potential data use and application, renders typical metadata documents insufficient for effectively communicating fitness-for-use. Thus, research has focused on the challenge of communicating fitness-for-use of geospatial data, proposing a more “user-centric” approach to geospatial metadata. We present the Geospatial User-Centric Metadata ontology (GUCM) for communicating fitness-for-use of spatial datasets to users in the spatial and other domains, to enable them to make informed data source selection decisions. GUCM enables metadata description for various components of a dataset in the context of different application domains. It captures producer-supplied and user-described metadata in structured format using concepts from domain-independent ontologies. This facilitates interoperability between spatial and nonspatial metadata on open data platforms and provides the means for searching/discovering spatial data based on user-specified quality and fitness-for-use criteria.

Googling the Lifetime Risk of Stroke Around the World.

Objective: We aimed to utilize the data on lifetime risk of stroke, from Global Burden of Disease (GBD) 2016, in combination with open data platforms to create an interactive map for use by clinicians and members of the public. Further, we explore the relationship between life expectancy and lifetime risk of stroke.Design: Enhancing visual display of large volume of data.Setting: Worldwide estimates of the lifetime risk of stroke obtained from the GBD 2016.Participants: None.Intervention: None.Methods: Data were extracted from a portable document format (pdf) copy of the GBD article on the lifetime risk of stroke and exported into the R programming environment (version 3.4.4). These data were merged with (i) the world map boundary, (ii) open data platforms from the World Bank (life expectancy and income), and (ii) open data from the United Nation Population Prospects 2017. Further we plotted the relationship between the adjusted lifetime risk of stroke and life expectancy.Outcomes: The map of the global burden of stroke shows a higher lifetime risk of stroke among high-income countries than in low-income countries (https://gntem3.shinyapps.io/strokeglobal/). The greatest risk was among upper-middle-income countries such as China and Eastern and Central European countries such as Latvia and Romania. The lifetime risk of stroke increased in countries with higher life expectancy (β = 0.48 ± 0.047, 95% confidence interval = 0.390–0.574, R2 = 0.38, p < 0.01).Conclusion: Overall life expectancy is a major driver of the lifetime risk of stroke. The interactive map enables clinicians to search information about the lifetime risk of stroke interactively and navigate by zooming in and out, while still retaining high resolution.

The Value of Marine Spatial Open Data Infrastructures—Potentials of IHO S-100 Standard tο Become the Universal Marine Data Model

Marine spatial “open” data infrastructures (MSDI) have a significant economic and societal potential for coastal nations and their realization is driven by the evolution of the International Hydrographic Organization’s (IHO) S-100 data model for facilitating marine domain interoperability and the World Wide Web Consortium’s (W3C) best practices for spatial data publishing on the Web. The recent European directive on open data and the re-use of public sector information, known as the “Open Data Directive” is a key driver towards the establishment of “open” MSDIs among other spatial data infrastructures. The paper discusses possible data architectures for the MSDIs, examines the maturity of open data platforms that they could be built upon and compares the most prominent marine spatial data models for their applicability in relation to three marine information domains. MSDIs can facilitate the continuous data capturing of spatial-temporal physical phenomena and human activities at sea and coastal areas, the corresponding data analysis and the decision-making for achieving continual improvement in the marine planning and management processes. MSDIs could play a key role in digital government transformation (DGT) for effective data sharing and offering marine services across various stakeholders. The information provided through a MSDI can be used for safe and efficient operation of maritime traffic, exploration and exploitation of marine resources, marine spatial planning (MSP), integrated coastal zone management (ICZM), environmental protection, and naval and maritime security.

Intent-based networks for 6G: Insights and challenges

Intent-Based Networks (IBNs), which are originally proposed to introduce Artificial Intelligence (AI) into the sixth-generation (6G) wireless networks, can effectively solve the challenges of traditional networks in terms of efficiency, flexibility, and security. IBNs are mainly used to transform users’ business intent into network configuration, operation, and maintenance strategies, which are prominent for designing the AI-enabled 6G networks. In particular, in order to meet the massive, intelligent service demands and overcome the time-varying radio propagation, IBNs can continuously learn and adapt to the time-varying network environment based on the massive collected network data in real-time. From the aspects of both the core network and radio access network, this article comprehensively surveys the architectures and key techniques of IBNs for 6G. In particular, the demonstration platforms of IBNs, such as the Apstra Operating System, Forward Networks Verification Platform, and One Convergence Service Interaction Platform, are presented. Moreover, the industrial development of IBNs is elaborated, including the emerging new products and startups to solve the problems of open data platforms, automated network operations, and preemptive network fault diagnosis. Finally, several open issues and challenges are identified as well to spur future researches.

Zooming Into the Ecosystem: Agency and Politics Around Open Data Platforms in Lyon and Berlin

Open data platforms provide free access to datasets in key areas of urban development. Often provided by the local state, open data platforms constitute a part of smart city strategies worldwide, serving different, potentially contradictory aims, i.e. fostering economic development, enhancing transparency of urban governance and reshaping the relation between citizens and the state. While benefits of open data are often highlighted, recent research has pointed out to open data initiatives failing to account for and include the ecosystem of urban actors and their interests. Instead, open data platforms are embedded in complex networks of actors and institutions, and consequently form both an object and an instrument of urban governance. Our interest lies in understanding how open data platforms are coproduced by different actors based on their conception of open data. Thus, we theorise the development of open data initiatives through a dynamic approach to agency focussing on the strategies of different actor groups shaping open data initiatives and platforms, in specific governance contexts that define barriers and windows of opportunity. Empirically, our paper will analyse the development and governance of open data initiatives and platforms in the cities of Lyon and Berlin. Departing from the initial steps for setting open data on the agenda, we will provide a process-based perspective unpacking actor strategies and agency to shape open data policies, concrete initiatives and platform design. The analysis is based on tracing the development processes and on interviews with representatives of the administration, open data initiatives and civil society. Our analysis identified a narrowing down of open data initiatives to objectives of economic development and efficient administration, despite the existence of broader visions on open data among other actors. This can be traced back to the impact of shifts in the urban governance contexts and high salience of personnel, financial and technical resources for defining the dominant conception of open data.

Ontology-based data acquisition model development for agricultural open data platforms and implementation of OWL2MVC tool

In the open data world, it is difficult to collect data in compliance with a certain data model that is of interest to different types of stakeholders within a domain like agriculture. Ontologies that provide broad vocabularies and metadata with respect to a given domain can be used to create various data models. We consider that while creating data acquisition forms to gather data related to an agricultural product, which is hazelnut in this study, from stakeholders of the relevant domain, the traits can be modeled as attributes of the data models. We propose a generic ontology-based data acquisition model to create data acquisition forms based on model-view-controller (MVC) design pattern, to publish and make use of on the agricultural open data platforms. We develop a tool called OWL2MVC that integrates the Hazelnut Ontology, which illustrates the effectiveness of the proposed model for generating data acquisition forms. Because model creation is implemented in compliance with the selection of ontology classes, stakeholders; in other words, the users of OWL2MVC Tool could generate data acquisition forms quickly and independently. OWL2MVC Tool was evaluated in terms of usability by fifty-three respondents implementing the case-study scenario. Among others the findings show that the tool has satisfactory usability score overall and is promising to provide stakeholders with required support for agricultural open data platforms.

Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of IoT Using Crop-Specific Trait Ontologies

In recent years, Internet-of-Things (IoT)-based applications have been used in various domains such as health, industry and agriculture. Considerable amounts of data in diverse formats are collected from wireless sensor networks (WSNs) integrated into IoT devices. Semantic interoperability of data gathered from IoT devices is generally being carried out using existing sensor ontologies. However, crop-specific trait ontologies—which include site-specific parameters concerning hazelnut as a particular agricultural product—can be used to make links between domain-specific variables and sensor measurement values as well. This research seeks to address how to use crop-specific trait ontologies for linking site-specific parameters to sensor measurement values. A data-integration approach for semantic and syntactic interoperability is proposed to achieve this objective. An open-data platform is developed and its usability is evaluated to justify the viability of the proposed approach. Furthermore, this research shows how to use web services and APIs to carry out the syntactic interoperability of sensor data in agriculture domain.

Visible mechanisms to manage "invisible hand": Dialogues to unite expectations, interests and need for open data platform in Central Asia

Visible mechanisms to manage "invisible hand": Dialogues to unite expectations, interests and need for open data platform in Central Asia

Cultivating open government data platform ecosystems through governance: Lessons from Buenos Aires, Mexico City and Montevideo

Open government data (OGD) initiatives are an emergent platform research topic. There is little understanding how these platforms are governed for the innovation of services using open data, where the cultivation of an installed base of heterogeneous service innovators can lead to increased usage of OGD. In this paper, we draw on established literature from digital platforms research to investigate how service innovation is cultivated in open government data contexts. We employ a comparative case study of open government data platforms in three leading Latin American cities and draw upon the concept of boundary resources taken from platform theory. Our research generates two key contributions. First, we propose a theoretical model, which explains how an OGD platform owner is able to govern the demand and the supply side of its platform to facilitate the cultivation of a platform ecosystem. Second, we develop contributions to practice in terms of a set of recommendations for governments in emerging countries concerning how to establish and manage a vibrant OGD platform ecosystem.

VectorNet's First Annual Entomological Network Meeting

This report describes the structure, contents and outcomes of the first Annual Entomological Network Meeting organized by VectorNet, a European Network for Medical and Veterinary Entomology, held 10–12 March 2020 in Amersfoort the Netherlands. In this meeting, entomological network members and national public and animal health professionals were introduced to the project, the contracting organizations (EFSA, ECDC) and the members of the VectorNet consortium. The focus of the meeting was on VectorNet networking strategies and the involvement of the entomological network members in risk assessments. An overview of ongoing and planned work was given and discussed. The objectives of the project include consolidating the existing European network, to provide scientific support to both ECDC and EFSA in their risk assessments of vectors and vector-borne diseases and to update information on the geographic distribution, abundance and seasonality of targeted arthropod vectors in EU/EEA and neighbouring countries. The target vector groups are mosquitoes, ticks, biting midges, sand flies, and a group of ‘others‘, including fleas and lice. VectorNet will contribute to systematic reviews and the integration of existing databases on vector distribution. The creation of a strong connection between medical and veterinary entomologists is an important step towards implementation of the one health paradigm to fight against and prevent the emergence and spread of VBDs to new areas in Europe. Operating on an open data platform, the project welcomes entomologists to contribute data on vector presence and density.

Development web and mobile application and open data platform for water quality management in Pak Phanang river basin

This paper aims to develop web and mobile application and open data platform to facilitate the community researchers use for monitoring the water quality management in Thailand. The paper developed a mobile and web application to collect and represent WQI data. Besides that, this paper elaborated the open data platform for sharing the WQI data to the other public sectors with two formats are people-readable format and machine-readable format. The population of this research is the community researchers who live in the Pakpanang river basin, including in local authorities, volunteers, and academic researchers. This paper also pays attention to the third parties are living in the outside area, which uses the WQI data. The experiment found that the overall user satisfaction whos participate in this project is in a good rank. The top three ranks of the function usage are: the first rank is a monthly report of the WQI data function. The second rank is a sending the WQI data by the volunteer function, and a calculating the WQI data by the academic researcher function. Finally, The third rank is open data usage function. Also, the measurement station increased from twenty to twenty-two stations. The volunteers expanded from the local authorities, volunteers, and academic researchers to students and teachers. For the future, this paper tries to apply a minimisation method for optimising The WQI parameters and also classify the proper parameters for each measurement station.

Enhancing pedestrian mobility in Smart Cities using Big Data

Smart City is an emerging concept in global urban development. A Smart City applies ICT technologies to provide greater efficiencies for its urban areas and civilian population. One of the key requirements for a Smart City is to exploit data from its ICT infrastructure (such as Internet of Things connected sensors) to improve city services and features such as accessibility and sustainability. To address this requirement, the City of Melbourne (COM) Smart City office maintains several hundred data sets relating to urban activity and development. These datasets address parking, mobility, land use, 3D data, statistics, environment, and major city developments such as rail projects. One promising dataset relates to pedestrian traffic. Data are obtained from sensors and updated on the COM website (City of Melbourne Open Data Platform: https://data.melbourne.vic.gov.au/.) at regular intervals. These data include the number of pedestrians passing 53 specific locations in the central business district and also their times and directions of travel. In a 24 h period, over 650,000 pedestrians were counted passing all locations. Peak rates of several thousand pedestrians per minute are regularly recorded during city rush hours at hotspots making the data amenable to Big Data analysis techniques. Results are obtained in graphical format as heatmaps and charts of city pedestrian traffic using both Microsoft Excel® for static analysis and PowerBI® for more advanced interactive visualisation and analysis. These findings can identify pedestrian hotspots and inform future locations of traffic lights and street configurations to make the city more pedestrian friendly. Further, the experience gained can be used to examine other data sets such as bicycle traffic that can be analysed to inform city infrastructure projects. Future work is suggested that could link these pedestrian flow data with social media data from smartphones and potentially wearable devices such as fitness monitors to correlate pedestrian satisfaction with traffic flow. The ‘happiness’ effect of pedestrians passing through green areas such as city parks can also be quantified. This research was undertaken with the assistance of Swinburne University under its Capstone Project scheme.

Implementation of Digital‐Era Governance: The Case of Open Data in U.S. Cities

AbstractThis article examines the institutional factors that influence the implementation of open data platforms in U.S. cities. Public management scholarship has argued that governance can be transformed by new information technologies that improve transparency and engagement, reduce administrative costs, and support performance management systems. However, this argument ignores key risks for administrators, as well as institutional and political obstacles that can thwart implementation. This article uses hierarchical negative binomial regression to analyze the organizational and institutional features influencing implementation in more than 1,500 departments across 60 cities. Department type and administrative capacity are strongly associated with the number of open data files available, while city‐level institutional characteristics and administrative capacity are not significant factors. Municipal demographics are also identified as a factor, suggesting a potential demand‐side influence from wealthy and technologically proficient residents.Evidence for Practice The implementation of open data policies benefits from targeted approaches at the department level rather than uniform, citywide objectives or requirements. City executive‐level positions such as chief data or information officers are not necessarily associated with successful implementation, measured by the number of open data files made available. Open data implementation involves additional administrative responsibilities and labor at the department level, so city administrators looking to expand the number and variety of data sets available through their open data platforms should devote time and resources to working directly with departments to facilitate and encourage data sharing. Administrators looking to expand the number and variety of data sets available through their open data platforms should consider the costs associated with investing in increasing individual departments’ abilities to balance the additional administrative responsibilities and labor involved.

Production of linked government datasets using enhanced LIRE architecture

This paper describes the enhanced LIRE (LInked RElations) architecture for creating relations between datasets available on open government portals. The architecture is improved to be applicable on different open government data platforms using minimal configuration at the Data processing layer. We evaluated the applicability of enhanced LIRE, its advantages and disadvantages, which resulted in necessary recommendations for the publication of dataset?s metadata to obtain better associations between datasets. Moreover, we introduced a LINDAT indicator that reflects the percentage of linked data in the total possible number of linked data on open government data portals.