Purpose: This paper aims to assess if the extent of openness and the coverage of data sets released by European governments have a significant impact on citizen trust in public institutions.Design/methodology/approach...Purpose: This paper aims to assess if the extent of openness and the coverage of data sets released by European governments have a significant impact on citizen trust in public institutions.Design/methodology/approach: Data for openness and coverage have been collected from the Open Data Inventory 2018(ODIN), by Open Data Watch;institutional trust is built up as a formative construct based on the European Social Survey(ESS), Round 9. The relations between the open government data features and trust have been tested on the basis of structural equation modelling(SEM).Findings: The paper reveals that as European governments improve data openness, disaggregation, and time coverage, people tend to trust them more. However, the size of the effect is still small and, comparatively, data coverage effect on citizens' confidence is more than twice than the impact of openness.Research limitations: This paper analyzes the causal effect of Open Government Data(OGD) features captured in a certain moment of time. In upcoming years, as OGD is implemented and a more consistent effect on people is expected, time series analysis will provide with a deeper insight.Practical implications: Public officers should continue working in the development of a technological framework that contributes to make OGD truly open. They should improve the added value of the increasing amount of open data currently available in order to boost internal and external innovations valuable both for public agencies and citizens.Originality/value: In a field of knowledge with little quantitative empirical evidence, this paper provides updated support for the positive effect of OGD strategies and it also points out areas of improvement in terms of the value that citizens can get from OGD coverage and openness.展开更多
Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese ...Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese A-share listed firms(2010–2022)and apply a staggered difference-in-differences model to investigate how data sharing impacts firm-level supply chain risk.Supply chain risk decreases significantly following PDOP establishment.Data sharing via PDOPs alleviates the“bullwhip effect”and promotes supply chain diversification,mitigating supply chain risks.In more complex firms,those with more advanced digital innovation,as well as non-state-owned firms,data sharing plays a greater role in alleviating supply chain risks.These findings increase awareness of the significance of data resources and offer practical guidance for enterprises’supply chain risk management.展开更多
Purpose:This research endeavors to investigate the impact of open government data on corporate investment,emphasizing the exploration of underlying mechanisms,heterogeneous effects,and implications for investment effi...Purpose:This research endeavors to investigate the impact of open government data on corporate investment,emphasizing the exploration of underlying mechanisms,heterogeneous effects,and implications for investment efficiency.Utilizing the implementation of government data open platforms as a quasi-natural experiment,this study aims to elucidate how public data transparency affects firms’investment decisions and resource allocation.Design/methodology/approach:This study employs a staggered Difference-in-Differences(DID)model as its principal methodological framework.This approach facilitates causal inference by examining the differential changes in corporate investment between firms influenced by the data openness policy and those that remain unaffected over time.Findings:The findings indicate that open government data substantially enhance corporate investment levels.A mechanistic analysis identifies three principal channels through which this effect is mediated:alleviation of overall financing constraints,reduction of financing costs,and expansion of the financing scale.A heterogeneity analysis suggests that the positive impact is more pronounced in state-owned enterprises,high-tech firms,and companies experiencing elevated levels of macroeconomic uncertainty.Moreover,the transparency of government data improves the responsiveness of corporate investment to emerging opportunities,thereby augmenting the overall efficiency of corporate investment.Research limitations:This study primarily examined the influence of government data transparency on corporate investment,while not accounting for the effects of macroeconomic variability,internal corporate governance frameworks,and industry-specific regulatory policies.Practical implications:Government open data platforms can effectively boost corporate investment and resource allocation.Policymakers should focus on improving the quality and accessibility of these data,especially in areas with high economic uncertainty,to support business investments.Firms,particularly high-tech and financially constrained firms,can use open data to ease capital limitations and find investment opportunities.Regulators should promote data transparency to enhance economic vitality through efficient corporate investments.Originality/value:This study enhances the existing literature by offering causal evidence of the impact of open government data on corporate investment,a subject that has been relatively underexplored empirically.By employing a quasi-natural experiment centered on the implementation of government data platforms,this study adopts a robust methodological approach to address endogeneity issues,thereby advancing methodological rigor in investigations of public data governance and corporate behavior.展开更多
With advancements in information technology and the increasing demand for data-driven governance,the openness of public data has become essential for global governance and social innovation.However,legal risks related...With advancements in information technology and the increasing demand for data-driven governance,the openness of public data has become essential for global governance and social innovation.However,legal risks related to privacy protection,data security,intellectual property,liability allocation,and legal adaptability pose significant challenges to data governance in China.This paper analyzes these risks and proposes three strategies:enhancing the legal framework through clear data classification and accountability mechanisms,establishing regulatory bodies to monitor data usage,and promoting public education on data privacy.These strategies aim to address gaps in legal discourse and guide effective data governance,contributing to the secure development of open data initiatives in China and beyond.展开更多
[目的/意义]评价Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0一书在开放关联数据赋能书目数据方面做出的学术贡献,帮助读者掌握开放关联数据的应用技能。[方法/过程]阐述开放关联数据应用指南的编撰目的,理解LODE-BD的...[目的/意义]评价Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0一书在开放关联数据赋能书目数据方面做出的学术贡献,帮助读者掌握开放关联数据的应用技能。[方法/过程]阐述开放关联数据应用指南的编撰目的,理解LODE-BD的实践建议,思考如何将书目数据表示为开放关联数据,帮助用户开放获取相关的书目资源,实现书目资源的互联互通。[结果/结论]该书是一本成熟的,关于如何选择合适编码策略来生成开放关联数据赋能的书目数据的操作指南,具有丰富的理论价值、方法指导与实践意义。展开更多
In the process of implementing data openness between banks and fin-tech companies,as the breadth and depth of cooperation between banks and enterprises continue to increase,there is a risk of“too much correlation to ...In the process of implementing data openness between banks and fin-tech companies,as the breadth and depth of cooperation between banks and enterprises continue to increase,there is a risk of“too much correlation to fail”and“too many links to fail”.There are problems with the implementation of financial data openness by regulatory agencies for banks and fin-tech enterprises,such as the ambiguity of regulatory responsibilities,the emphasis on financial regulatory goals,and the lag in regulatory methods.To address these issues,it is necessary to clarify the responsibilities of financial regulatory agencies,establish a collaborative mechanism for financial regulation,coordinate the types of risks in bank enterprise cooperation,achieve the technical implementation of financial regulatory measures and the design of regulatory systems,obtain regulatory data in real time,establish a hierarchical regulatory system for bank enterprise cooperation to improve the regulatory path,and ensure the rational and legal use of financial data in bank enterprise cooperation.展开更多
Open data strategies are being adopted in disaster-related data particularly because of the need to provide information on global targets and indicators for implementation of the Sendai Framework for Disaster Risk Red...Open data strategies are being adopted in disaster-related data particularly because of the need to provide information on global targets and indicators for implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030.In all phases of disaster risk management including forecasting,emergency response and post-disaster reconstruction,the need for interconnected multidisciplinary open data for collaborative reporting as well as study and analysis are apparent,in order to determine disaster impact data in timely and reportable manner.The extraordinary progress in computing and information technology in the past decade,such as broad local and wide-area network connectivity(e.g.Internet),highperformance computing,service and cloud computing,big data methods and mobile devices,provides the technical foundation for connecting open data to support disaster risk research.A new generation of disaster data infrastructure based on interconnected open data is evolving rapidly.There are two levels in the conceptual model of Linked Open Data for Global Disaster Risk Research(LODGD)Working Group of the Committee on Data for Science and Technology(CODATA),which is the Committee on Data of the International Council for Science(ICSU):data characterization and data connection.In data characterization,the knowledge about disaster taxonomy and data dependency on disaster events requires specific scientific study as it aims to understand and present the correlation between specific disaster events and scientific data through the integration of literature analysis and semantic knowledge discovery.Data connection concepts deal with technical methods to connect distributed data resources identified by data characterization of disaster type.In the science community,interconnected open data for disaster risk impact assessment are beginning to influence how disaster data are shared,and this will need to extend data coverage and provide better ways of utilizing data across domains where innovation and integration are now necessarily needed.展开更多
Purpose: The purpose of this exploratory study is to provide modern local governments with potential use cases for their open data, in order to help inform related future policies and decision-making. The concrete con...Purpose: The purpose of this exploratory study is to provide modern local governments with potential use cases for their open data, in order to help inform related future policies and decision-making. The concrete context was that of the Vaxjo municipality located in southeastern Sweden.Design/methodology/approach: The methodology was two-fold: 1) a survey of potential end users(n=151) from a local university;and, 2) analysis of survey results using a theoretical model regarding local strategies for implementing open government data.Findings: Most datasets predicted to be useful were on: sustainability and environment;preschool and school;municipality and politics. The use context given is primarily research and development, informing policies and decision making;but also education, informing personal choices, informing citizens and creating services based on open data. Not the least, the need for educating target user groups on data literacy emerged. A tentative pattern comprising a technical perspective on open data and a social perspective on open government was identified. Research limitations: In line with available funding, the nature of the study was exploratory and implemented as an anonymous web-based survey of employees and students at the local university. Further research involving(qualitative) surveys with all stakeholders would allow for creating a more complete picture of the matter. Practical implications: The study determines potential use cases and use contexts for open government data, in order to help inform related future policies and decision-making.Originality/value: Modern local governments, and especially in Sweden, are faced with a challenge of how to make their data open, how to learn about which types of data will be most relevant for their end users and what will be different societal purposes. The paper contributes to knowledge that modern local governments can resort to when it comes to attitudes of local citizens to open government data in the context of an open government data perspective.展开更多
Purpose:To develop a set of metrics and identify criteria for assessing the functionality of LOD KOS products while providing common guiding principles that can be used by LOD KOS producers and users to maximize the f...Purpose:To develop a set of metrics and identify criteria for assessing the functionality of LOD KOS products while providing common guiding principles that can be used by LOD KOS producers and users to maximize the functions and usages of LOD KOS products.Design/methodology/approach:Data collection and analysis were conducted at three time periods in 2015–16,2017 and 2019.The sample data used in the comprehensive data analysis comprises all datasets tagged as types of KOS in the Datahub and extracted through their respective SPARQL endpoints.A comparative study of the LOD KOS collected from terminology services Linked Open Vocabularies(LOV)and BioPortal was also performed.Findings:The study proposes a set of Functional,Impactful and Transformable(FIT)metrics for LOD KOS as value vocabularies.The FAIR principles,with additional recommendations,are presented for LOD KOS as open data.Research limitations:The metrics need to be further tested and aligned with the best practices and international standards of both open data and various types of KOS.Practical implications:Assessment performed with FAIR and FIT metrics support the creation and delivery of user-friendly,discoverable and interoperable LOD KOS datasets which can be used for innovative applications,act as a knowledge base,become a foundation of semantic analysis and entity extractions and enhance research in science and the humanities.Originality/value:Our research provides best practice guidelines for LOD KOS as value vocabularies.展开更多
Systematically analyze the composition of post-marketing adverse drug reaction data and the open mode in the EU, and summarize its characteristics. EU post-marketing ADR data is open to six categories of stakeholders:...Systematically analyze the composition of post-marketing adverse drug reaction data and the open mode in the EU, and summarize its characteristics. EU post-marketing ADR data is open to six categories of stakeholders: EMA, EC, medicines regulatory authorities in EEA member states, healthcare professionals and the public, Marketing Authorization Holders, academia, WHO and medicines regulatory authorities in third countries. The EU has implemented hierarchical opening for ADRs, with different levels containing different data and facing different stakeholders. Openness is divided into active and passive openness. In opening up data, the EU complies with relevant personal data protection laws to protect the privacy of individuals. The EU’s post-marketing adverse drug reaction data openness is characterized by a combination of data openness and privacy protection, active and passive openness, and a hierarchy of data openness. It is hoped that this can provide a reference for the opening up of post-marketing adverse drug reaction data in China.展开更多
Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,auton...Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.展开更多
Urban open data is the key to the construction of smart city. Through the research on evaluation of urban open data, the concept, types, characteristics and other basic problems of urban open data are systematically s...Urban open data is the key to the construction of smart city. Through the research on evaluation of urban open data, the concept, types, characteristics and other basic problems of urban open data are systematically summarized. From perspective of “quality”, “opening” and “acquisition”, a complete urban open data evaluation framework and index system is built. And the corresponding weights of evaluation indexes and score and overall rating methods are determined, so as to objectively evaluate the conditions of urban open data, and describe, monitor, guide and promote the construction and development of urban open data.展开更多
This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers ...This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers in land management and territorial planning,by first screening for areas with a higher debris flow susceptibility.Five environmental predisposing factors,namely,bedrock lithology,fracture network,quaternary deposits,slope inclination,and hydrographic network,were selected as independent parameters and their mutual interactions were described and quantified using the Rock Engineering System(RES)methodology.For each parameter,specific indexes were proposed,aiming to provide a final synthetic and representative index of debris flow susceptibility at the basin scale.The methodology was tested in four basins located in the Upper Susa Valley(NW Italian Alps)where debris flow events are the predominant natural hazard.The proposed matrix can represent a useful standardized tool,universally applicable,since it is independent of type and characteristic of the basin.展开更多
In recent years, transparency and accountability seem to find new impulse, with the development of ICT （information and communication technology） and the prospective of open data that invest the public system at a n...In recent years, transparency and accountability seem to find new impulse, with the development of ICT （information and communication technology） and the prospective of open data that invest the public system at a national and supranational level. Public institutions tend to make available to the public, more data and information concerning the administration, the manner of use of public goods and resources. At the same time, each institution is called upon to deal with the demand of transparency and participation by citizens who increasingly use Internet 2.0 and social media. After a reflection on how public administrations acted in the phase of Web 1.0 to practice transparency and accountability in terms of communication, this paper considers the elements of continuity and the new opportunities linked to the advent of Web 2.0 and open data. At the end of this analysis, the focus is on the strengths and weaknesses of this process, with a particular attention to the role of the public communication.展开更多
With the rapid development of lnternet technology, the volume of data has increased exponentially. As the large amounts of data are no longer easy to be managed and secured by the owners, big data security and privacy...With the rapid development of lnternet technology, the volume of data has increased exponentially. As the large amounts of data are no longer easy to be managed and secured by the owners, big data security and privacy has become a hot issue. One of the most popular research fields for solving the data security and data privacy is within the scope of big data governance and security, In this paper, we introduce the basic concepts of data governance and security. Then, all the state-of-the-art open source frameworks for data governance and security, including Apache Falcon, Apache Atlas, Apache Ranger, Apache Sentry and Kerberos, are detailed and discussed with descriptions of their implementation principles and possible applications.展开更多
This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, ...This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. first, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.展开更多
文摘Purpose: This paper aims to assess if the extent of openness and the coverage of data sets released by European governments have a significant impact on citizen trust in public institutions.Design/methodology/approach: Data for openness and coverage have been collected from the Open Data Inventory 2018(ODIN), by Open Data Watch;institutional trust is built up as a formative construct based on the European Social Survey(ESS), Round 9. The relations between the open government data features and trust have been tested on the basis of structural equation modelling(SEM).Findings: The paper reveals that as European governments improve data openness, disaggregation, and time coverage, people tend to trust them more. However, the size of the effect is still small and, comparatively, data coverage effect on citizens' confidence is more than twice than the impact of openness.Research limitations: This paper analyzes the causal effect of Open Government Data(OGD) features captured in a certain moment of time. In upcoming years, as OGD is implemented and a more consistent effect on people is expected, time series analysis will provide with a deeper insight.Practical implications: Public officers should continue working in the development of a technological framework that contributes to make OGD truly open. They should improve the added value of the increasing amount of open data currently available in order to boost internal and external innovations valuable both for public agencies and citizens.Originality/value: In a field of knowledge with little quantitative empirical evidence, this paper provides updated support for the positive effect of OGD strategies and it also points out areas of improvement in terms of the value that citizens can get from OGD coverage and openness.
文摘Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese A-share listed firms(2010–2022)and apply a staggered difference-in-differences model to investigate how data sharing impacts firm-level supply chain risk.Supply chain risk decreases significantly following PDOP establishment.Data sharing via PDOPs alleviates the“bullwhip effect”and promotes supply chain diversification,mitigating supply chain risks.In more complex firms,those with more advanced digital innovation,as well as non-state-owned firms,data sharing plays a greater role in alleviating supply chain risks.These findings increase awareness of the significance of data resources and offer practical guidance for enterprises’supply chain risk management.
基金supported by the following grants:National Natural Science Foundation of China(Grant No.72271147)Natural Science Foundation of Guangdong Province(Grant No.2022A1515010573)+1 种基金STU Scientific Research Initiation(Grant No.STF21005,STF21004)the Philosophy and Social Science Planning Project of Guangdong Province(Grant No.GD21CGL12,GD23XYJ76).
文摘Purpose:This research endeavors to investigate the impact of open government data on corporate investment,emphasizing the exploration of underlying mechanisms,heterogeneous effects,and implications for investment efficiency.Utilizing the implementation of government data open platforms as a quasi-natural experiment,this study aims to elucidate how public data transparency affects firms’investment decisions and resource allocation.Design/methodology/approach:This study employs a staggered Difference-in-Differences(DID)model as its principal methodological framework.This approach facilitates causal inference by examining the differential changes in corporate investment between firms influenced by the data openness policy and those that remain unaffected over time.Findings:The findings indicate that open government data substantially enhance corporate investment levels.A mechanistic analysis identifies three principal channels through which this effect is mediated:alleviation of overall financing constraints,reduction of financing costs,and expansion of the financing scale.A heterogeneity analysis suggests that the positive impact is more pronounced in state-owned enterprises,high-tech firms,and companies experiencing elevated levels of macroeconomic uncertainty.Moreover,the transparency of government data improves the responsiveness of corporate investment to emerging opportunities,thereby augmenting the overall efficiency of corporate investment.Research limitations:This study primarily examined the influence of government data transparency on corporate investment,while not accounting for the effects of macroeconomic variability,internal corporate governance frameworks,and industry-specific regulatory policies.Practical implications:Government open data platforms can effectively boost corporate investment and resource allocation.Policymakers should focus on improving the quality and accessibility of these data,especially in areas with high economic uncertainty,to support business investments.Firms,particularly high-tech and financially constrained firms,can use open data to ease capital limitations and find investment opportunities.Regulators should promote data transparency to enhance economic vitality through efficient corporate investments.Originality/value:This study enhances the existing literature by offering causal evidence of the impact of open government data on corporate investment,a subject that has been relatively underexplored empirically.By employing a quasi-natural experiment centered on the implementation of government data platforms,this study adopts a robust methodological approach to address endogeneity issues,thereby advancing methodological rigor in investigations of public data governance and corporate behavior.
基金Tianjin Education Commission Research Program in Humanities and Social Sciences(Project No.2022SK064)。
文摘With advancements in information technology and the increasing demand for data-driven governance,the openness of public data has become essential for global governance and social innovation.However,legal risks related to privacy protection,data security,intellectual property,liability allocation,and legal adaptability pose significant challenges to data governance in China.This paper analyzes these risks and proposes three strategies:enhancing the legal framework through clear data classification and accountability mechanisms,establishing regulatory bodies to monitor data usage,and promoting public education on data privacy.These strategies aim to address gaps in legal discourse and guide effective data governance,contributing to the secure development of open data initiatives in China and beyond.
文摘[目的/意义]评价Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0一书在开放关联数据赋能书目数据方面做出的学术贡献,帮助读者掌握开放关联数据的应用技能。[方法/过程]阐述开放关联数据应用指南的编撰目的,理解LODE-BD的实践建议,思考如何将书目数据表示为开放关联数据,帮助用户开放获取相关的书目资源,实现书目资源的互联互通。[结果/结论]该书是一本成熟的,关于如何选择合适编码策略来生成开放关联数据赋能的书目数据的操作指南,具有丰富的理论价值、方法指导与实践意义。
文摘In the process of implementing data openness between banks and fin-tech companies,as the breadth and depth of cooperation between banks and enterprises continue to increase,there is a risk of“too much correlation to fail”and“too many links to fail”.There are problems with the implementation of financial data openness by regulatory agencies for banks and fin-tech enterprises,such as the ambiguity of regulatory responsibilities,the emphasis on financial regulatory goals,and the lag in regulatory methods.To address these issues,it is necessary to clarify the responsibilities of financial regulatory agencies,establish a collaborative mechanism for financial regulation,coordinate the types of risks in bank enterprise cooperation,achieve the technical implementation of financial regulatory measures and the design of regulatory systems,obtain regulatory data in real time,establish a hierarchical regulatory system for bank enterprise cooperation to improve the regulatory path,and ensure the rational and legal use of financial data in bank enterprise cooperation.
基金This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences[grant number XDA19020201].
文摘Open data strategies are being adopted in disaster-related data particularly because of the need to provide information on global targets and indicators for implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030.In all phases of disaster risk management including forecasting,emergency response and post-disaster reconstruction,the need for interconnected multidisciplinary open data for collaborative reporting as well as study and analysis are apparent,in order to determine disaster impact data in timely and reportable manner.The extraordinary progress in computing and information technology in the past decade,such as broad local and wide-area network connectivity(e.g.Internet),highperformance computing,service and cloud computing,big data methods and mobile devices,provides the technical foundation for connecting open data to support disaster risk research.A new generation of disaster data infrastructure based on interconnected open data is evolving rapidly.There are two levels in the conceptual model of Linked Open Data for Global Disaster Risk Research(LODGD)Working Group of the Committee on Data for Science and Technology(CODATA),which is the Committee on Data of the International Council for Science(ICSU):data characterization and data connection.In data characterization,the knowledge about disaster taxonomy and data dependency on disaster events requires specific scientific study as it aims to understand and present the correlation between specific disaster events and scientific data through the integration of literature analysis and semantic knowledge discovery.Data connection concepts deal with technical methods to connect distributed data resources identified by data characterization of disaster type.In the science community,interconnected open data for disaster risk impact assessment are beginning to influence how disaster data are shared,and this will need to extend data coverage and provide better ways of utilizing data across domains where innovation and integration are now necessarily needed.
文摘Purpose: The purpose of this exploratory study is to provide modern local governments with potential use cases for their open data, in order to help inform related future policies and decision-making. The concrete context was that of the Vaxjo municipality located in southeastern Sweden.Design/methodology/approach: The methodology was two-fold: 1) a survey of potential end users(n=151) from a local university;and, 2) analysis of survey results using a theoretical model regarding local strategies for implementing open government data.Findings: Most datasets predicted to be useful were on: sustainability and environment;preschool and school;municipality and politics. The use context given is primarily research and development, informing policies and decision making;but also education, informing personal choices, informing citizens and creating services based on open data. Not the least, the need for educating target user groups on data literacy emerged. A tentative pattern comprising a technical perspective on open data and a social perspective on open government was identified. Research limitations: In line with available funding, the nature of the study was exploratory and implemented as an anonymous web-based survey of employees and students at the local university. Further research involving(qualitative) surveys with all stakeholders would allow for creating a more complete picture of the matter. Practical implications: The study determines potential use cases and use contexts for open government data, in order to help inform related future policies and decision-making.Originality/value: Modern local governments, and especially in Sweden, are faced with a challenge of how to make their data open, how to learn about which types of data will be most relevant for their end users and what will be different societal purposes. The paper contributes to knowledge that modern local governments can resort to when it comes to attitudes of local citizens to open government data in the context of an open government data perspective.
基金College of Communication and Information(CCI)Research and Creative Activity Fund,Kent State University
文摘Purpose:To develop a set of metrics and identify criteria for assessing the functionality of LOD KOS products while providing common guiding principles that can be used by LOD KOS producers and users to maximize the functions and usages of LOD KOS products.Design/methodology/approach:Data collection and analysis were conducted at three time periods in 2015–16,2017 and 2019.The sample data used in the comprehensive data analysis comprises all datasets tagged as types of KOS in the Datahub and extracted through their respective SPARQL endpoints.A comparative study of the LOD KOS collected from terminology services Linked Open Vocabularies(LOV)and BioPortal was also performed.Findings:The study proposes a set of Functional,Impactful and Transformable(FIT)metrics for LOD KOS as value vocabularies.The FAIR principles,with additional recommendations,are presented for LOD KOS as open data.Research limitations:The metrics need to be further tested and aligned with the best practices and international standards of both open data and various types of KOS.Practical implications:Assessment performed with FAIR and FIT metrics support the creation and delivery of user-friendly,discoverable and interoperable LOD KOS datasets which can be used for innovative applications,act as a knowledge base,become a foundation of semantic analysis and entity extractions and enhance research in science and the humanities.Originality/value:Our research provides best practice guidelines for LOD KOS as value vocabularies.
文摘Systematically analyze the composition of post-marketing adverse drug reaction data and the open mode in the EU, and summarize its characteristics. EU post-marketing ADR data is open to six categories of stakeholders: EMA, EC, medicines regulatory authorities in EEA member states, healthcare professionals and the public, Marketing Authorization Holders, academia, WHO and medicines regulatory authorities in third countries. The EU has implemented hierarchical opening for ADRs, with different levels containing different data and facing different stakeholders. Openness is divided into active and passive openness. In opening up data, the EU complies with relevant personal data protection laws to protect the privacy of individuals. The EU’s post-marketing adverse drug reaction data openness is characterized by a combination of data openness and privacy protection, active and passive openness, and a hierarchy of data openness. It is hoped that this can provide a reference for the opening up of post-marketing adverse drug reaction data in China.
文摘Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.
文摘Urban open data is the key to the construction of smart city. Through the research on evaluation of urban open data, the concept, types, characteristics and other basic problems of urban open data are systematically summarized. From perspective of “quality”, “opening” and “acquisition”, a complete urban open data evaluation framework and index system is built. And the corresponding weights of evaluation indexes and score and overall rating methods are determined, so as to objectively evaluate the conditions of urban open data, and describe, monitor, guide and promote the construction and development of urban open data.
文摘This research describes a quantitative,rapid,and low-cost methodology for debris flow susceptibility evaluation at the basin scale using open-access data and geodatabases.The proposed approach can aid decision makers in land management and territorial planning,by first screening for areas with a higher debris flow susceptibility.Five environmental predisposing factors,namely,bedrock lithology,fracture network,quaternary deposits,slope inclination,and hydrographic network,were selected as independent parameters and their mutual interactions were described and quantified using the Rock Engineering System(RES)methodology.For each parameter,specific indexes were proposed,aiming to provide a final synthetic and representative index of debris flow susceptibility at the basin scale.The methodology was tested in four basins located in the Upper Susa Valley(NW Italian Alps)where debris flow events are the predominant natural hazard.The proposed matrix can represent a useful standardized tool,universally applicable,since it is independent of type and characteristic of the basin.
文摘In recent years, transparency and accountability seem to find new impulse, with the development of ICT （information and communication technology） and the prospective of open data that invest the public system at a national and supranational level. Public institutions tend to make available to the public, more data and information concerning the administration, the manner of use of public goods and resources. At the same time, each institution is called upon to deal with the demand of transparency and participation by citizens who increasingly use Internet 2.0 and social media. After a reflection on how public administrations acted in the phase of Web 1.0 to practice transparency and accountability in terms of communication, this paper considers the elements of continuity and the new opportunities linked to the advent of Web 2.0 and open data. At the end of this analysis, the focus is on the strengths and weaknesses of this process, with a particular attention to the role of the public communication.
文摘With the rapid development of lnternet technology, the volume of data has increased exponentially. As the large amounts of data are no longer easy to be managed and secured by the owners, big data security and privacy has become a hot issue. One of the most popular research fields for solving the data security and data privacy is within the scope of big data governance and security, In this paper, we introduce the basic concepts of data governance and security. Then, all the state-of-the-art open source frameworks for data governance and security, including Apache Falcon, Apache Atlas, Apache Ranger, Apache Sentry and Kerberos, are detailed and discussed with descriptions of their implementation principles and possible applications.
基金This work was funded by National Natural Science Foundation of China(grant numbers. 51478189 and 51308220)%Natural Science Foundation of Guangdong(grant number 2014A03031326)%Fundamental Research Funds for the Central Universities(grant number 2015ZZ0022)
文摘This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. first, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.
