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    突發(fā)公共衛(wèi)生事件智慧城市數(shù)據(jù)利用框架構(gòu)建研究

    2022-07-02 06:22:46安小米許濟(jì)滄王麗麗
    信息資源管理學(xué)報(bào) 2022年3期
    關(guān)鍵詞:王麗麗香港城市大學(xué)信息資源管理

    安小米 許濟(jì)滄,2 王麗麗 黃 婕

    (1.中國(guó)人民大學(xué)信息資源管理學(xué)院,北京,100872; 2.香港城市大學(xué)數(shù)據(jù)科學(xué)學(xué)院,香港,999077)

    1 Introduction

    The smart city refers to the“city where improvements in quality of life,services,sustainability and resilience are accelerated by the effective integration of physical,digital and social systems and by the transformative use of data and technology” (IEC CDV 60050-831-01-27)[1].Facing the challenges posed by public health emergencies(PHE),smart cities are supposed to play an important role to improve the effects of data exchange and data-based decision-making.However,to fight against COVID-19,a considerable number of top-ranked smart cities in indexes,such as the Smart City Index[2],IMD Smart City Index 2019[3],E-Government Development Index(EGDI)[4],and Open Data Barometer[5],achieved unsatisfactory performance.Responding to PHE,smart city should not only focus on data collection and exchange but also on data use and decisionmaking.As said by WHO Director-General Tedros Adhanom Ghebreyesus at the Munich Security Conference on 15 February 2020, “We’re not just fighting an epidemic;we’re fighting an infodemic”.In fact,responding to PHE,smart city data use faces common problems worldwide that“Data are available”, “Data are useful”, “Data are easy to use”,and“Data are not abused”.However,there are rare studies on the topic of smart city data use responding to PHE.Existing studies highlighted regulatory requirements for data protection more significanthy than its effective use[6-9].Several researchers stressed the construction of Real-time Medical Emergency Response Systems,Public Health Surveillance Systems and the interoperability of Emergency Data Sharing Projects,whereas where the data are originated from and whether they are useful were rarely discussed[10-11].A comprehensive framework for smart city data use responding to PHE is urgently in demands.

    Accordingly,this study aims to propose a smart city data use framework responding to PHE.The core aspects consist of data openness to ensure that data are available,data quality to ensure that data are useful,data exchange to ensure that data are easy to use,as well as data value realization to ensure that data are not abused.To be more specific,this paper asked and answered the research questions that what issues and concerns should be considered in composing a smart city data use framework responding to PHE.

    The rest of the study is organized as follows.In Section 2,the related works are presented,and the core aspects and concerns in smart city data use framework responding to PHE are streamlined.In Section 3,the four-phase research design is described.In Section 4,the basic findings in the four-phase research are proposed.In Section 5,based on the findings,validated core issues and concerns of the framework are identified and discussed.In Section 6,the conclusions are drawn,including the research contributions,limitations and subsequent research directions.

    2 Related Work

    By reviewing smart city standards published and those under development,some standards have been found relevant to data use and service,e.g,ISO 37156[12],ISO/DIS 37110[13],ISO 37166[14],ISO/CD 37173[15],ISO/DIS 37170[16].However,none of existing standards created a comprehensive smart city data use framework responding to emergencies.It is the same with the situation in literature.Some researchers shed light on the“Data are available”aspect.Song et al[17].studied the influencing factors of people’s fear of missing out(FOMO)toward personal ICT use and its further impact on life satisfaction during the pandemic.Shiau et al[18]discussed the roles of IS/IT in providing services and support on information gathering,analysis,and management during major public emergencies and pandemic crises,such as the battle against the new coronavirus.Some researchers focused on the“Data are useful”aspect.Chen[19]analyzed the key problems and conditions for the implementation of data governance in enterprises.Data quality and its related standards and regulations were embedded in the framework of data governance in enterprises.A large number of enterprise data resources are scattered in various systems.Due to the lack of a complete data standard system,the data interaction and sharing between various systems is poor.Due to the lack of standardized management and appropriate control,the dispersion of data will lead to the same data being stored in different systems,which can not be effectively identified,and the reliability of data can not be guaranteed.Other researchers attached importance to the“Data are easy to use”aspect.In order to promote the progress of scientific data management and sharing work in China,Xing et al[20]promoted the emergent“Internet of Data”should be interoperable not only by people,but notably also by machines.They believed that general controlled vocabularies,ontologies,thesauruses with URIs and good data models contributed to the machine-understandable characteristics.To address the difficulties of information resource sharing,Yan and Zhu[21]proposed an E-government Interoperability Framework based on the top-level design.In their theory,the public service conceptual model,interoperability layered system and interoperability protocol are three key components of the E-government Interoperability Framework.Other researches took considerations of“Data are not abused”.Masaryk et al[22]proposed a scheme of outsourcing similarity search.They defined evaluation criteria for these systems with an emphasis on usability,privacy and efficiency in real applications.Chen et al[23]surveyed the current research progress of data ethics issues in internet-mediated research,summarized the connotation and characteristics of internet-mediated research,and combed the typical ethics issues and the governance mode of data ethics issues in internet-mediated research.The researches above only focused on specific concerns on smart city data use.There is a lack of a holistic framework covering the four aspects of data use in literature.There is also a lack of PHE scenario specific smart city data use frameworks.Thus,we first did literature review on the four aspects and the possible issues and concerns in the framework.Then we will compose a smart city data use framework for the PHE domain.

    2.1 Generic aspects of the smart city data use responding to PHE in the literature

    1)Data are available:Availability is a precondition of smart city data use responding to PHE[24].Zuiderwijk et al.[25]presented some best practices in the UK and Netherland as the typical cases of data use.In the revised version of the EU Directive on Public Sector Information Reuse in 2019,it was required that data should be easily accessed,queried,processed and associated with other data while not being restricted[26].This requirement complies with the Open Data Charter of the Group of Eight(G8)[27].The data charter proposes five open government principles.The first principle just refers to open data by default.It is also a core concern in the open data initiative delivered by the U.S.Pre-president’s Obama in 2009[28].Some scholars believed that the basic impacts on public value created by open data included releasing data for strengthened governance,releasing data for innovation,improving accessibility for people with special needs or disabilities,and supporting scientific results applied in policy and management decisions[29-30].

    2)Data are useful:To ensure that data are useful,data quality has been proposed as a precondition of smart city data use.In the 1990s,as guided by Wang and Strong[31],the data quality research group at MIT proposed the theory of Total Data Quality Management(TDQM).It was the first time that scholars considered the ideology of data quality.Data quality is defined as the degree to which a set of inherent characteristics of data satisfies the requirements(ISO 8000-2:2020)[32].Wang and Strong[31]split data quality into intrinsic data quality,contextual data quality,representational data quality,and accessibility data quality.The worldwide famous data quality assessment frameworks including A Methodology for Information Quality Assessment[33],Canadian Institute for Health data methodology[34],Data Quality Assessment Framework[35],Data Quality for the Quality Assessment of Financial Data[36],Comprehensive Methodology for Data Quality Management[37],as well as Common Open Data Assessment Framework[38].The common concerns of the aforementioned frameworks include accuracy,timeliness and completeness.In Section 2.2,more specific concerns in data quality assessment are discussed.

    3)Data are easy to use:To ensure that data are easy to use,interoperability is embedded as an essential issue in the smart city data use framework.Combined with linked data[27],interoperability refers to a mechanism to exchange and share data at the system level.The Institute of Electrical and Electronics Engineers(IEEE)defines interoperability as“the ability of two or more systems or components to exchange information and to use the information having been exchanged.”[39-40].Janssen et al.[41]split interoperability into three parts,including the syntactic interoperability that requires systems to comply with the identical data format enabling the efficient exchange of data via standards,semantic interoperability that ensures that information is interpreted in an identical manner,as well as pragmatic interoperability that refers to agreements with respect to data availability,information quality and conditions for use.Interoperability shapes the condition for two or more entities to achieve collaboration by exchanging information and communicating with each other.Interoperability requires the fulfillment of conditions from the technical level to the organizational level[39-40,42-43].In Section 2.2,other specific concerns relevant to data that are easy to use are discussed.

    4)Data are not abused:To ensure that data are not abused,numerous views with various dimensions from stakeholders’interests and concerns are highlighted,with the first priority of the people-centric perspective.This perspective stresses the user feedback and user experience.For instance,Zuiderwijk et al.[44]emphasized the linkage and visualization of data for a better user experience.An explorative case study was conducted to provide insights into the value proposition of open data marketplaces by Smithet et al.[45].De Donato et al.[46]considered public value as the value created via the collective deliberation by involving citizens,public agencies and stakeholders.This can be achieved by taking legal,privacy and collaborative steps to achieve fit-for-use.The four aspects of data use and their correspording literature sources are presented in Table 1.In Section 2.2,other data value realization concerns are discussed.

    Table 1 Four Aspects of Data Use in the Literature

    2.2 Specific concerns about smart city data use responding to PHE in the literature

    According to Gurstein[59], “open data”endows people with access to the basic infrastructure and the background knowledge and skills to use the data for specific ends.Thus,network infrastructure,acting as a material proposition for PHE data opening and exchange,refers to one of the explicit characteristics of the“Data are available”aspect.Bekiaris et al.[62]and Vanderheiden[63]discussed the inclusiveness of data open,placing an emphasis on the justice and welfare,especially on accessibility for the physically disabled.Gurstein[59],Bertot et al.[64],Napoli and Karaganis[65],and Halonen[27]mentioned the importance of opening a wide range of PHE data.The authors regard availability as a core concern in the framework for the effective use of PHE data.The availability exhibits a different meaning with“accessibility”.Newly digitized information is“accessible”to all on an equal basis.However,the availability of resources is directly proportional to the existing resources available to those with the access provided[66].The concept of coverage of data is generalized from the descriptions in the research by Zuiderwijk et al.[25].They proposed publishing data at a low granulation level,instead of at a high aggregation level.Zuiderwijk et al.[53]required governments to develop open data policies that focus on ensuring the availability,and to cooperatie with businesses and citizens to create alliances between governmental data providers and companies,which is expected to increase open data use.Thus,the authors define three sets of relationships to express the role that each interested party should take in the smart city data use framework responding to PHE,i.e.,individuall contribution of government in the data use,government-enterprise cooperation on data development and use,and government-citizen industry cooperation on data development and use.Lastly,all businesses with respect to data engineering and strategy should comply with the guidance from data laws,regulations and policies[42,48,67-68].

    Reviewing the globally notable data quality frameworks(e.g.,Total Data Quality Management[31],A Methodology for Information Quality Assessment[33],Canadian Institute for Health Data Methodology[34],Data Quality Assessment Framework[51],and Data Quality for the Quality Assessment of Financial Data[36]),completeness is the most mentioned term.It is expressed as the proportion of stored data against the potential of“100%complete” (ITU-T Technical Report D4.3)[73].Timeliness is mentioned in[27,31,69-72].Timeliness expresses the degree to which data represent reality from the required point in time.Accuracy refers to the degree to which data correctly indicate the“real world”object or event being described[73].Consistency is the absence of difference when comparing two or more representations of a particular thing against a definition[73].Traceability suggests that the origin of components can be determined(ISO/IEC/IEEE 15289)[74].They are also involved in the data quality aspect of the framework for the effective use of PHEdata[70,75-76].

    Interoperability refers to the ability of different information systems,devices and applications(systems)to access,exchange,integrate and cooperatively use data in a coordinated manner,in and across organizational,regional and national boundaries,as an attempt to provide portability of information.Health data exchange architectures,application interfaces,and standards enable data to be accessed and shared appropriately and securely[39-40,43].Scholl and Klischewski[77]identified nine major constraints affecting the interoperability.Some classifications and clustering of the mentioned concerns can be streamlined as follows.Technical interoperability refers to network connectivity,ensuring that systems are connected over wired or wireless networks.Systems are supposed to be connected at any time from any place,enabling real-time data exchange.Semantic interoperability ensures that information is interpreted consistently.It consists of creating ontologies and using semantic technologies to reason.Functional interoperability refers to agreements regarding data availability,information quality,and conditions for use(e.g.,juridical status),considering the setting in which data is collected,the purposes the data can(or cannot)be used for,and the legal status for each data source to ensure that its use does not violate laws or regulations[42].Lastly,linked data provides promises of improved accessibility,usability and value of open data[78-79].

    The publication of data generates the so-called public goodness introduced by Moore[80].Public goodness is the creation of value through collective deliberation by involving citizens,public agencies,and stakeholders[81-82].The concerns of the aspect,i.e.,data are exploited for goodness,are associated with such public value-oriented targets.Among all the concerns,data re-usability[27,50],user satisfaction[27],data utilization authority control measures[83],and data security control measures are considered representative[24].The overview of the smart city data use framework responding to PHE proposed according to the literature is listed in Table 2.

    Table 2 Specific Concerns about Smart City Data Use Responding to PHE According to the Literature

    The proposed framework contains 25 core concerns clustered in 4 core aspects.In the remaining sections of this study,the framework is modified and re-modified according to the questionnaires conducted throughout the nation and provinces.

    3 Research Design and Methods

    The methodology of this research is mainly based on methods of empirical studies,especially the survey.The smart city data use framework responding to public health emergencies is modified,re-modified,and validated by four-phase surveys,which answer three research questions in Section 1.The respective phase has specific purposes and connections,as presented in Figure 1.

    When determining the core issues and concerns at phase 1,the authors comply with four relevant principles.The first is the relevance to smart community infrastructure,i.e.,relevance to the smart city(conceptual design in plan,development,operation,maintenance,re-development and feedback).The second is the relevance to data exchange and sharing,indicating relevance to data exchange and sharing to develop and operate smart community infrastructure.The third is relevance to data-based and data-driven utilization,which means relevance to data-based and datadriven smart community infrastructure data use(e.g.,data value creation,data value maintenance,data value-adding and data as an enabler).The last is relevance to a PHE,which refers to relevance to the emergency protection,information disclosure,and urgent response to PHE.

    To know the stakeholders’opinions on the aforementioned issues and concerns and to select issues and concerns of the smart city data use framework responding to PHE in phase 1,the authors delivered questionnaires nationwide.The questionnaire was designed to collect binary choices from various data users(e.g.,government,companies and departments in public health domain).The authors applied stratified sampling method by considering stakeholders’professions.According to the actual distribution of smart city data use stakeholders,we took 261 government-sponsored institutions,24 data governance agencies,29 PHE response related enterprises,and 113 university professionals as samples.Questionnaires were delivered online and offline.In total,427 completed questionnaires were collected by March,2020.

    Phase 2 survey aims to examine the local acceptance ratios of smart city data use framework responding to public health emergencies and to prepare for the test-bed validation survey.The authors have sufficient reasons to select Shandong as the representative province in China in the aspect of data use[115]: (1)Shandong adheres to the unified construction of the whole province,and the provincial finance has invested over 80 million yuan for the construction of the provincial national health information platform.(2)Shandong Center for Disease Contro and Prevention(CDC)has now compiled and completed a resource directory and connected it with the service platform of the Shandong Provincial government.222 resource directories of information sharing have been established,and over 40 data sets have been developed,which can be released according to requirements.(3)Since the outbreak of COVID-19,all 543 hospitals under the system have already opened fever clinics.17,000 doctors have been connected to the system,and 210,000 patients have received treatments.The authors sampled randomly in different cities in Shandong in May,2020.We applied the modified questionnaire(with specific definition of each issue and concern)from phase 1 to an iterative province-wide data workers’survey in Shandong and received 118 feedbacks.

    At phase 3,to validate the proposed measurement model,the authors took Shandong Province as the test-bed object to examine whether the existing issues and concerns belonged to any of the four aspects.Meanwhile,the validity of the issues and concerns was examined by confirmatory factor analysis(CFA).The data were collected by randomly-sampled questionnaires in cities of Shandong Province.A total of 71 feedbacks were received(Jan,2022)to re-evaluate the data use of PHE in Shandong Province.

    At phase 4,to make this framework act as a real guideline to map,build,and monitor the smart city data use responding to PHE,the authors drafted it as a national standard of China.Directed by Standardization Administration of the People’s Republic of China,reported by National Urban Sustainable Development Standardization Technical Committee and executed by China and National Information Technology Standardization Network,this draft was listed in Approved National Standard Projects in April,2021.After five internal review meetings held by secretariat of National Information Technology Standardization Network,this standard item obtained 88.24%approval votes and entered the period of consultation.Till April,2022,this standard item has only obtained two tiny modification recommendations,which proves that it is well-recognized by experts in China.

    4 Research Findings

    4.1 Findings from the nationwide expertise’s questionnaire survey in China

    By the nationwide expert questionnaire survey in China,427 completed questionnaires were gained,including 147 from medical team members who aided Hubei against COVID-19.Besides,76 questionnaires were from faculties in Chinese health care centers,while 276 were from professionals regarding data governance(see Figure 2 and Figure 3).Our decisions on the processing of issues and concerns are summarized in Table 3,based on their opinions.

    Table 3 Comments adopted from 427 questionnaires

    4.2 Findings from the iterative province-wide questionnaire survey in Shandong Province

    The authors applied the modified questionnaire from the phase 1 to the phase 2 iterative province-wide data workers’questionnaire survey in Shandong and received 118 feedbacks.All the concerns in the smart city data use framework responding to PHE have a significant improvement in the adoption rate.The two rounds’adoption rate detailed comparison is in Figure 4,Figure 5,Figure 6 and Figure 7.Thus,we adopted the framework and the definitions for all issues and concerns.The whole framework is accepted as the measurement model to be examined in next phase.The re-modified smart city data use framework responding to PHE is shown in Figure 8,in which the demands,aspects,and core concerns are also defined.

    4.3 Findings from the test-bed questionnaire survey in Shandong Province

    The response and background of the test-bed questionnaire survey are shown in Table 4.In the dimension of“data are available(A)”,the scores of network infrastructure(A1),inclusiveness(A2),and data accessibility(A3)are 2.97,3.52 and 3.39(5-point scale,the same below),respectively,which are above average.About half of the respondents consider that the coverage of data(A4)has achieved the coverage of multiple topics,departments,locations and keywords,which is at a medium level.The contributions and cooperations among government,enterprises,and citizens(A5,A6,A7)are 3.59,3.32,and 2.45,respectively.This proves that the cooperations with citizens should be enhanced.Finally,the data laws,regulations and policies(A8)in Shandong province are not sufficient,with an average point of 2.62.

    Table 4 Response and background of the test-bed questionnaire survey

    In the dimension of“data are useful(B)”,the timeliness(B4)and accuracy(B5)need improvement.Their average scores are 2.94 and 2.55,respectively.The scores of completeness(B1),authenticity(B2),reliability(B3),consistency(B6),and trace-ability(B7)are all above 3.

    For“data are easy to use(C)”,all the respondents show that their units have taken interoperability(C1)measures to ensure data security to certain degrees.Among technical interoperability,semantic interoperability,and organizational interoperability,the organizational interoperability obtains the highest score in the Shandong test-bed survey which is 3.30 averagely.Linkability(C2)obtains a score of 3.24.Most respondents believe that Shandong has performance on providing optional description formats of associated data descriptions.The user experience(C3)scores 2.72.Some respondents do not believe the data presentation interface is beautiful and easy to operate in Shandong Province.

    In the dimension of“data are not abused(D)”,the overall data utilization impacts(D7)in Shandong Province is good,with a score of 3.76.The user satisfaction(D6)of data service users is high,achieving 3.97 points.These indicate that the goal of data utilization is fulfilled.Except for the number of best practices(D5)obtaining 2.92 points,other remaining indices,e.g.,data sharing measures(D1),data utilization authority control measures(D2),data security control measures(D3),and data monitoring and early warning measure(D4),are all above 3.7 points.

    4.4 Findings from CFA of the smart city data use framework responding to PHE

    To explain the key factors and examine the validity of the smart city data use framework responding to PHE,the authors applied the AMOSsoftware to run a CFA model based on the testbed survey.After several modifications,the final CFA model is accepted(See Figure 9).The number of distinct sample moments is 91.The number of distinct parameters to be estimated is 32.The minimum was achieved where X2=64.031,DF=59,and P=0.304.

    We find the key factors in the CFA model include inclusiveness(A2),data accessibility(A3),contribution of government in data utilization(A5),reliability(B3),accuracy(B5),technical interoperability(C1.1),semantic interoperability(C1.2),user experience(C3),data sharing measures(D1),data utilization authority control measures(D2),data security control measures(D3),data monitoring and early warning measures(D4),and data utilization impacts(D7).Their P values are extremely significant(See Table 5).The model fit results show good performance(See Table 6).Through statistic analysis,we scientifically dropped out group A and other factors.The modified CFA model fits perfectly as RFI-rho1=0.872,which is greater than 0.85(See Table 9).Under the settings of parameters in Figure 9,the RMSEA is 0.035(See Table 13).Other necessary CFA model results are shown in Table 7,Table 8,Table 10,Table 11,Table 12,Table 14,Table 15,and Table 16.

    Table 5 Factor estimation result of CFA model

    Table 8 RMRand GFI result of CFA model

    Table 9 Baseline comparisons of CFA model

    Table 10 Parsimony-adjusted measures of CFA model

    Table 11 NCP of CFA model

    Table 13 RMSEA of CFA model

    Table 14 AIC of CFA model

    Table 15 ECVI of CFA model

    Table 16 Hoelter of CFA model

    4.5 Findings from drafting the framework as a national standard

    In theory,this standard drafting work shows that this framework is nationally advanced and scientific.After five internal review meetings,the proposed framework is recognized by nationwide famous professionals.The approval ratio is 88.34%and the consultation results are nearly perfect.In practice,this framework is of practicability and operability.In the process of standard development,relying on smart city infrastructure development and operation enterprises in different cities such as Chengdu,Nanjing,Jinan,Hangzhou and Beijing,the framework is verified by public health emergency medical and disease control institutions in Yunnan,Wuhan and Shanghai.

    5 Discussions

    It is validated that the smart city data use framework responding to PHE can be used to analyze the improvement direction of the effective use of data in the development of smart cities.

    The findings show that there are three prominent problems in the utilization of data resources in Shandong Province.They are data quality assurance,data sharing and exchange,and the release of data value.Based on the problems found in the process of investigation,the present study puts forward the following suggestions.First,rules and regulations for the effective utilization of data resources should be formulated and modified.On the one hand,relevant laws and policies on data use,issue local rules and regulations on data security and special laws for data use should be further implemented.On the other hand,to optimize the data quality management system,one critical approach is to refine the quality management standards of data collection,release and maintenance of each unit,clarify the responsibility of data quality management,and assign the responsibility of data management to people.Second,interoperability standard collaboration mechanism across scenarios need to be established and improved.On the technical side,it is necessary to establish a unified system for basic data.

    6 Conclusions

    The present study rationalizes the urgent research demands on the effective use of data and proposes a comprehensive smart city data use framework responding to PHE.Moreover,a four-phaseempirical verification was conducted to verify and continuously improve the proposed framework.The contribution of the proposed framework is that it acts as a guideline and national standard in the smart city data use responding to PHE,which is conducive to guiding further improvement.The findings of the test-bed survey in Shandong demonstrate the validity of the proposed framework for data use in smart cities.The meaning of this framework is that it will act as China’s national standard by 6 May,2023,guiding the smart city data use responding to PHE in China.The proposed framework with four core aspects is the first of its kind to guide and evaluate the development of smart city data use responding to PHE.The four aspects are summarized as follows.

    6.1 Data are available

    “Data are not available”to most of the companies and citizens.To a large degree,the problem gets in the way of the effective use of data in the development of smart cities.Thus,the aspect of“data are available”is mentioned in the framework.It mainly focuses on three levels with nine concerns.For the first level,it points out the requirement of smart cities on the aspect that“data are available”especially on data preparation capabilities like network infrastructure,data openness,data availability,and coverage of data.Second,the inclusiveness of different data users is less cared about in the literature.However,all people with disabilities or poverty living in poor have the right to share the benefits brought from data.No one should be left behind.The use of data and the availability of data are equal to everyone.Thus,the framework adds this concern to the aspect of“data are available”.Thirdly,the aspect has concerns on a collaborative relationship among multiple stakeholders including government,business companies,and citizens.This can continually stimulate the development of data use for social good or commerce.In sum,the framework highlights the“data are available”aspect at the first place and regards it as a fundamental solution for the improvement of the effectiveness of data use.

    6.2 Data are useful

    In the prevention and control of COVID-19,fake news and unauthorized reports pervade everyday life.It causes panic among citizens and undermines the accuracy of decision-making in smart city systems.The proposed framework highlights the precondition that“data are useful”.In this aspect,concerns are around the data quality dimensions,aiming at improving the completeness,authenticity,reliability,timeliness,accuracy,consistency,and traceability of data.The authors summarize all the core concerns by reviewing famous data quality frameworks and give specific definitions and requirements according to the PHE scenarios and smart city standards.The concerns in“data are useful”in the development of smart cities and assuring the right decisions are made.

    6.3 Data are easy to use

    In the data research area,data sharing and exchange systems have always been a hot spot.A bridge is built between the data providers and data users.Different from the simple network infrastructure mentioned in the first aspect, “data easy to use”stresses the importance of interoperability standards for exchange at the technical level,semantic level,and functional level.Besides,linked data protocols are recognized in the framework.Moreover,the authors also pay more attention to non-technical concerns like the feelings and experiences of the users.Accordingly,a closed feedback system is built to help improve the ease of use of data.

    6.4 Data are not abused

    In the proposed framework,the authors put data that are not abused as the last but not least aspect to be considered.To be specific,the concerns from three stakeholders’perspectives are involved.From the government perspective,monitoring responsibility should be taken for data sharing,opening,authority control,security,and early warning measures to assure data are not abused.From the business perspective,sufficient best practices should be conducted to facilitate large-scale applications in the market,thereby benefiting more citizens in the data value realization sense.From the citizen perspective,social good brought by data use should be scored by users’satisfaction,and the utilization impacts it aims to achieve.The three perspectives from various dimensions aim to achieve public,private and people partnerships in the effective use of data.Besides,the framework shows abilities in guiding and evaluating the development of data use in smart cities.

    By analyzing the results of questionnaires conducted in Shandong Province,the authors identify several problems,such as inconsistency in data format on the“data that are useful”aspect,insufficient user experience on the“data are easy to use”aspect,and inadequate best practices in surveyed units on the“data are not abused”aspect.The authors highlight that the improvement directions include strengthening standard systems for data quality management and interoperability,as well as building a unified system for basic data.

    The limitation of this study is that this framework raises the requirements with respect to the effective use of data but no specific road maps to satisfy these requirements.In subsequent studies,the authors will continue to apply this framework in more regions nationwide and worldwide to enhance the feasibility of this framework.

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