政府信息公开对地理信息资源开发利用的影响——基于NYC open data计划的案例研究

公开政府数据已经成为政府信息公开的新趋势,而随着各国政府数据公开计划的推进与实施,相关信息资源的深度利用越发受到关注,由此所催生的相关产业的发展前景也被普遍看好。本文以纽约市政府数据公开计划为例,利用案例研究的方法,探究政府信息公开对于地理信息资源开发利用的影响。研究结果表明:随着政府所掌握的地理信息资源的公开,地理信息资源产品将向着功能多样、有效程度高的方向发展,用户将获得更好的使用体验,进而推动地理信息资源产业的发展;同时,政府信息公开所带来的地理信息资源开发利用的深化,将加快智慧城市的建设步伐。

FAIR + FIT: Guiding Principles and Functional Metrics for Linked Open Data(LOD) KOS Products

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.

“开放数据”(Open Data)的基本逻辑——以NYC Open Data为样本

为了加强政府的责任和响应能力,提高公共机构的运作水平和相互之间的协同效率,回应公众对公共数据的需求,创造新的经济机会,一些政府以立法的形式,正在运用最新的大数据技术建设开放数据系统。系统所体现的知识开放性的科学规范尊重,建设者缜密的计划,公开而严格的技术标准,以及高度的开放性和互动性,给我们提供了极佳的启示。

Open Data Services和Socket的应用研究——数据库服务器与应用程序间网络通信接口模块的设计

在数据库应用系统开发时常遇到的问题是如何合理的设计外部进程访问数据库的时间控制方案,在满足设计要求的响应时间的前提下,把握好系统与网络负载同系统事务响应处理速度之间的平衡关系。但在实际开发过程中对于某些类型数据的响应处理缺乏有效率的解决途径。此类数据采用通常的处理方式往往不能较好地得到解决。基于此,开发了1种由ODSAPI和Socket编程的数据库ESP扩展方法,由应用系统主动查询方式变为数据库系统主动通知或推送的方式,从而提供了1种高效率的解决方案。

开放关联数据赋能书目数据的实践指南--评Linked Open Data Enabled Bibliographical Data(LODE-BD)3.0

[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。

Research on the Evaluation of Urban Open Data

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.

LSTM-based lane change prediction using Waymo open motion dataset: The role of vehicle operating space

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.

Bolzano Traffic: An Example of Open ITS Deployment for Advanced Traveller Information Services

This paper aims to present the experience gathered in the Italian alpine city of Bolzano within the project“Bolzano Traffic”whose goal is the introduction of an experimental open ITS platform for local service providers,fostering the diffusion of advanced traveller information services and the future deployment of cooperative mobility systems in the region.Several end-users applications targeted to the needs of different user groups have been developed in collaboration with local companies and research centers;a partnership with the EU Co-Cities project has been activated as well.The implemented services rely on real-time travel and traffic information collected by urban traffic monitoring systems or published by local stakeholders(e.g.public transportation operators).An active involvement of end-users,who have recently started testing these demo applications for free,is actually on-going.

How to assess the success of the open data ecosystem?

Open data are currently a hot topic and are associated with realising ambitions such as a more transparent and efficient government,solving societal problems,and increasing economic value.To describe and monitor the state of open data in countries and organisations,several open data assessment frameworks were developed.Despite high scores in these assessment frameworks,the actual(re)use of open government data(OGD)fails to live up to its expectations.Our review of existing open data assessment frameworks reveals that these only cover parts of the open data ecosystem.We have developed a framework,which assesses open data supply,open data governance,and open data user characteristics holistically.This holistic open data framework assesses the maturity of the open data ecosystem and proves to be a useful tool to indicate which aspects of the open data ecosystem are successful and which aspects require attention.Our initial assessment in the Netherlands indicates that the traditional geographical data perform significantly better than non-geographical data,such as healthcare data.Therefore,open geographical data policies in the Netherlands may provide useful cues for other OGD strategies.

HiLog:OpenHarmony的高性能日志系统

日志是计算机系统中记录事件状态信息的的重要载体,日志系统负责计算机系统的日志生成、收集和输出.OpenHarmony是新兴的、面向全设备、全场景的开源操作系统.在所述工作之前,包括日志系统在内OpenHarmony有许多关键子系统尚未构建,而OpenHarmony的开源特性使第三方开发者可以为其贡献核心代码.为了解决Open Harmony日志系统缺乏的问题,主要开展如下工作:(1)分析当今主流日志系统的技术架构和优缺点;(2)基于OpenHarmony操作系统的异构设备互联特性设计HiLog日志系统模型规范;(3)设计并实现第1个面向OpenHarmony的日志系统HiLog,并贡献到OpenHarmony主线;(4)对HiLog日志系统的关键指标进行测试和对比试验.实验数据表明,在基础性能方面,HiLog和Log的日志写入阶段吞吐量分别为1500 KB/s和700 KB/s,相比Android日志系统吞吐量提升114%;在日志持久化方面,HiLog可以3.5%的压缩率进行持久化,并且丢包率小于6‰,远低于Log.此外,HiLog还具备数据安全、流量控制等新型实用能力.

OpenAIRE关联开放数据研究

文章对OpenAIRE关联开放数据从数据模型、词汇表的选择和创建、数据映射、LOD的批量生成、数据的链接、对外开放查询进行了详细的分析,为我国分散的机构知识库、学术平台、期刊平台等数据的语义化整合、数据互操作和开放获取提供了一种新的方法与思路。但是目前OpenAIRE关联开放数据的实现仍然存在许多问题和挑战:URIs不够稳定;OpenAIRE LOD的数据生成过程是人工实施的;主要是通过URI访问,数据链接的质量有待提高。建议在OpenAIRE关联开放数据的实现过程中进一步增强数据稳定性、实施数据自动转换方法、开展多路径查询方式、加强数据质量控制与评估。

Gap analysis on open data interconnectivity for disaster risk research

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.

Government Data Openness and Coverage. How do They Affect Trust in European Countries?

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.

Research Data Management Implementation at Peking University Library:Foster and Promote Open Science and Open Data

Research Data Management(RDM)has become increasingly important for more and more academic institutions.Using the Peking University Open Research Data Repository(PKU-ORDR)project as an example,this paper will review a library-based university-wide open research data repository project and related RDM services implementation process including project kickoff,needs assessment,partnerships establishment,software investigation and selection,software customization,as well as data curation services and training.Through the review,some issues revealed during the stages of the implementation process are also discussed and addressed in the paper such as awareness of research data,demands from data providers and users,data policies and requirements from home institution,requirements from funding agencies and publishers,the collaboration between administrative units and libraries,and concerns from data providers and users.The significance of the study is that the paper shows an example of creating an Open Data repository and RDM services for other Chinese academic libraries planning to implement their RDM services for their home institutions.The authors of the paper have also observed since the PKU-ORDR and RDM services implemented in 2015,the Peking University Library(PKUL)has helped numerous researchers to support the entire research life cycle and enhanced Open Science(OS)practices on campus,as well as impacted the national OS movement in China through various national events and activities hosted by the PKUL.

Paving the Way to Open Data

It is easy to argue that open data are critical to enabling faster and more effective research discovery.In this article,we describe the approach we have taken at Wiley to support open data and to start enabling more data to be FAIR data(Findable,Accessible,Interoperable and Reusable)with the implementation of four data policies:“Encourages”,“Expects”,“Mandates”and“Mandates and Peer Reviews Data”.We describe the rationale for these policies and levels of adoption so far.In the coming months we plan to measure and monitor the implementation of these policies via the publication of data availability statements and data citations.With this information,we’ll be able to celebrate adoption of data-sharing practices by the research communities we work with and serve,and we hope to showcase researchers from those communities leading in open research.

Why Open Government Data? The Case of a Swedish Municipality

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.

FAIR Versus Open Data: A Comparison of Objectives and Principles

This article assesses the difference between the concepts of ‘open data’ and ‘FAIR data’ in data management. FAIR data is understood as data that complies with the FAIR Guidelines—data that is Findable, Accessible, Interoperable and Reusable—while open data was born out of awareness of the need to democratise data by improving its accessibility, based on the idea that data should not have limitations that prevent people from using it. This study compared FAIR data with open data by analysing relevant documents using a coding analysis with conceptual labels based on Kingdon’s theory of agenda setting. The study found that in relation to FAIR data the problem stream focuses on the complexity of data collected for research, while open data primarily emphasises giving the public access to non-confidential data. In the policy stream, the two concepts share common standpoints in terms of making data available and reusable, although different approaches are adopted in practice to accomplish these goals. In the politics stream, stakeholders with different objectives support FAIR data and from those who support open data.

Exposing vocabularies for soil as Linked Open Data

Standards to describe soil properties are well established,with many ISO specifications and a few international thesauri available for specific applications.Besides,in recent years,the European directive on "Infrastructure for Spatial Information in the European Community(INSPIRE)"has brought together most of the existing standards into a well defined model.However,the adoption of these standards so far has not reached the level of semantic interoperability,defined in the paper,which would facilitate the building of data services that reuse and combine data from different sources.This paper reviews standards for describing soil data and reports on the work done within the EC funded agINFRA project to apply Linked Data technologies to existing standards and data in order to improve the interoperability of soil datasets.The main result of this work is twofold.First,an RDF vocabulary for soil concepts based on the UML INSPIRE model was published.Second,a KOS(Knowledge Organization System)for soil data was published and mapped to existing relevant KOS,based on the analysis of the SISI database of the CREA of Italy.This work also has a methodological value,in that it proposes and applies a methodology to standardize metadata used in local scientific databases,a very common situation in the scientific domain.Finally,this work aims at contributing towards a wider adoption of the INSPIRE directive,by providing an RDF version of it.

Research on the Opening of Adverse Drug Reaction Data in the EU

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.