This report is based on information flow, information marketing, and information value theory, and follows the concept of sustainable data openness. It tracks and evaluates the data openness of important cities around the world from the entire process of data flow, and constructs an evaluation framework for data openness around the United Nations' sustainable development goals. It conducts a global evaluation of data openness in important cities and proposes countermeasures and suggestions. Efforts should be made to promote the use of limited resources by the public sector to continuously open up high-quality data, establish and improve long-term mechanisms to promote the application of open data, and stimulate the continuous release of the value of data products. Help global governments gradually form a sustainable and benign open data ecosystem, and assist in advancing global e-government to a higher stage.

Since its release in 2019, the first edition of the report has received widespread attention worldwide and has become a barometer of global urban data openness. In 2021, the project team revised and improved the report based on the first two versions, presenting two important changes.

One is the evaluation object. Two cities, Surat and Brisbane, have been deleted, and two new cities, Qingdao and Hangzhou, have been added. The open data of the Indian city of Surat has been migrated to a national level open platform, and the original platform has been shut down; Sydney has already participated in the evaluation in Australia, and Brisbane's performance in the first two years was mediocre, lacking regional representativeness and reference value, so it was removed from the evaluation object. The degree of data openness in Qingdao has rapidly increased in the past two years, while Hangzhou, as a pioneer in China's digital transformation, has gradually gained international recognition. Therefore, these two cities are included in the evaluation to observe the global impact of their data openness.

The second is the evaluation indicators. The world situation is constantly changing, especially in the post pandemic era. Data openness work in various countries continues to advance and play an important role, and the estimated indicators of data openness in important cities around the world should also be adjusted. In 2021, indicators such as "(Yes/No) Open COVID-19 data", "(Yes/No) Visualize data", "Types of visual presentation", "(Yes/No) Provide common development tools", "(Yes/No) Pilot applications (typical applications)", etc. were added; Deleted indicators such as "number of datasets for a single topic", "API compatibility ratio", "application achievements", "historical records", and "data interpretability"; Change the "user engagement layer" to the "user usage layer" and add a "user convenience" observation dimension below it; Correspondingly change the weight of some indicators. The methods and indicator system for evaluating the data openness of major global cities in 2021 are detailed in Appendix 2 of this book.

Based on indicators such as the global impact, regional and cultural representation of cities, the report selects the cities with the highest development potential and scale, as well as data open platforms, from the "World City Roster 2020" compiled by the Globalization and World Class Cities Research Group. Meanwhile, select representative cities from the BRICS countries that have established data open platforms.

The domain names of various city data open platforms were obtained through various methods such as Google search, searching on national data open platforms in various countries, and searching on the website of the Open Knowledge Foundation www.dataportals.org. The evaluation objects were finally determined, as shown in Table 1.

表1 评估对象
序号	城市名	平台名称	平台网址
1	多伦多（加拿大）	City of Toronto Open Data Portal （多伦多市数据开放门户）	https：//open.toronto.ca/
2	洛杉矶（美国）	LOS ANGELES Open Data （洛杉矶数据开放门户）	https：//data.lacity.org/
3	纽约（美国）	NYC Open Data （纽约数据开放）	https：//opendata.cityofnewyork.us/
4	芝加哥（美国）	CHICAGO Data Portal （芝加哥市数据门户）	https：//data.cityofchicago.org/
5	墨西哥城（墨西哥）	Datos CDMX （墨西哥城数据门户）	https：//datos.cdmx.gob.mx/
6	悉尼（澳大利亚）	City of Sydney Data hub-Open Data （悉尼市数据中心—数据开放）	https：//data.cityofsydney.nsw.gov.au/pages/open-data
7	奥克兰（新西兰）	Auckland Council Open Data （奥克兰议会数据开放）	https：//data-aucklandcouncil.opendata.arcgis.com/
8	开普顿（南非）	City of Cape Town Open Data Portal （开普顿市数据开放门户）	https ： //odp.capetown.gov.za/
9	布宜诺斯艾利斯（阿根廷）	Buenos Aires Data （布宜诺斯艾利斯数据）	https：//data.buenosaires.gob.ar/
10	里约热内卢（巴西）	data.rio （里约数据）	http：//www.data.rio/
11	都柏林（爱尔兰）	Dublinked Open Data Store （都柏林数据开放库）	https：//data.smartdublin.ie/
12	法兰克福（德国）	Offene Daten Frankfurt （数据开放法兰克福）	https：//offenedaten.frankfurt.de/home/
13	莫斯科（俄罗斯）	Портал открытых ДAнных Правительства Москвы （莫斯科政府公共数据门户）	https：//data.mos.ru/
14	巴黎（法国）	Paris Data （数据开放巴黎）	https：//opendata.paris.fr/pages/home/
15	里昂（法国）	Metropolitan Data of the Grand Lyon （大里昂的大都会数据）	https：//data.grandlyon.com/accueil
16	伦敦（英国）	LONDON DATASTORE （伦敦数据库）	https：//data.london.gov.uk/
17	迪拜（阿联酋）	Dubai Pulse192181 （迪拜脉冲）	https：//www.dubaipulse.gov.ae/
18	首尔（韩国）	서울열린데이터광장 （首尔数据开放广场）	http：//data.seoul.go.kr/
19	东京（日本）	东京都オープンデータカタログサイト（东京都数据开放目录网站）	https：//portal.data.metro.tokyo.lg.jp/
20	新加坡（新加坡）	Data.gov.sg （新加坡数据）	https：//data.gov.sg/
21	雅加达（印度尼西亚）	JAKARTA Open Data （雅加达数据开放）	http：//data.jakarta.go.id/
22	北京（中国）	北京市政务数据资源网	https：//data.beijing.gov.cn/
23	广州（中国）	广州市政府数据统一开放平台	http：//data.gz.gov.cn/
24	贵阳（中国）	贵阳市政府数据开放平台	https：//data.guiyang.gov.cn/city/index.htm
25	杭州（中国）	杭州数据开放平台	https：//data.hz.zjzwfw.gov.cn/
26	青岛（中国）	青岛公共数据开放网	http：//data.qingdao.gov.cn/
27	上海（中国）	上海市公共数据开放平台	https：//data.sh.gov.cn/
28	深圳（中国）	深圳市政府数据开放平台	https：//opendata.sz.gov.cn/
29	香港（中国）	资料一线通	https：//data.gov.hk/sc/
30	台北（中国）	台北市资料大平台	https：//data.taipei/#/
注：按洲、国家、城市的音序排序。

The methods for obtaining basic security layer data include: firstly, searching for data from data open platforms in various cities; The second is to obtain data from websites such as the government, city hall, and parliament of various cities; The third is to use Google's advanced search to obtain data; The fourth is to obtain data from academic papers both domestically and internationally. The deadline for obtaining data is May 15th, 2021.

The methods for obtaining open quality layer and user usage layer data include: firstly, designing programs to capture data on urban data open platforms; The second is to search for relevant data on the urban data open platform. The time period for obtaining data is from April 19th to May 17th, 2021.

The methods for obtaining value release layer data include: firstly, searching for data on data open platforms in various cities; The second is to use Google's advanced search function to obtain data; The third is to obtain data from authoritative reports. The deadline for obtaining data is May 15th, 2021. The deadline for obtaining academic papers, books, and patent data is May 30, 2021.

In addition, the report mines and statistically analyzes the number of datasets based on the actual situation of the open platform data organization model. If the data of a certain indicator in the city cannot be queried from the above methods, then mark the value of this indicator as zero.

The weight of the indicators is determined by scoring from approximately 40 experts in the field of open data from around the world.

Calculation of indicators: Using extreme value processing method, the actual data obtained and the processed graded scoring data are standardized together, then weighted and calculated, and finally the comprehensive index is converted into a percentage system for display.

The calculation formula for the comprehensive index of data openness in each city is: ∑ (standardized score of basic guarantee layer x weight)+∑ (standardized score of open quality layer x weight)+∑ (standardized score of user use layer x weight)+∑ (standardized score of value release layer x weight)

The construction of the indicator system is based on the principles of data openness, internationally and domestically renowned data openness evaluation report indicators, expert opinions, and the current situation and trends of international data openness.

The 2021 Global Important City Data Open Evaluation Index System includes 4 evaluation dimensions and 77 evaluation indicators. The four evaluation dimensions include: basic assurance layer, open quality layer, user usage layer, and value release layer. The basic security layer mainly examines the fundamental security of data openness, consisting of policy/legal frameworks and organizational work; The open quality layer is mainly used to evaluate the quality of data on open platforms, involving openness depth, openness breadth, data activity, and metadata standardization; The user layer mainly evaluates the input and output of the platform, involving data usage, platform interaction, and user convenience; The value release layer mainly evaluates the degree of value release of open data, involving economic value, political value, and social value.

The overall ranking of cities and the rankings and scores of each dimension are shown in Table 2.

All 9 cities shortlisted by China are in the top 20. Among them, 8 cities ranked in the top 15, 6 cities entered the top 10, and 2 cities entered the top 5. Among the 30 cities where "experts gather", Chinese cities have performed particularly well and have reached the leading level of global data openness.

表2 城市排名
城市名	总排名	综合指数	综合指数（百分制）	基础保障层指数		开放质量层指数		用户使用层指数		价值释放层指数
城市名	总排名	综合指数	综合指数（百分制）	排名	指数	排名	指数	排名	指数	排名	指数
上海（中国）	1	0.5774	100.0000	3	0.2128	8	0.1175	1	0.1833	4	0.0638
纽约（美国）	2	0.5741	99.4285	1	0.2470	4	0.1264	16	0.0821	1	0.1186
芝加哥（美国）	3	0.5596	96.9172	5	0.1971	12	0.1091	5	0.1633	3	0.0901
首尔（韩国）	4	0.5093	88.2057	2	0.2420	9	0.1163	12	0.1000	6	0.0510
贵阳（中国）	5	0.4855	84.0838	11	0.1804	1	0.1396	4	0.1640	24	0.0015
洛杉矶（美国）	6	0.4530	78.4551	12	0.1795	7	0.1221	7	0.1416	13	0.0098
广州（中国）	7	0.4421	76.5674	26	0.1018	3	0.1281	6	0.1616	7	0.0506
深圳（中国）	8	0.4420	76.5501	21	0.1321	5	0.1257	2	0.1821	23	0.0021
北京（中国）	9	0.4278	74.0908	9	0.1879	21	0.0692	3	0.1653	16	0.0054
青岛（中国）	10	0.3982	68.9643	14	0.1726	15	0.1012	9	0.1236	25	0.0008
伦敦（英国）	11	0.3955	68.4967	23	0.1180	6	0.1246	21	0.0400	2	0.1129
香港（中国）	12	0.3782	65.5005	15	0.1715	26	0.0543	12	0.1000	5	0.0524
迪拜（阿联酋）	13	0.3559	61.6384	10	0.1877	24	0.0644	11	0.1033	28	0.0005
东京（日本）	14	0.3543	61.3613	7	0.1926	2	0.1337	25	0.0200	14	0.0080
台北（中国）	15	0.3478	60.2355	6	0.1960	16	0.0955	20	0.0417	10	0.0146
巴黎（法国）	15	0.3478	60.2355	19	0.1339	17	0.0912	10	0.1072	9	0.0155
新加坡（新加坡）	17	0.3412	59.0925	16	0.1587	22	0.0671	14	0.0900	8	0.0254
多伦多（加拿大）	18	0.3330	57.6723	4	0.2000	13	0.1054	25	0.0200	15	0.0076
雅加达（印度尼西亚）	19	0.3171	54.9186	8	0.1891	18	0.0872	21	0.0400	25	0.0008
杭州（中国）	20	0.3087	53.4638	25	0.1033	20	0.0697	8	0.1328	19	0.0029
莫斯科（俄罗斯）	21	0.2785	48.2335	18	0.1378	25	0.0636	18	0.0745	21	0.0026
悉尼（澳大利亚）	22	0.2737	47.4021	19	0.1339	27	0.0448	14	0.0900	17	0.0050
里约热内卢（巴西）	23	0.2570	44.5099	22	0.1250	23	0.0661	19	0.0633	21	0.0026
都柏林（爱尔兰）	24	0.2550	44.1635	29	0.0655	10	0.1123	17	0.0767	28	0.0005
开普顿（南非）	25	0.2412	41.7735	13	0.1775	30	0.0106	21	0.0400	11	0.0131
墨西哥城（墨西哥）	26	0.2361	40.8902	17	0.1445	19	0.0789	28	0.0000	12	0.0127
布宜诺斯艾利斯（阿根廷）	27	0.2187	37.8767	24	0.1077	11	0.1102	28	0.0000	25	0.0008
里昂（法国）	28	0.2015	34.8978	27	0.0823	14	0.1042	27	0.0100	17	0.0050
奥克兰（新西兰）	29	0.1445	25.0260	28	0.0693	28	0.0425	24	0.0300	20	0.0027
法兰克福（德国）	30	0.0908	15.7257	30	0.0508	29	0.0399	28	0.0000	30	0.0001

The three selected American cities have remained in the top 10 for three consecutive years, and New York and Chicago have been in the top 5 for three consecutive years. At the moment when the global data opening is "benchmarking the United States", "keeping pace with the United States" and "catching up with the United States", American cities can still "stand on Mount Taishan" and steadily become the world leader, which shows that the United States is still moving forward at a fast pace in data opening.

（3） The level of data openness in North American and Asian cities is generally higher than in other continents

Among the top 20 cities, 14 are from Asia and 4 are from North America. Or, apart from London, Paris, and Moscow, the top 20 cities belong to Asia and North America, while the bottom 10 cities are mostly distributed in other continents. In terms of ranking and quantity, the level of data openness in North American and Asian cities is significantly higher than in other continents.

Seoul ranked 1st, 3rd, and 4th in the evaluation from 2019 to 2021, although its ranking slightly declined, overall it is at a world-class level. Singapore ranked 12th, 12th, and 16th respectively from 2019 to 2021, consistently at the average level of major cities worldwide. The evaluation results of the two cities differ significantly from the public impression. Firstly, Singapore's global leadership in smart city construction does not necessarily mean that it is in a leading position in all aspects related to data; Secondly, it is necessary to gain a deeper understanding of Seoul's achievements in data openness and re-examine the level of data openness in this "rigorous" and "conservative" city.

In 2020, Shanghai became the world's number one with a composite index (percentage system) that was nearly 30 points higher than the second place New York. In 2021, despite changes in the evaluation index system and weights, Shanghai still emerged with a slight advantage and achieved a consecutive victory. The data openness work in Shanghai has been steady and withstood the test, and the achievement of first place is due to its strength.

The average compliance rate of key indicators in the basic guarantee layer was 45.26%, a decrease of 0.26 percentage points from the previous year, and the overall performance declined (see Table 3).

表3 基础保障层关键指标及达标城市占比
指标名称	达标城市的数量或占比
制定了专门的数据开放法规或政策	19个
用法律条文来规范开放数据行为	7个
开放数据平台列有隐私政策的条款	24个
有完整的隐私政策	9个
制定了个人隐私保护法规或相关政策	16个
制定了个人隐私保护法	8个
制定了数据安全法规或政策	10个
通过开放许可协议规范了利益相关方的权责	30个
有完整的开放许可协议	24个
规定开放数据所有权	14个
将开放数据所有权归属于数据开放主体	12个
规定开放数据属于全社会	2个
免费开放数据	76.67%
对部分数据收费	5个
为数据开放制订专门计划	46.67%
2011～2014年颁布了数据开放计划	6个
直接负责数据开放的部门级别是“市政厅（市政府办公室或市长办公室）或市议会”	2个
直接负责数据开放的部门是“一级局（厅或部或专项职能办公室或开放数据小组或开放数据委员会）”	80.00%
上一年的政府报告（施政报告或施政纲领）提到了数据开放工作	26.67%
上一年的市财政明确做出了数据开放的具体预算	20.00%
曾举办过开放数据竞赛	66.67%

Table 3 Key indicators of the basic guarantee layer and the proportion of cities that meet the standards

The average compliance rate of key indicators in the open quality layer is 47.92%, a decrease of 0.22 percentage points from the previous year, and the overall performance has declined (see Table 4).

表4 开放质量层关键指标及城市达标情况
指标名称	城市达标情况
数据集数量	26.67%的城市超过均值（3404.73个）
可用数据集比例	3/4的城市超过均值（92.37%），15个城市达到100%
开放新冠肺炎疫情数据	20个城市
有效API比例	13个城市超过70%，8个城市为100%，6个城市不提供API
开放机构数量	13个城市超过50个，6个城市的开放机构是个位数
及时更新的数据集比例	均值为37.95%，低于均值的城市有14个，11个城市的数值为0
数据集元数据项标准元数据完备率	12个城市超过均值（35.06%），只有贵阳1个城市达到100%
元数据值的标准元数据覆盖率	19个城市超过均值（85.65%）

The average compliance rate of key indicators in the user usage layer is 35.66%, an increase of 6 percentage points from the previous year, and the performance has significantly improved (see Table 5).

表5 用户使用层关键指标及达标城市数量
单位：个
指标名称	达标城市数量
提供“数据下载量”字段	13
拥有API调用次数的统计元数据	5
设置数据评价功能并公开了评分或评价内容	14
同时公开评分和评价内容	7
提供数据请求模块	18
为实现数据请求的功能而设计了专门系统	16
公开地回复了用户的数据请求	10
公开了建议响应的次数	7
采用可视化方式呈现数据	20
同时提供仪表板和地图两种可视化服务	5
提供常用的开发工具	10

Table 5 Key indicators of user usage layer and number of cities that meet the standards

The average compliance rate of key indicators in the value release layer was 34.67%, an increase of 10.27 percentage points from the previous year, indicating a significant improvement in performance (see Table 6).

表6 价值释放层关键指标及城市达标情况
指标名称	城市达标情况
创新企业	拥有10家以上创新企业的城市只有9个，有12个城市暂无创新企业
进入独角兽名单的创新企业	0个企业
没有开放数据创新企业融资记录	18个城市
拥有“试点应用（典型应用）”的城市	6个城市
权威报告收录因数据开放带来政府效率提升案例	总数为16个
权威报告收录因数据开放带来政府透明度、响应、问责制提高案例	总数为11个，增长3个
权威报告收录因数据开放带来公民成本降低案例	总数为7个，增长1个
权威报告收录因数据开放带来政府成本降低案例	总数为2个
公开报道有关政府透明度、响应、问责制提高以及政府效率提升的数据	总数为0个
公开报道有关因数据开放带来政府效率提升的数据	总数为0个
利用城市开放数据公开发布的科研论文和图书总数	均值为90.03，超过均值的城市有7个
利用该城市开放数据获取专利总数	有数值的城市仍然是3个：纽约有4个、芝加哥有3个、巴黎有2个

The report summarizes 17 cities with significant advantages, including 10 star cities, as shown in Table 7.

表7 优势指标与明星城市
排名	城市名	主要优势	排名变化及明星称号
1	上海（中国）	①制定了《上海市公共数据开放暂行办法》，是中国第一部专门针对公共数据开放的地方政府规章 ②自评估以来连续3年政府工作报告都涉及数据开放内容 ③从2014年到2020年连续7年制订数据开放工作计划 ④开放平台有完整的开放许可协议 ⑤保留收费权利。“依申请类开放数据依特定条件享有免费访问、获取和增值利用的权利，但我们保留对部分数据加工产品收费访问及收费获取的权利” ⑥2015年至今连续7年举办“SODA上海开放数据创新应用大赛”，这也是国内首个大规模的政府数据开放创新大赛 ⑦拥有试点应用（典型应用）项目——普惠金融 ⑧累计创新产品149个 ⑨“State of Open Data：Histories and Horizons”评价上海数据开放模式时描述为“具有巨大创造力” ⑩《2020联合国电子政务报告》提及上海数据开放工作 ⑾可用数据集比例99.89% ⑿开放机构100个 ⒀元数据值的标准元数据覆盖率93.65% ⒁同时有数据下载量和API调用量的元数据统计。平均下载量和API调用量分别为442.07次和165.34次 ⒂同时公开对数据集的评论和评分 ⒃回复数据请求47次 ⒄回复数据建议104次	①连续两年获全球重要城市数据开放冠军 ②在用户使用层排名第1，荣获“用户使用之星”
2	纽约（美国）	①《开放数据法》（Open Data Law）是一部专门的开放数据法律，其2012 年通过市议会决议，于2018 年12 月31日起正式实施 ②市长数据分析办公室（MODA）和信息技术与电信部（DoITT）的数据开放团队负责纽约数据开放工作，并由市长直接管理，并要求其每年提交数据开放报告 ③开放平台有完整的隐私政策和开放许可协议 ④2020年市长管理报告和政府预算中均有数据开放内容 ⑤拥有试点应用（典型应用）项目——餐厅评级 ⑥培育86家数据开放创新企业 ⑦利用该城市的数据开放公开发表和出版的科研论文和图书数为283篇（部） ⑧利用该城市开放数据获取专利数为4个 ⑨有效API占比100% ⑩数据集平均下载量为3404.67次 ⑾回复数据请求100次	①连续3年获全球重要城市数据开放亚军 ②在基础保障层排名第1，荣获“基础保障之星” ③在价值释放层排名第1，荣获“价值释放之星”
3	芝加哥（美国）	①2012年颁布《开放数据行政令》 ②由市长任命负责开放数据的创新和技术部首席数字官 ③开放平台有完整的隐私政策和开放许可协议 ④拥有试点应用（典型应用）项目——开放网格 ⑤利用该城市开放数据公开发表和出版的科研论文和图书数为403篇（部） ⑥利用该城市开放数据获取专利数为3个 ⑦有效API占比100% ⑧数据集平均下载量为61114.56次 ⑨回复数据请求186次	①总排名上升2个位次 ①“数据平均下载量”排名第1，荣获“下载总量之星” ③“数据请求回复次数”排名第1，荣获“请求应答之星”
4	首尔（韩国）	①开放平台有完整的隐私政策和开放许可协议 ②从2013年开始制订专门数据开放计划 ③组织过13次开放数据竞赛 ④有284家开放数据创新企业 ⑤累计创新产品817个 ⑥利用该城市开放数据公开发表和出版的科研论文和图书数为255篇（部） ⑦及时更新比例92% ⑧同时公开对数据集的评论和评分	①总排名下降1个位次 ②“创新产品数量”排名第1，荣获“创新产品之星” ③“组织开放数据大赛届次”排名第1，荣获“竞赛组织之星”
5	贵阳（中国）	①《贵阳市政府数据共享开放条例》是一部专门的地方性法规 ②《贵阳市大数据安全管理条例》是专门的大数据安全管理条例 ③开放数据许可协议完整 ④可用数据集比例为100% ⑤开放机构257个 ⑥数据集元数据项标准元数据完备率100% ⑦元数据值的标准元数据覆盖率100% ⑧数据集平均下载量为496.30次 ⑨同时公开对数据集的评论和评分 ⑩回复数据请求42次	①总排名上升1个位次 ②在开放质量层排名第1，荣获“开放质量之星”
6	洛杉矶（美国）	①有专门开放数据行政命令：2013年洛杉矶市政府《第3号行政指令》 ②有《网络安全指令》 ③开放许可协议完整 ④2020年的政府预算中包含数据开放与数字服务的项目 ⑤从2014年开始连续7年组织LA hacks大赛 ⑥可用数据集比例为100% ⑦有效API占比100% ⑧元数据值的标准元数据覆盖率93.25% ⑨数据集平均下载量为5843.21次 ⑩回复数据请求110次	总排名上升3个位次
7	广州（中国）	①拥有试点应用（典型应用）项目——壹镇通 ②可用数据集比例为100% ③数据集元数据项标准元数据完备率88.64% ④元数据值的标准元数据覆盖率98.73% ⑤及时更新的数据集比例87.88% ⑥同时公开对数据集的评论和评分 ⑦回复数据请求20次	①总排名上升1个位次 ②排名第1次超过深圳
8	深圳（中国）	①保留数据收费权利。“本网站提供的各项网络服务目前均为免费，但我们保留收费浏览及收费下载的权利” ②《深圳市人民政府2020年政府信息公开工作年度报告》中包括数据开放内容 ③可用数据集比例为100% ④有效API占比98.81% ⑤数据集元数据项标准元数据完备率93.73% ⑥元数据值的标准元数据覆盖率99.28% ⑦同时有数据下载量和API调用量的元数据统计。平均下载量和API调用量分别为149.82次和9269.55次 ⑧平台同时公开对数据集的评论和评分 ⑨回复数据请求123次	总排名下降1个位次
9	北京（中国）	①颁布《北京市交通出行数据开放管理办法（试行）》 ②有专门数据开放计划 ③累计创新产品70个 ④可用数据集比例为90.25% ⑤开放机构103个 ⑥同时有数据下载量和API调用量的元数据统计。平均下载量和API调用量分别为31.43次和1.26次 ⑦回复数据建议20次	总排名下降5个位次
10	青岛（中国）	①颁布《青岛市公共数据开放管理办法》 ②有完整的开放许可协议 ③举办了山东省数据应用（青岛）创新创业大赛 ④数据集数量9051个 ⑤可用数据集比例为100% ⑥平台同时公开对数据集的评论和评分 ⑦回复数据请求47次 ⑧回复数据建议10次	①第1次被纳入评估对象即获得第10名，荣获“明日希望之星”
11	伦敦（英国）	①开放平台有完整的隐私政策和开放许可协议 ②拥有试点应用（典型应用）项目——Citymapper ③利用该城市开放数据公开发表和出版的科研论文和图书数为528篇（部） ④开放机构115个 ⑤及时更新比例87.87% ⑥元数据值的标准元数据覆盖率为92.78%	①总排名上升7个位次 ②“利用该城市开放数据公开发布的科研论文和图书总数”排名第1，荣获“学术引用之星”
12	香港（中国）	①拥有试点应用（典型应用）项目——MOOVIT实时公交 ②有仪表板和地图数据两种数据可视化呈现手段 ③可用数据集占比94.70% ④开放机构111个	总排名上升1个位次
14	东京（日本）	令和2年（2020年）东京都预算纲要，包含数据开放预算	①总排名上升1个位次 ②“可用数据集”26410个，排名第1，荣获“数据载量之星” ③“及时更新数据比例”97.22%，排名第1，荣获“更新及时之星”
15	巴黎（法国）	①开放平台有完整的隐私政策和开放许可协议 ②举办了5届开放数据大赛 ③可用数据集占比100% ④有效API比例100% ⑤元数据值的标准元数据覆盖率94.33% ⑥同时有数据下载量和API调用量的元数据统计。平均下载量和API调用量分别为18587.85次和369807.52次	①总排名下降5个位次 ②“API调用量”排名第1，荣获“数据调用之星”
16	新加坡（新加坡）	①《2020联合国电子政务报告》中提及新加坡数据开放工作 ②可用数据集占比100%	总排名下降4个位次
19	杭州（中国）	①2018年开始制订数据开放计划，早于青岛 ②创新产品117个 ③可用数据集占比100% ④同时有数据下载量和API调用量的元数据统计平均下载量和API调用量分别为47.56次和0.30次 ⑤回复数据建议15次	作为2020年才上线的数据开放平台，部分指标表现突出，荣获“成长潜力之星”
21	悉尼（澳大利亚）	①开放平台有完整的隐私政策和开放许可协议 ②2020政府工作报告和预算中均包含数据开放内容 ③《2020联合国电子政务报告》提及悉尼数据开放工作 ④可用数据集占比100%	总排名上升3个位次

By comparing horizontally and vertically, analyze the indicators that need to be improved in 9 cities in China, and provide the following suggestions.

（1） Shanghai leverages its advantages to cultivate and improve an open data ecosystem

In 2021, although Shanghai maintained its leading position globally, its total score decreased by 30.34% year-on-year. Shanghai can take the following measures: formulate a complete privacy policy for open platforms, increase the proportion of effective APIs, update data in a timely manner, improve the completeness rate of standard metadata items in datasets, provide users with data dashboards, continue to cultivate innovative enterprises, increase the publicity of urban data openness, and initiate research on the contribution rate of open data in the political, economic, and social fields.

（2） Guiyang accelerates the formulation of regulations and standards, continuously enhances the advantages of the big data industry

In 2021, Guiyang's ranking rose by one place, with a year-on-year decrease of 0.10% in total score. Guiyang needs to improve its platform privacy policy, open up more city level data, strive to increase the proportion of effective APIs, improve API call volume metadata, provide users with data dashboards, continue to organize data open competitions and expand the scale and influence of the competitions, vigorously cultivate open data innovation enterprises, and increase the promotion of urban data openness.

（3） Guangzhou maintains platform advantages to promote data value conversion

In 2021, Guangzhou's ranking rose by one place, with a year-on-year increase of 7.36% in total score, and surpassed Shenzhen for the first time. Guangzhou can take the following measures: formulate a complete platform privacy policy, improve the integrity of open license agreements, open up more data, increase the proportion of effective APIs, increase the metadata of "API call volume", provide users with data dashboards, persist in organizing open data competitions, vigorously cultivate innovative enterprises, and increase the promotion of urban data openness.

In 2021, although Shenzhen dropped one place, the total score increased by 7.13% year-on-year. The next step for Shenzhen is to develop a complete platform privacy policy, open up more data, expand the scope of open institutions, update data in a timely manner, provide users with data dashboards, continue to organize open data competitions, cultivate innovative enterprises, and increase the publicity of urban data openness.

（5） Beijing improves platform metadata quality and platform interaction function

In 2021, Beijing dropped 5 places, with a year-on-year decrease of 24.11% in total score. Beijing needs to improve the integrity of its platform privacy policies and open license agreements, significantly increase the proportion of effective APIs, increase the "update frequency" metadata, and publicly disclose user comments and ratings on data, promptly respond to user data requests, provide users with data dashboards, cultivate innovative enterprises, increase the promotion of urban data openness, and initiate research on the contribution rate of open data in the political, economic, and social fields.

（6） Qingdao accelerates the cultivation and improvement of platform functions and data industry

In 2021, Qingdao achieved outstanding performance by ranking 10th on the evaluation list for the first time. Qingdao can try to take the following measures: improve the integrity of privacy policies on open platforms, expand the scope of open institutions, increase the proportion of effective APIs, update data in a timely manner, increase metadata on "data resource keywords" and "API call volume", provide users with data dashboards, persist in organizing open data competitions, vigorously cultivate innovative enterprises, and increase the promotion of urban data openness.

In 2021, Hong Kong's ranking rose by one place, with a total score increase of 10.81% year-on-year. Hong Kong should improve its privacy policy, open up more data, strive to increase the proportion of effective APIs, increase metadata for "data resource keywords," "data downloads," and "API call volume," improve the coverage of standard metadata values, enhance data evaluation and request capabilities, promptly respond to user data suggestions, organize open data competitions, vigorously cultivate innovative enterprises, and increase the promotion of urban data openness.

（8） Taipei consolidates its foundation and improves the scattered status of its datasets

In 2021, Taipei dropped 4 places and its total score decreased by 7.48% year-on-year. Taipei should formulate a special plan for data opening, change the fragmented status of data sets, open up data related to the COVID-19, vigorously increase the proportion of available data, increase the proportion of effective APIs and the standard metadata completeness rate of data set metadata items, increase the data evaluation function, provide users with data dashboards and data maps, provide users with data development tools, vigorously cultivate innovative enterprises, and increase the publicity of urban data opening.

In 2021, Hangzhou entered the evaluation scope for the first time, ranked 19th, and was awarded the "Star of Growth Potential", indicating great potential for future progress. Hangzhou can improve the integrity of privacy policies, open up more data, expand the scope of open institutions, increase metadata for "data resource keywords" and "update frequency", provide users with data dashboards, organize open data competitions, vigorously cultivate innovative enterprises, and increase the promotion of urban data openness.