Evidence map›Paper›PMID 39991486›Full record

ReviewInnovation (Cambridge (Mass.))2025

MetaCity: Data-driven sustainable development of complex cities.

Yunke Zhang, Yuming Lin, Guanjie Zheng, Yu Liu, Nicholas Sukiennik, Fengli Xu, Yongjun Xu, Feng Lu, Qi Wang, Yuan Lai and 9 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Innovation (Cambridge (Mass.)), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Yunke ZhangDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Yuming LinDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Guanjie ZhengJohn Hopcroft Center for Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China.
Yu LiuDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Nicholas SukiennikDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Fengli XuDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Yongjun XuUniversity of Chinese Academy of Sciences, Beijing 100049, China.
Feng LuUniversity of Chinese Academy of Sciences, Beijing 100049, China.
Qi WangDepartment of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA.
Yuan LaiSchool of Architecture, Tsinghua University, Beijing 100084, China.
Li TianSchool of Architecture, Tsinghua University, Beijing 100084, China.
Nan LiSchool of Civil Engineering, Tsinghua University, Beijing 100084, China.
Dongping FangSchool of Civil Engineering, Tsinghua University, Beijing 100084, China.
Fei WangUniversity of Chinese Academy of Sciences, Beijing 100049, China.
Tao ZhouBig Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
Yong LiDepartment of Electronic Engineering, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
Yu ZhengJD iCity, JD Technology & JD Intelligent Cities Research, Beijing 100176, China.
Zhiqiang WuCollege of Architecture and Urban Planning, Tongji University, Shanghai 200292, China.
Huadong GuoInternational Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cities are complex systems that develop under complicated interactions among their human and environmental components. Urbanization generates substantial outcomes and opportunities while raising challenges including congestion, air pollution, inequality, etc., calling for efficient and reasonable solutions to sustainable developments. Fortunately, booming technologies generate large-scale data of complex cities, providing a chance to propose data-driven solutions for sustainable urban developments. This paper provides a comprehensive overview of data-driven urban sustainability practice. In this review article, we conceptualize MetaCity, a general framework for optimizing resource usage and allocation problems in complex cities with data-driven approaches. Under this framework, we decompose specific urban sustainable goals, e.g., efficiency and resilience, review practical urban problems under these goals, and explore the probability of using data-driven technologies as potential solutions to the challenge of complexity. On the basis of extensive urban data, we integrate urban problem discovery, operation of urban systems simulation, and complex decision-making problem solving into an entire cohesive framework to achieve sustainable development goals by optimizing resource allocation problems in complex cities.

Indexed as

artificial intelligencedata-driven methodssustainable developmenturban complex systems

Identifiers

PMID39991486
PMCPMC11846039

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.