DOI: 10.5281/zenodo.15467918
title: Advanced Energy Performance Assessment towards Smart Living in Building and District Level

description: Name: Data used to assess citizens’ preferences regarding accessibility and transport within the 15-minute city model.




Summary: This dataset contains survey responses from citizens across several European countries regarding their preferences on transport modes and acceptable access times to key urban services and infrastructures (e.g., green areas, educational centres, health services, and public transport stops). The data are used to analyse urban priorities and to identify citizen profiles through clustering techniques, supporting the assessment of the 15-minute city model from a citizen-centred perspective.




License: CC-BY-SA




Acknowledge: These data have been collected in the framework of the SMARTLIVINGEPC project. This project has received funding from the European Union’s Horizon Europe programme under grant agreement No. 101069639.




Disclaimer: Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.




Collection Date: 2024-1 / 2024-04 




Publication Date: 22/04/2025




DOI: 10.5281/zenodo.15467919




Other repositories: https://github.com/maria23p/MariaTFG.git




Author: University of Deusto




Objective of collection: The objective of this survey is to identify the most relevant indicators that will be used to develop an Advanced Assessment of the Energy Performance of neighborhoods, within the framework of the Smart Living EPC (SLEPC) project. To do this, the survey will collect information 






1 - Making a score of Categories and Indicators to assess neighborhoods.




2 - Carry out a brief evaluation of methodologies (asset or operational)




3 - Carrying out a valuation of parameters of the 15 min Cities.




Participants are asked to answer questions based on their knowledge and experience, and the survey is expected to last approximately 25 minutes. The information provided in this questionnaire will be used for research purposes. It will not be used in a way that allows the identification of individual responses. The data collected will be anonymous and no personally identifiable information will be collected. Participation is voluntary. There are no significant risks or benefits associated with participation. Anonymized research data will be archived in accordance with current data sharing practices.

The SLEPC project is funded by Horizon Europe and will run from October 2022 to September 2025. Its objective is to establish a new holistic and operational framework for the evaluation of the energy performance of buildings and neighborhoods, which integrates energy and non-energy evaluation, social aspects, life cycle analysis and life cost cycle analysis.  





Description:






RAW data (CSV):






Energy Performance Survey.csv: Public participants’ general survey Including mobility behaviour characteristics, transport preferences, energy related attitudes, and basic sociodemographic information.




Prolific_export_6628d87a7c0a6f8f8c32efdc.csv: Sociodemographic data exported from Prolific. Includes variables such as age, gender, and country residence, as well as participation metadata. Used to enrich survey responses.





Processed file (CSV):






mergedataUNIF.csv: Integrated dataset merging survey responses with Prolific sociodemographic data when possible, and complemented with information from the survey. This file is the main dataset used for the analysis, including clustering and correlation studies related to the 15-minute city model.  





The information below provides a structured description of the variables grouped by blocks:





1. Survey metadata and administrative variables: Columns 1 - 6 : Includes identifiers and technical information related to survey completion, such as Respondent.ID, Respondent.ID, Collector.ID, Start.Date, End.Date, language of response, and consent confirmation.







2. Proximity and urban services importance: Columns 7 - 12 & 16-18 :  Variables measuring the importance assigned by respondents to the proximity of different urban infrastructures and services (e.g. healthcare, education, green areas, etc.) Responses are recorded on a continuous scale from 1 (not important at all) to 100 (extremely important).







3. Preferred access time to services: Columns 19 - 138 : Numeric variables indicating the maximum acceptable travel time (in minutes) to reach different urban services and infrastructures, with values ranging from 0 to 60 minutes.







4. Preferred means of transport: Columns 139 - 258 : Categorical variables capturing respondents’ preferred modes of transport (e.g. walking, cycling, public transport, private car, etc.) to access different destinations on a regular basis.







5. Behavioural responses under fuel scarcity scenarios: Columns 259 - 278 : Variables capturing respondents’ stated behavioural reactions to hypothetical fuel scarcity scenarios, such as fuel price increases or fuel rationing due to international conflicts. 







6. Sociodemographic variables: Columns 279 - 385 : Includes gender, age education level, employment status, income range, political orientation, country of residence, and other background variables.







7.  Attention check  question: Columns 13 - 15 :  Include a question designed to verify the consistency of respondents’ answers. Responses are used to identify inattentive or random responders.







5 star: ⭐⭐⭐




Preprocessing steps: The data has been re-coded and cleaned using the scripts provided.  




Reuse: NA




Update policy: No more updates are planned.




Ethics and legal aspects: The survey does not contain personal data and all persons answering it have accepted a consent form. 




Technical aspects: 




Other: