DMP: home field advantage in professional soccer

Data management plan (DMP) DMP: home field advantage in professional soccer Version Effective date Description of document/changes 1.0 27/11/2025 First version of the DMP – created for the start of the project Level of distribution This DMP is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). It is publicly available under 10.5281/zenodo.17740846 2 DMP version 1.0 Project details Project Coordinator Principal Investigator Not applicable Contact person (responsible for data management and DMP) Nikolas Graf, [email protected], TU Wien, ROR: ror.org/04d836q62 Contributors Nikolas Graf, [email protected], TU Wien, ROR: ror.org/04d836q62, Researcher Start date 2025-11-30 End date 2026-01-29 Funder Not applicable Funding programme, grant number Not applicable Internal project number None Reference This DMP is directly based on the Use Case Description submitted in Exercise 1. List of acronyms DMP data management plan RDM research data management … … … … … … … … … … … … DMP version 1.0 3 Content INHALTSVERZEICHNIS INTRODUCTION 4 Science Europe practical guide, FAIR data 4 Relevant Policies and Guidelines 4 1. DATA DESCRIPTION 5 1a Lists of datasets that will be reused or produced 5 1b Data generation and reuse 5 2. DOCUMENTATION AND DATA QUALITY 6 2a Data organisation, metadata and documentation 6 2b Data quality control 6 3. STORAGE AND BACKUP DURING RESEARCH PROCESS 6 3a Storage and backup facilities 6 3b Data security and protection of sensitive data 7 4. LEGAL AND ETHICAL REQUIREMENTS 7 4a Personal data 7 4b Intellectual property rights and ownership 7 4c Ethical issues 7 5. DATA SHARING AND LONG-TERM PRESERVATION 7 5a Data publication and access conditions 7 5b Long-term preservation and deletion of data 8 6. RDM RESPONSIBILITIES AND RESOURCES 8 6a RDM-roles and responsibilities 8 6b Resources 9 4 DMP version 1.0 Introduction Science Europe practical guide, FAIR data A DMP is a structured document that keeps record of what research data is created and what happens to that data during and after a project. It helps with planning the research process and defining responsibilities in a research project involving several researchers or institutions. For writing this DMP, we followed the recommendations of Science Europe as they reflect the guidelines agreed upon by the major funders in Europe. To make our data FAIR, they generally will be treated according to the following criteria:  We will make our data findable, by uploading it to a data repository that provides a persistent identifier and adding relevant metadata.  We will make our data accessible by providing open access to data, wherever possible. In cases, where open access is not possible, we will provide meaningful metadata plus contact information for access requests.  We will make our data interoperable by providing and describing data in a way that is common within our domain by using the same file formats, schemas and vocabularies. We will provide good documentation for all our datasets.  We will make our data reusable by adding metadata and comprehensive Readme files to all published datasets. The descriptions include details on the methodology used, analytical and procedural information. In case of publication, licenses for code and data will always be assigned and clearly marked. Relevant Policies and Guidelines  European Commission’s document on Ethics and Data Protection: https://ec.europa.eu/info/funding-tenders/opportunities/docs/20212027/horizon/guidance/ethics-and-data-protection_he_en.pdf  Other (e.g. from a project partner) DMP version 1.0 5 1. Data description 1a Lists of datasets that will be reused or produced Produced datasets dataset ID title type format estimated volume contains sensitive data P1 research_question_a nswers Plain text text/plain 100 - 1000 MB no P2 process_research_q uestions Source code application/xpython-code 100 - 1000 MB no Description for "research_question_answers": This dataset is considered to be part of the produced data. It is a single text file produced as the output of a source-code execution and contains the answers to all the research questions: 1. The average points achieved from the examined teams in the examined season, separated into the home points average and the away points average. Furthermore the difference home points average minus away points average. 2. The differences home points average minus away points separated into all examined leagues in a list, furthermore the maximum and minimum value of that list. 3. Separated into the examined periods, the differences home points average minus away points average, and the change between these values. Description for "process_research_questions": This dataset is considered to be part of the produced data. It is a single source-code file authored by the researcher and is responsible for the accumulation and the processing transforming the reused data into the produced data using the csv library of the python programming language. Reused datasets dataset ID title source rights (e.g. license) contains sensitive data R1 Major football league results 2024/25 https://github.com/datasets/foo tball-datasets PDDL v1.0 no R2 International football game results https://github.com/martj42/inter national_results CC0 v1.0 Universal no Description for "Major football league results 2024/25": This dataset consist of five csv files, one for each examined league (Bundesliga, Premier League, Serie A, La Liga, Ligue 1). Each of these files contains the entire amount of encounters during the season with all necessary columns to answer the research questions. Each file is named "season-2425.csv", placed as the only file in a directory named after the corresponding league. The files are obtained 6 DMP version 1.0 from the source below under the Public Domain Dedication and License v1.0 Description for "International football game results": This dataset consist of a single csv file. It contains a selection of national-team-encounters starting with the year 1872 until 2024, with all necessary columns to answer the research questions. The file is named "results.csv" and is obtained from the source below under the Creative Commons Zero v1.0 Universal license 1b Data generation and reuse Methods and software used for data generation and reuse The reused data will be accumulated and processed into the produced data using the csv library of the python programming language. 2. Documentation and data quality 2a Data organisation, metadata and documentation  The project is version-controlled using Git.  Folder structure keeps produced and reused data strictly separated: o /process_research_questions.py o /produced_data/ → contains only P1 o /reused_data/league/<league_name>/season-2425.csv → R1 o /reused_data/international/results.csv → R2  Metadata: o README files (Markdown) describe data structure and workflow. o Repository-provided metadata (e.g., Dublin Core / DataCite) will be completed during publication. 2b Data quality control The following data quality checks will be done: repeated samples or measurements and peer review of data. 3. Storage and backup during research process 3a Storage and backup facilities For the duration of the project, storage and backup of data will be ensured by Nikolas Graf (acting as the person responsible for data management and DMP) in cooperation with the system operator. The data will be stored on the servers of TU Wien. P1 (research_question_answers), P2 (process_research_questions), R1 (Major football league results 2024/25), R2 (International football game results) will be stored on TUcloud: TUcloud is a sync&share service provided by Campus IT for TU Wien members. It runs on Campus IT servers and offers features known from public cloud systems, such as Dropbox, for example, the exchange of data with authorised persons. Deleted files can be recovered within 180 days. DMP version 1.0 7 3b Data security and protection of sensitive data We pay strict attention to compliance with the relevant institutional and national data protection policies listed in the introduction of this document. At this stage, it is not foreseen to process any sensitive data in the project. If this changes, advice will be sought from the data protection specialist at TU Wien, and the DMP will be updated. Access to data during research: dataset ID selected project members all other project members the public P1 reading only reading only reading only P2 writing reading only reading only R1 reading only reading only reading only R2 reading only reading only reading only 4. Legal and ethical requirements 4a Personal data At this stage, it is not foreseen to process any personal data in the project. If this changes, advice will be sought from the data protection specialist at TU Wien, and the DMP will be updated. 4b Intellectual property rights and rights of use  Reused datasets: o R1 under PDDL 1.0 → can be reused without restricons o R2 under CC0 1.0 → can be reused without restricons  Produced datasets: o Licensed under CC BY 4.0, as declared at the top of the DMP.  The researcher holds authorship of P1 and P2 but provides open access under CC BY. 4c Ethical issues No particular ethical issue is foreseen with the data to be used or produced by the project. This section will be updated if issues arise. 5. Data sharing and long-term preservation 5a Data publication and access conditions As far as possible, obtained datasets will be published in repositories. Details on access conditions, reuse licenses, reasons for restrictions, etc. are collected in the table below. 8 DMP version 1.0 dataset ID access conditions estimated publication date location for publication (repository) PID license P1 Open Access 2025-11-30 TU Wien Research Data 10.70124/4 n9szsxq92 CC BY 4.0 P2 Open Access 2025-11-30 TU Wien Research Data 10.70124/t 26czx7762 CC BY 4.0 Repository description: TU Wien Research Data is an institutional repository of TU Wien to enable storing, sharing and publishing of digital objects, in particular research data. It facilitates the funders' requirements for open access to research data and the FAIR principles by making research output findable, accessible, interoperable, and reusable. A DOI is assigned to each dataset published in TU Wien Research Data. This service is developed by the TU Wien Center for Research Data Management and hosted by TU.it. https://test.researchdata.tuwien.at/ Methods or software needed to access and use data: The aren't any tools necessary in order to view the results of the analysis, however if one aims for running the analysis locally, a python executable is needed in order to run the script. 5b Long-term preservation and deletion of data dataset ID location for long-term storage minimum retention period (≥ 10 years) foreseeable research uses and/or users P1 TU Wien Research Data 10 years Anyone who's interested in the statistical analysis of professional soccer games lying in the past, including professionals working in the sports industry as well as researchers examining different research questions. P2 TU Wien Research Data 10 years 6. RDM responsibilities and resources 6a RDM-roles and responsibilities The researcher will direct the data management process overall, with the research assistants responsible for ensuring metadata production, day-to-day cross-checks, back-up and other quality control activities are maintained. DMP version 1.0 9 6b Resources There are no costs dedicated to data management and ensuring that data will be FAIR.