Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects"

Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" Version 2 Description This plan outlines the data used in the project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" (project ID: VPP – Mākslīgais intelekts – 2024/1-0003), which is funded by the Latvian Council of Science. Funder Grant Latvian Council of Science VPPMākslīgais intelekts-2024/1-0003 Researchers Raivis Skadiņš (0000-0003-0929-2380) LICENSE:CC-BY-4.0 DOI: - 06/10/2025 Organizations University of Latvia Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 1. Main Info Title of DMP: Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" Description: This plan outlines the data used in the project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" (project ID: VPP – Mākslīgais intelekts – 2024/1-0003), which is funded by the Latvian Council of Science. Researchers: Raivis Skadiņš (0000-0003-0929-2380) Organizations: University of Latvia Contact: Skadiņš Raivis ([email protected]) 2. Funding Funding organizations: Latvian Council of Science Grants: VPPMākslīgais intelekts-2024/1-0003 Project: 3. License License: CC-BY-4.0 Access Rights: Public Publication Date: 2025-02-27 4. Templates Descriptions CFCA example documents Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 This dataset has been prepared by the Central Finance and Contracting Agency (CFCA) to provide researchers with insights into CFCA processes related to the monitoring, analysis, and processing of complex project management data. The dataset is stored in CFCA's information system, KPVIS. Due to the sensitive nature of the data, it is not publicly accessible. Template: LCS FARP Type: Dataset 1 Data Summary 1.1 Data Summary 1.1.1 What is the purpose of the data collection/generation? This dataset, prepared by the Central Finance and Contracting Agency (CFCA), is designed to support research on CFCA’s processes for monitoring, analyzing, and managing complex project data. It provides valuable insights into how CFCA oversees project implementation and evaluates performance. 1.1.2 Type of data generated/collected Textual data 1.1.3 Format of data generated/collected • HTML • PDF • XLS • Others Microsoft Word 1.1.4 Expected size of the data – give expected size and choose unit of measurement 50 MB Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 1.1.5 Are you re-using this data set? No 1.1.6 If No, please describe, if you have considered re-using any of existing data? This dataset is specific to CFCA and contains sensitive information. It has not been previously published and has been created exclusively for this project. 1.1.8 To whom the data might be useful ("data utility")? Other relevant remarks) Just for the goals of this project 2 Research Data Management 2.1 Metadata and documentation 2.1.1 Will data be attributed with standard identification mechanism (e.g. persistent and unique identifiers such as Digital Object Identifiers – DOI)? No 2.1.2 Do you plan to provide metadata for your data? Yes 2.1.3 Will you use any metadata standard? Yes Dublin Core 2.1.4 Will search keywords be provided that optimize possibilities for re-use? No 2.1.5 Will you follow any naming conventions for keywords? No 2.1.6 Will you provide clear version numbers? Yes 2.2 Making data openly accessible 2.2.1 What type of access the data generated/produced will have (choose one)? Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 restricted, no access (access is denied, files will be opened only through contact person to the authors) The dataset is stored in CFCA's information system, KPVIS. Due to the sensitive nature of the data, it is not publicly accessible. 2.2.2 Will you apply embargo period to access for your data? No 2.2.3 Will data, associated metadata, documentation and code be made accessible with means of a repository? No Data will be stored in CFCA's information system KPVIS. 2.2.4 What methods or software tools are needed to access the data? CFCA's information system KPVIS 2.2.5 Will documentation about the software needed to access the data included? No 2.2.6 Is it possible to include the relevant software (e.g. in open source code)? No 2.3 Making data interoperable 2.3.1 Are the formats open to software applications and to recombination with different data sets? No 2.3.2 Will you use data standard vocabulary/taxonomy to make your data interoperable? No 2.4 Increase data re-use 2.4.2 Are the data usable by third parties, in particular after the end of the project? No Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 2.4.4 How long is it intended that the data remains re-usable? 2025-08-27 2.4.5 Are data quality assurance processes provided? No 3 Resources and Security 3.1 Allocation of resources 3.1.1 How will costs be covered for making data FAIR during project realization? Data will be created by CFCA, as their contribution to the project. 3.2 Data security 3.2.1 What security measures will be used for data security? Data is stored in CFCA'a information system KPVIS, which provides user authentication and authorization. 3.3 Ethical aspects 3.3.1 Are there any ethical or legal issues that could have an impact on data collection and sharing? No 3.3.2 Have you got/will you get permission from ethics committee to collect and process data (if applicable)? No 3.3.3 Is informed consent for data sharing and long term preservation included in questionnaires dealing with personal data, if applicable? No 3.3.4 Will data collected/generated include personal data/ sensitive information? Yes 3.3.5 If yes, what are the methods used to process and access personal data/sensitive information Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 Other Due to the sensitive nature of the data, it is not publicly accessible. Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 Procurement Validation Dataset The dataset consists of 30 procurement documents evaluated by CFCA experts. The procurement checklists prepared by the experts have been transformed into machinereadable form. For each procurement, 168 questions are asked regarding its compliance with legislation, and each question has an answer provided. The dataset is divided into two subsets: a development dataset (10 procurements) and an evaluation dataset (20 procurements). The dataset consists of: 1) questions based on the checklist S.7.1.-PL-21 (09.12.2019 edition); 2) a labeled dataset corresponding to 30 procurements evaluated by CFCA. Template: LCS FARP Type: Dataset 1 Data Summary 1.1 Data Summary 1.1.1 What is the purpose of the data collection/generation? The dataset was created to support the evaluation of automated procurement validation methods within the project. It contains procurement projects, relevant legislation, and reference annotations of procurement validation questionnaires associated with each project. The reference annotations (i.e., correct answers) were originally provided by the national authority, the Central Finance and Contracting Agency (CFCA), and subsequently transformed by the authors into a machine-readable format. This dataset directly contributes to the project objective of testing and improving AI-based approaches for procurement validation. 1.1.2 Type of data generated/collected Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 2.2.3 Will data, associated metadata, documentation and code be made accessible with means of a repository? Yes CLARIN-LV repository 2.2.5 Will documentation about the software needed to access the data included? No 2.2.6 Is it possible to include the relevant software (e.g. in open source code)? No 2.3 Making data interoperable 2.3.1 Are the formats open to software applications and to recombination with different data sets? No 2.3.2 Will you use data standard vocabulary/taxonomy to make your data interoperable? No 2.4 Increase data re-use 2.4.1 How will the data be licensed to permit the widest re-use possible? Indicate the license planned to use CC BY-NC-SA 4.0 https://creativecommons.org/licenses/by-nc-sa/4.0/ 2.4.2 Are the data usable by third parties, in particular after the end of the project? Yes 2.4.3 When will the data be made available for re-use? 2025-08-27 2.4.5 Are data quality assurance processes provided? Data Management Plan | Data Management Plan for project "Analysis of the Applicability of Artificial Intelligence Methods in the Field of European Union Fund Projects" LICENSE:CC-BY-4.0 DOI: - 06/10/2025 No 3 Resources and Security 3.1 Allocation of resources 3.1.2 Who will be responsible for data management in your project? Raivis Skadiņš (0000-0003-0929-2380) 3.3 Ethical aspects 3.3.1 Are there any ethical or legal issues that could have an impact on data collection and sharing? No 3.3.2 Have you got/will you get permission from ethics committee to collect and process data (if applicable)? No 3.3.3 Is informed consent for data sharing and long term preservation included in questionnaires dealing with personal data, if applicable? No 3.3.4 Will data collected/generated include personal data/ sensitive information? 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