Bibliometric collection on digital decision-support technologies and data integration in circular economy research (2015-2025)

DescriptionThis dataset contains the public bibliometric collection and reproduction package used for a bibliometric analysis of research at the intersection of circular economy, digital technologies, data integration, and decision support. The public corpus contains 2,953 included Scopus bibliographic records. The initial screened set comprised 4,731 records. Automated dictionary-based screening retained 2,924 records and excluded 1,807 records. A manual quality-control step was then applied to potential false negatives identified through QC flags: 34 automatically excluded records were manually audited, 29 records were added to the included corpus, and 5 records remained excluded. The final corpus therefore contains 2,953 included records. Although the underlying Scopus query covered the 2015–2025 period, the included collection spans 2016–2025 because no 2015 records remained after screening. The public collection is provided as included_corpus_public.csv. It excludes abstracts, cited references, affiliations, funding text and other restricted Scopus-derived full-text metadata. The accompanying bibliometric_pipeline.zip archive contains the R code, configuration files, screening dictionaries, manual include DOI list, public QC flags, generated bibliometric tables, figures and LDA outputs required to verify the reported results. The licensed raw Scopus export is not included. Search query TITLE-ABS-KEY ( "circular economy" )AND TITLE-ABS-KEY ( "decision support" OR "decision-support" OR "decision making" OR "decision-making" OR "decision support system*" OR "DSS" OR "multi-criteria" OR "MCDA" OR "MCDM" OR "data-driven" OR "data integration" OR "digital technolog*" OR "big data" OR "artificial intelligence" OR "machine learning" OR "internet of things" OR "IoT" OR "blockchain" OR "digital twin" OR "industry 4.0" OR "industry 5.0")AND PUBYEAR > 2014 AND PUBYEAR < 2026AND ( LIMIT-TO ( LANGUAGE , "English" ) )AND ( LIMIT-TO ( DOCTYPE , "ar" ) OR LIMIT-TO ( DOCTYPE , "re" ) )AND EXCLUDE ( AFFILCOUNTRY , "Iran" )AND EXCLUDE ( AFFILCOUNTRY , "Russian Federation" ) Screening logic Screening was implemented in a reproducible R pipeline based on title, abstract, author keywords, and index keywords. Records were evaluated using dictionary-based signals related to circular economy, digital technologies, decision support, data integration and decision context. Records without a circular economy signal were excluded. Records with a strong circular economy anchor in the title or keywords were retained when paired with decision-support, data-integration, or digital-technology signals in combination with decision-context evidence. Records with only an abstract-level circular economy signal were retained only under stricter conditions. QC flags were used to identify records requiring additional manual inspection, especially potential false negatives. QC flags did not imply automatic inclusion. Only records listed in the archived manual include DOI file were added after manual quality control. Eligibility criteria Eligible records were English-language journal articles and reviews within the 2015–2025 query window, with abstracts required. The dataset is intended to support transparency, reproducibility, and reuse in bibliometric and review-based research. Funding The research was funded by a grant from the state budget of Ukraine "Fundamentals of Sustainable and Inclusive Regional Spatial Development for Post-War Reconstruction in the Context of Digital Transformation" (# 0125U001620, 2025-2027).