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Bibliographic Details
Main Author: Bian, Xin
Format: Recurso digital
Language:
Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.18812553
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Table of Contents:
  • <p>This dataset contains the bibliographic records underlying the study <em>“Digital Storytelling in Transforming Industrial Heritage Landscapes: An Evidence-Chain Audit of Regeneration-Relevant Interpretive Outcomes (2011–2026)”</em>.</p> <p>The data were retrieved from the Scopus database in February 2026 using a structured TITLE-ABS-KEY search strategy combining terms related to industrial heritage and digital storytelling. The search was restricted to English-language publications (Articles and Conference Papers) published between 2011 and February 2026.</p> <p>Following deduplication and multi-stage screening based on predefined inclusion and exclusion criteria, 42 studies were retained for full evidence-chain analysis. The dataset includes:</p> <ul> <li> <p>Full bibliographic metadata (authors, titles, year, source title, affiliations, DOI, abstract, keywords)</p> </li> <li> <p>Document type classification</p> </li> <li> <p>Publication year and source distribution</p> </li> <li> <p>Author country and collaboration information</p> </li> <li> <p>Keyword fields used for co-occurrence mapping and thematic clustering</p> </li> </ul> <p>This dataset supports:</p> <ul> <li> <p>Micro-bibliometric mapping (publication trends, source ecology, geographic distribution)</p> </li> <li> <p>Keyword co-occurrence network analysis</p> </li> <li> <p>Evidence-chain traceability auditing at the study level</p> </li> </ul> <p>The dataset is provided for transparency, reproducibility, and secondary bibliometric analysis. No personal data beyond publicly available bibliographic metadata are included.</p>