2026-10-14T04:48:22Z https://www.scidb.cn/oai

10.57760/sciencedb.013zq 2026-09-29T16:16:23Z

2026-09-29 Supplementary Dataset for Research on Iteration of AIGC Animation Creation Methodology in the Text‑to‑Video Era doi:10.57760/sciencedb.013zq en This dataset is supplementary research data for the journal article The Iteration of Creative Methodology in AIGC Animation Production in the Era of Text‑to‑Video Models, prepared for journal data deposition and open‑access archiving requirements. It consists of four core components. First, the reference dataset containing 39 verified Chinese and English bibliographic entries with metadata including document type, authors, titles, publication venues, publication year, DOI or arXiv identifier, and verification status. Literature was cross‑checked against ACM DL, IEEE Xplore, arXiv, DBLP and CNKI. Second, comparative datasets of mainstream AIGC‑video platforms including Seedance 2.0, Kling 3.0, Runway Gen‑4/Gen‑4.5, Sora 2, Pika 2.5, Luma Ray3, Vidu Q3 and Hailuo 2.3. It compiles publicly available information covering pricing tiers, resolution, maximum generation duration, interaction features, team‑collaboration functionality and proxy‑model technical pathways. All platform‑related data are snapshot records as of September 2026; commercial parameters are subject to frequent updates and re‑verification is required for formal usage. Third, a comparison matrix contrasting traditional and AI‑era creative cognitive modes across seven dimensions: starting point of thought, core cognitive load, consistency assurance mechanism, distribution of creative agency, trial‑and‑error cost, decision visibility and source of uncertainty. Fourth, provenance records for all source materials with official URLs and reliability ratings. Case analysis, comparative research and creative‑workflow deconstruction were adopted in this study. No human‑subject data, personal private data or proprietary data were collected. Bilingual Chinese‑English workbook files are provided. Citation indices [1]‑[39] strictly follow the first‑appearance order in the original manuscript. This dataset can support further research on generative video, human‑AI co‑creation for animation, interaction design and AIGC creative methodology. Text‑to‑Video Model; AIGC Animation; Human‑AI Co‑Creation; Creative Methodology; Generative AI; Interaction Design Abuduaini Tuoheti PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank