SotA Lens: A Network-Augmented Methodology and Tool for Exploratory State-of-the-Art Reviews

TL;DR

SotA Lens is a network-augmented methodology and lightweight software toolkit designed to facilitate exploratory State-of-the-Art reviews, especially in multidisciplinary fields with dispersed and unstable terminology.

Contribution

It introduces an original review-support methodology and software that map broad research fields, identify clusters and gaps, aiding researchers before systematic review protocols.

Findings

Generated a citation graph with 2,198 vertices and 8,249 edges from 200 seed results.

Produced a filtered component with 986 vertices and 2,693 edges, labeled into sixteen communities.

Demonstrated the approach on Dynamic Projection-Mapping and Spatial Augmented Reality domains.

Abstract

Researchers often begin new projects by conducting a broad State-of-the-Art review before they are ready to define the narrow protocol required by a systematic review. This is especially common in multidisciplinary areas where terminology is unstable, communities are weakly connected, and relevant work is dispersed across technical and application domains. This paper presents SotA Lens, a network-augmented methodology and lightweight software toolkit for exploratory State-of-the-Art reviews. The approach combines documented seed search, DOI-level metadata resolution, bounded citation expansion, directed graph construction, community detection, ranking of authors and subject terms, and human labelling of research communities. It is designed to complement, not replace, established review protocols such as PRISMA, PRISMA-ScR, systematic mapping studies, and bibliometric science mapping. The method is demonstrated through a proof-of-concept review of Dynamic Projection-Mapping and Spatial Augmented Reality. Starting from approximately 200 seed search results, the workflow produced a citation graph with 2,198 DOI-level vertices and 8,249 reference edges; a filtered largest component for 2010-2023 contained 986 vertices, 2,693 edges, and sixteen labelled communities. The contribution is both methodological and practical: SotA Lens helps researchers map broad fields, identify clusters and gaps, and produce auditable review artifacts before committing to a narrower systematic review protocol. This paper is not intended as a domain survey of Dynamic Projection-Mapping or Spatial Augmented Reality; rather, it introduces and demonstrates an original review-support methodology and software artifact using that domain as a proof-of-concept case study.