LLM NetOps/AIOps Six-Pillar Evidence Audit Dataset
Year: 2026
Type: dataset
Abstract: This dataset accompanies the survey “Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety” (arXiv:2605.12729, https://arxiv.org/abs/2605.12729). It provides the record-level evidence audit used to support the survey’s analysis of LLM-enabled NetOps and AIOps across operational capability and autonomy, architecture and tool grounding, assurance and operational control, evaluation and benchmarking, security and adversarial robustness, and human factors, governance, and standards. The dataset records evidential status, analytical pillar, operational domain, task, autonomy role where applicable, tool surface, evaluation setting, safety controls, inclusion rationale, manuscript location, and permissible claim boundary. Separate files provide the direct LLM-facing subset, operational-system coding, search-update records, coverage-validation records, transparent exclusions, contextual comparison surveys, and PRISMA-style search and corpus accounting. The release includes machine-readable CSV and JSON files, a formatted workbook, a data dictionary, a matching machine-readable bibliography, citation metadata, a CC BY 4.0 licence, and integrity checksums. It contains no source full text, reviewer correspondence, private contact details, or internal compilation material.
Source: Mendeley Data
DOI: 10.17632/2p5ppxzy4s
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204237193
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