NB-IoT End-to-End Data Path Fault Localization QA Dataset

#fault localization #data path analysis #evidence-based diagnostic reasoning #NB-IoT network fault diagnosis #end-to-end connectivity monitoring #IoT network troubleshooting

5000
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This dataset focuses on NB-IoT uplink and downlink service anomalies, pairing anomaly reports with textual observations from the access network, core network, and service connection path. Its question-and-answer records organize diagnostic questions, stepwise elimination reasoning, and final fault assessments across key segments of the end-to-end data path. It supports fault-localization reasoning training, diagnostic QA evaluation, and research on NB-IoT network operations; the sample count and other scale details have not been provided.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
confidence	number	Estimated confidence in the selected fault location, expressed as a value from 0 to 1.
final_answer	string	Direct answer to the diagnostic question, summarizing the most likely fault location and the main supporting rationale.
fault_hypothesis	string	Concise explanation of the likely fault mechanism and its location, grounded in the supplied observations.
elimination_steps	array	Ordered diagnostic steps that assess evidence and eliminate or retain possible fault locations along the data path.
traffic_direction	string	Direction of the affected NB-IoT business traffic.
anomaly_description	string	User-reported or system-reported description of the abnormal NB-IoT service behavior.
diagnostic_question	string	Question to be answered by tracing and localizing the fault along the end-to-end NB-IoT data path.
core_network_observation	string	Textual observations or diagnostic results for the NB-IoT core network portion of the data path.
access_network_observation	string	Textual observations or diagnostic results for the device and radio access network portion of the data path.
most_likely_fault_location	string	The end-to-end path segment most likely responsible for the reported anomaly.
service_connection_observation	string	Textual observations or diagnostic results for the connection between the core network and the destination service or application.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: The records focus on NB-IoT service anomaly diagnosis and include traffic direction, anomaly description, access and core network observations, service connection observations, diagnostic questions, elimination steps, the most likely fault location, a fault hypothesis, confidence, and a final answer.

Which tasks is the dataset suitable for?: It can support training and evaluation for end-to-end network fault localization, root cause analysis, evidence-based diagnostic reasoning, and question answering, including reasoning-oriented supervised fine-tuning.

What are the dataset size and quality specifications?: The available information describes the subject matter and field structure but does not specify the sample count, coverage versions, annotation agreement, or quality evaluation results. Review the product specifications and sample records before acquisition.

How can I obtain the data, and what license applies?: Access methods, available formats, and license terms should be confirmed in the product listing or with the data provider. Before use, verify that the license covers your intended training, evaluation, commercial deployment, and redistribution activities.

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Cite this Work

@dataset{Mobiusi2026,
  title={NB-IoT End-to-End Data Path Fault Localization QA Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/0d3be01a04cc78d291aec881ba398ca2?dataset_scene_id=19},
  urldate={2026-10-17},
  keywords={NB-IoT fault localization,NB-IoT QA dataset,IoT network diagnostics,end-to-end path troubleshooting,access network fault analysis,core network diagnostics,network root cause analysis,reasoning SFT data},
  version={1.0}
}

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