nram97/wireless_taxonomy

📶 Wireless Taxonomy Dataset

The Wireless Taxonomy Dataset is a structured corpus of wireless communication research metadata, created to support the development of a standardized benchmark for the wireless research community.
It captures the relationships between datasets, papers, and citations, emphasizing data provenance, collection environments, and modality-level detail across the OSI stack.

This taxonomy was curated as part an effort to systematically identify and classify datasets collected from real-world, lab-based, or high-fidelity wireless environments.

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🧭 Overview

The dataset provides a unified reference for wireless research data sources, including:

• Publications from ACM SIGCOMM, IMC, and CoNEXT (2022–2025)
• Descriptions of datasets used or generated in these papers
• Mappings between datasets, publications, and BibTeX references

The curation emphasizes datasets that involve physical or trace-driven wireless environments, such as operational LTE/5G systems, SDR testbeds, or validated wireless emulations.

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🗂️ Dataset Structure

This repository consists of three interlinked CSV tables, each available as a configuration:

Config	File	Description
datasets	Wireless_Datasets.csv	Metadata describing qualifying wireless datasets, including dataset names, OSI layer coverage, modalities, and collection environments.
papers	Wireless_Papers.csv	A structured index of research papers analyzed, including authors, venues, years, dataset usage, and taxonomy keys.
bibtex	Bibtex.csv	Canonical citation metadata linking publications to datasets via shared BibTeX keys.

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🔗 Linking and Relational Schema

Each table contains a shared relational variable: bibtex_citation_key.
This key enables relational joins across the three tables.

• A single dataset may link to multiple papers (e.g., reused benchmarks).
• Papers may list multiple datasets.
• Merging on bibtex_citation_key reconstructs the complete dataset–paper–citation graph.

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🧪 Methodology

The taxonomy was constructed through a combination of structured corpus analysis and manual validation.
Publications from major networking and wireless conferences between 2022 and 2025 were reviewed to identify papers containing datasets from qualifying wireless environments — namely, real-world deployments, physical testbeds, or high-fidelity simulations/emulations.

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📑 Schema Description

Field	Description
dataset_name	Name or descriptive identifier of the dataset.
bibtex_citation_key	Shared key linking datasets to papers and citations.
osi_layers	OSI layers represented in the dataset (e.g., L1, L4).
modalities	Collected data types (e.g., RF traces, latency, throughput).
availability	Indicates whether the dataset is open, closed, or n/a.
collection_environment	Describes how the dataset was collected: Real-world deployment, Physical Testbed, or High-Fidelity Simulation.

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⚙️ Example Usage

from datasets import load_dataset

# Load the dataset taxonomy
datasets_table = load_dataset("your-hf-username/wireless_taxonomy", name="datasets", split="train")

# Explore papers and linked citations
papers_table = load_dataset("your-hf-username/wireless_taxonomy", name="papers", split="train")
bib_table = load_dataset("your-hf-username/wireless_taxonomy", name="bibtex", split="train")

# Join tables via the BibTeX citation key
import pandas as pd

df = pd.merge(datasets_table.to_pandas(), papers_table.to_pandas(), on="bibtex_citation_key")
df.head()