| --- |
| tags: |
| - wireless |
| - taxonomy |
| - communication-systems |
| - datasets |
| - metadata |
| - benchmarking |
| - reproducibility |
| license: mit |
| language: |
| - en |
| pretty_name: Wireless Taxonomy Dataset |
| --- |
| |
| # 📶 Wireless Taxonomy Dataset |
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| 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. |
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| 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 |
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| The dataset provides a unified reference for wireless research data sources, including: |
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| - 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 |
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| 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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| --- |
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| ## 🗂️ Dataset Structure |
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| This repository consists of **three interlinked CSV tables**, each available as a configuration: |
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| | Config | File | Description | |
| |---------|------|-------------| |
| | **`datasets`** | [`Wireless_Datasets.csv`](./datasets/Wireless_Datasets.csv) | Metadata describing qualifying wireless datasets, including dataset names, OSI layer coverage, modalities, and collection environments. | |
| | **`papers`** | [`Wireless_Papers.csv`](./papers/Wireless_Papers.csv) | A structured index of research papers analyzed, including authors, venues, years, dataset usage, and taxonomy keys. | |
| | **`bibtex`** | [`Bibtex.csv`](./bibtex/Bibtex.csv) | Canonical citation metadata linking publications to datasets via shared BibTeX keys. | |
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| ## 🔗 Linking and Relational Schema |
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| Each table contains a shared relational variable: **`bibtex_citation_key`**. |
| This key enables relational joins across the three tables. |
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| - 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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| --- |
|
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| ## 🧪 Methodology |
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| 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 |
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| | 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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| --- |
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| ## ⚙️ Example Usage |
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| ```python |
| 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() |
| |