Add comprehensive README with BioASQ attribution and license info

README.md

@@ -1,70 +1,294 @@
 ---
-dataset_info:
-  features:
-  - name: type
-    dtype: string
-  - name: question
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: ideal_answer
-    dtype: string
-  - name: documents
-    sequence: string
-  - name: snippets
-    list:
-    - name: beginSection
-      dtype: string
-    - name: document
-      dtype: string
-    - name: endSection
-      dtype: string
-    - name: offsetInBeginSection
-      dtype: int64
-    - name: offsetInEndSection
-      dtype: int64
-    - name: text
-      dtype: string
-  - name: asq_challenge
-    dtype: int64
-  - name: folder_name
-    dtype: string
-  - name: concepts
-    sequence: string
-  - name: triples
-    list:
-    - name: o
-      dtype: string
-    - name: p
-      dtype: string
-    - name: s
-      dtype: string
-  - name: id
-    dtype: string
-  splits:
-  - name: factoid
-    num_bytes: 10651614
-    num_examples: 1609
-  - name: yesno
-    num_bytes: 9912166
-    num_examples: 1464
-  - name: summary
-    num_bytes: 8033411
-    num_examples: 1283
-  - name: list
-    num_bytes: 7576487
-    num_examples: 1048
-  download_size: 10986092
-  dataset_size: 36173678
-configs:
-- config_name: default
-  data_files:
-  - split: factoid
-    path: data/factoid-*
-  - split: yesno
-    path: data/yesno-*
-  - split: summary
-    path: data/summary-*
-  - split: list
-    path: data/list-*
+license: other
+license_name: bioasq-research-license
+license_link: https://bioasq.org/participate
+task_categories:
+- question-answering
+- summarization
+language:
+- en
+tags:
+- biomedical
+- scientific-qa
+- biology
+- medicine
+- pubmed
+size_categories:
+- 1K<n<10K
 ---
+
+# BioASQ - All Question Types
+
+A comprehensive dataset containing all question types from the BioASQ challenge, organized by question type as separate splits.
+
+## Dataset Description
+
+This dataset contains **5,404 biomedical questions** from the BioASQ challenge, distributed across four question types:
+
+- **factoid** (1,609 samples): Questions with short factual answers
+- **yesno** (1,464 samples): Yes/No questions
+- **summary** (1,283 samples): Questions requiring summarization
+- **list** (1,048 samples): Questions with list-based answers
+
+Each question type is provided as a separate split for convenient filtering and evaluation.
+
+## Source and Attribution
+
+### Original Dataset
+
+This dataset is derived from the **BioASQ Challenge** data. BioASQ is a series of challenges on large-scale biomedical semantic indexing and question answering.
+
+**IMPORTANT**: To use BioASQ data, you must:
+1. Register at: https://bioasq.org/
+2. Review and comply with BioASQ terms of use
+3. Cite the BioASQ papers (see below)
+4. Acknowledge the BioASQ dataset in any publications
+
+### Citations
+
+If you use this dataset, please cite the following papers:
+
+**Primary BioASQ Paper**:
+```bibtex
+@article{tsatsaronis2015bioasq,
+  title={An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition},
+  author={Tsatsaronis, George and Balikas, Georgios and Malakasiotis, Prodromos and Partalas, Ioannis and Zschunke, Matthias and Alvers, Michael R and Weissenborn, Dirk and Krithara, Anastasia and Petridis, Sergios and Polychronopoulos, Dimitris and others},
+  journal={BMC bioinformatics},
+  volume={16},
+  number={1},
+  pages={1--28},
+  year={2015},
+  publisher={BioMed Central}
+}
+```
+
+**If using this organized version**:
+```bibtex
+@misc{bioasq_all_types,
+  title={BioASQ All Question Types Dataset},
+  author={[Your Name]},
+  year={2026},
+  note={Reorganized version of BioASQ challenge data with question types as splits},
+  url={https://huggingface.co/datasets/jmhb/BioASQ}
+}
+```
+
+**PaperSearchQA** (if used in context of this project):
+```bibtex
+@inproceedings{papersearchqa2026,
+  title={PaperSearchQA: A Large-Scale Dataset for Question Answering over Biomedical Literature},
+  author={[Authors to be added]},
+  booktitle={Proceedings of the 2026 Conference of the European Chapter of the Association for Computational Linguistics (EACL)},
+  year={2026},
+  url={https://jmhb0.github.io/PaperSearchQA}
+}
+```
+
+## License and Terms of Use
+
+### BioASQ License
+
+The original BioASQ data is available for **research and educational purposes** under specific terms:
+
+- **Non-commercial use**: Freely available for academic research and education
+- **Commercial use**: Requires written permission from BioASQ organizers
+- **Attribution**: Must cite BioASQ papers and acknowledge the dataset
+- **Registration**: Users must register at https://bioasq.org/
+
+For full license terms, see: https://bioasq.org/participate
+
+### This Dataset
+
+This reorganized version is provided **AS-IS** for research purposes and is subject to the original BioASQ terms. The reorganization (splitting by question type) is released under **CC BY 4.0**, but the underlying data remains under BioASQ terms.
+
+## Dataset Structure
+
+### Splits
+
+The dataset has **four splits**, one for each question type:
+
+| Split | Samples | Description |
+|-------|---------|-------------|
+| `factoid` | 1,609 | Questions with short factual answers (e.g., "What is the function of protein X?") |
+| `yesno` | 1,464 | Yes/No questions (e.g., "Is aspirin effective for headaches?") |
+| `summary` | 1,283 | Questions requiring summarization (e.g., "Describe the role of...") |
+| `list` | 1,048 | Questions with list-based answers (e.g., "List all known variants of...") |
+
+### Fields
+
+Each sample contains the following fields:
+
+```python
+{
+    'id': str,                    # Unique question ID
+    'type': str,                  # Question type ('factoid', 'yesno', 'summary', or 'list')
+    'question': str,              # The question text
+    'answer': list or str,        # Answer(s) - format varies by type
+    'ideal_answer': str or list,  # Detailed/ideal answer
+    'documents': list,            # Relevant PubMed document IDs (URLs)
+    'snippets': list,             # Relevant text snippets from documents
+    'concepts': list,             # Medical concepts mentioned
+    'triples': list,              # Knowledge graph triples (if available)
+    'asq_challenge': str,         # BioASQ challenge identifier
+    'folder_name': str,           # Source folder
+}
+```
+
+### Answer Formats by Type
+
+- **factoid**: `answer` is a list of short text answers
+- **yesno**: `answer` is "yes" or "no"
+- **summary**: `answer` is typically empty; use `ideal_answer` for summary text
+- **list**: `answer` is a list of items
+
+## Usage
+
+### Load All Splits
+
+```python
+from datasets import load_dataset
+
+# Load entire dataset
+dataset = load_dataset("jmhb/BioASQ_all_types")
+
+print(dataset.keys())
+# dict_keys(['factoid', 'yesno', 'summary', 'list'])
+
+# Access specific split
+factoid_questions = dataset['factoid']
+print(f"Factoid questions: {len(factoid_questions)}")
+```
+
+### Load Specific Split
+
+```python
+# Load only factoid questions
+factoid_data = load_dataset("jmhb/BioASQ_all_types", split="factoid")
+
+# Example question
+sample = factoid_data[0]
+print(f"Question: {sample['question']}")
+print(f"Answer: {sample['answer']}")
+print(f"Documents: {sample['documents'][:2]}...")
+```
+
+### Filter by Type
+
+```python
+# Get all yes/no questions
+yesno_data = load_dataset("jmhb/BioASQ_all_types", split="yesno")
+
+# Count yes vs no answers
+yes_count = sum(1 for ex in yesno_data if ex['answer'] == 'yes')
+no_count = sum(1 for ex in yesno_data if ex['answer'] == 'no')
+print(f"Yes: {yes_count}, No: {no_count}")
+```
+
+### Iterate Over All Types
+
+```python
+dataset = load_dataset("jmhb/BioASQ_all_types")
+
+for question_type, split_data in dataset.items():
+    print(f"\n{question_type.upper()} Questions:")
+    print(f"  Total: {len(split_data)}")
+
+    # Show first example
+    example = split_data[0]
+    print(f"  Sample: {example['question'][:100]}...")
+```
+
+## Data Statistics
+
+### Overall Statistics
+
+- **Total Questions**: 5,404
+- **Question Types**: 4 (factoid, yesno, summary, list)
+- **Source**: BioASQ challenges 1-9
+- **Domain**: Biomedical and life sciences
+- **Language**: English
+
+### Question Type Distribution
+
+```
+factoid:  29.8% (1,609 questions)
+yesno:    27.1% (1,464 questions)
+summary:  23.7% (1,283 questions)
+list:     19.4% (1,048 questions)
+```
+
+### Sample Questions by Type
+
+**Factoid**:
+- "What is the genetic basis of Huntington's disease?"
+- "Which protein is encoded by the BRCA1 gene?"
+
+**Yes/No**:
+- "Is the protein Papilin secreted?"
+- "Does metformin interfere with vitamin B12 absorption?"
+
+**Summary**:
+- "Describe the role of the immune system in cancer development."
+- "What is known about the association between coffee consumption and health?"
+
+**List**:
+- "List symptoms of Alzheimer's disease."
+- "Which genes are associated with autosomal dominant Alzheimer's disease?"
+
+## Limitations and Considerations
+
+1. **Question Distribution**: Not uniformly distributed across types
+2. **Answer Variability**: Answer formats vary significantly by type
+3. **Domain Specificity**: Highly specialized biomedical knowledge required
+4. **Evaluation Complexity**: Different metrics needed for different question types
+5. **Document Access**: Referenced PubMed documents may require separate retrieval
+6. **Knowledge Cutoff**: Questions are based on medical knowledge available up to the challenge date
+
+## Evaluation
+
+Different question types require different evaluation metrics:
+
+- **Factoid**: Exact Match (EM), F1 score
+- **Yes/No**: Accuracy, F1 score
+- **Summary**: ROUGE, BERTScore, human evaluation
+- **List**: F1 score, Partial Match
+
+See the [BioASQ evaluation tools](http://participants-area.bioasq.org/general_information/Task6b/) for official evaluation scripts.
+
+## Related Resources
+
+### BioASQ
+- **Website**: https://bioasq.org/
+- **Participate**: https://bioasq.org/participate
+- **Papers**: https://bioasq.org/publications
+
+### PubMed Corpus
+- **Full PubMed Corpus**: https://huggingface.co/datasets/jmhb/pubmed_bioasq_2022
+- **NLM PubMed**: https://pubmed.ncbi.nlm.nih.gov/
+
+### PaperSearchQA Project
+- **Website**: https://jmhb0.github.io/PaperSearchQA
+- **GitHub**: https://github.com/jmhb0/PaperSearchQA
+- **Main Dataset**: https://huggingface.co/datasets/jmhb/PaperSearchQA
+- **Collection**: https://huggingface.co/collections/jmhb/papersearchqa
+
+## Contact and Support
+
+For questions about:
+- **Original BioASQ data**: Contact BioASQ organizers at https://bioasq.org/contact
+- **This dataset organization**: Open an issue on the PaperSearchQA GitHub
+- **PaperSearchQA project**: Visit https://jmhb0.github.io/PaperSearchQA
+
+## Acknowledgments
+
+- **BioASQ Organizers**: For creating and maintaining this valuable resource
+- **PubMed/NCBI**: For the underlying biomedical literature
+- **Challenge Participants**: For advancing biomedical QA research
+- **Funding Agencies**: Supporting the BioASQ challenges
+
+## Version History
+
+- **v1.0** (2026-01): Initial release with all question types as separate splits
+  - 5,404 questions across 4 types
+  - Organized from BioASQ challenges 1-9
+  - Split by question type for convenient access