Cite every source cohort, note LTS4 supervision

DATA.md

@@ -369,26 +369,92 @@ StandardScaler + logistic-regression probe as described above.
   weights.
 - **Hardware timings** are wall-clock measurements on specific GPUs.
 
-## Licence
+## Datasets used
+
+This release is built from seven public cohorts. If you use it, please cite GrapHist **and**
+the source cohort(s) your work touches.
 
-Released `cc-by-nc-sa-4.0`. Derived from public cohorts: BACH/ICIAR 2018, BreakHis, BRACS,
-TCGA-BRCA, PanNuke, NuCLS and
-[SPIDER-breast](https://huggingface.co/datasets/histai/SPIDER-breast), which is
-`cc-by-nc-4.0`, research use only:
+| Cohort | Used for | Source |
+|---|---|---|
+| **TCGA-BRCA** | pre-training (11.1 M graphs), slide-level evaluation, survival | [GDC Data Portal](https://portal.gdc.cancer.gov/) |
+| **BACH** (ICIAR 2018) | slide-level subtyping, homophily | [Grand Challenge](https://iciar2018-challenge.grand-challenge.org/) |
+| **BRACS** | slide-level subtyping, homophily | [bracs.icar.cnr.it](https://www.bracs.icar.cnr.it/) |
+| **BreakHis** | slide-level subtyping, homophily | [P&D Lab, UFPR](https://web.inf.ufpr.br/vri/databases/breast-cancer-histopathological-database-breakhis/) |
+| **NuCLS** | cell-type identification, homophily | [NuCLS](https://sites.google.com/view/nucls/home) |
+| **PanNuke** | cell-type identification, homophily | [TIA Centre, Warwick](https://warwick.ac.uk/fac/sci/dcs/research/tia/data/pannuke/) |
+| **SPIDER-breast** | patch-level subtyping | [histai/SPIDER-breast](https://huggingface.co/datasets/histai/SPIDER-breast) |
+
+<details>
+<summary>BibTeX for the source cohorts</summary>
 
 ```bibtex
+@article{weinstein2013cancer,
+  title={The cancer genome atlas pan-cancer analysis project},
+  author={Weinstein, John N and Collisson, Eric A and Mills, Gordon B and Shaw, Kenna R and
+          Ozenberger, Brad A and Ellrott, Kyle and Shmulevich, Ilya and Sander, Chris and
+          Stuart, Joshua M},
+  journal={Nature Genetics}, volume={45}, number={10}, pages={1113--1120}, year={2013},
+  publisher={Nature Publishing Group}
+}
+
+@article{aresta2019bach,
+  title={{BACH}: Grand challenge on breast cancer histology images},
+  author={Aresta, Guilherme and Ara{\'u}jo, Teresa and Kwok, Scotty and
+          Chennamsetty, Sai Saketh and Safwan, Mohammed and Alex, Varghese and others},
+  journal={Medical Image Analysis}, volume={56}, pages={122--139}, year={2019},
+  publisher={Elsevier}
+}
+
+@article{brancati2022bracs,
+  title={{BRACS}: A Dataset for BReAst Carcinoma Subtyping in {H\&E} Histology Images},
+  author={Brancati, Nadia and Anniciello, Anna Maria and Pati, Pushpak and Riccio, Daniel and
+          Scognamiglio, Giosu{\`e} and Jaume, Guillaume and De Pietro, Giuseppe and
+          Di Bonito, Maurizio and Foncubierta, Antonio and Botti, Gerardo and others},
+  journal={Database}, volume={2022}, pages={baac093}, year={2022},
+  publisher={Oxford University Press UK}
+}
+
+@article{spanhol2015dataset,
+  title={A dataset for breast cancer histopathological image classification},
+  author={Spanhol, Fabio A and Oliveira, Luiz S and Petitjean, Caroline and Heutte, Laurent},
+  journal={IEEE Transactions on Biomedical Engineering}, volume={63}, number={7},
+  pages={1455--1462}, year={2015}, publisher={IEEE}
+}
+
+@article{amgad2022nucls,
+  title={{NuCLS}: A scalable crowdsourcing approach and dataset for nucleus classification and
+         segmentation in breast cancer},
+  author={Amgad, Mohamed and Atteya, Lamees A and Hussein, Hagar and Mohammed, Kareem Hosny and
+          Hafiz, Ehab and Elsebaie, Maha AT and Alhusseiny, Ahmed M and
+          AlMoslemany, Mohamed Atef and Elmatboly, Abdelmagid M and Pappalardo, Philip A and others},
+  journal={GigaScience}, volume={11}, pages={giac037}, year={2022},
+  publisher={Oxford University Press}
+}
+
+@article{gamper2020pannuke,
+  title={{PanNuke} dataset extension, insights and baselines},
+  author={Gamper, Jevgenij and Koohbanani, Navid Alemi and Benes, Ksenija and Graham, Simon and
+          Jahanifar, Mostafa and Khurram, Syed Ali and Azam, Ayesha and Hewitt, Katherine and
+          Rajpoot, Nasir},
+  journal={arXiv preprint arXiv:2003.10778}, year={2020}
+}
+
 @article{nechaev2025spider,
-  title   = {SPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models},
-  author  = {Nechaev, Dmitry and Pchelnikov, Alexey and Ivanova, Ekaterina},
-  year    = {2025},
-  eprint  = {2503.02876},
-  archivePrefix = {arXiv}
+  title={{SPIDER}: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models},
+  author={Nechaev, Dmitry and Pchelnikov, Alexey and Ivanova, Ekaterina},
+  year={2025}, eprint={2503.02876}, archivePrefix={arXiv}, primaryClass={cs.CV}
 }
 ```
+</details>
+
+## Licence
+
+Released `cc-by-nc-sa-4.0`. SPIDER-breast is `cc-by-nc-4.0`, research use only, and those
+terms travel with the derived graphs:
 
 `labels/tcga_brca_clinical.tsv` is the open-access GDC clinical export, redistributed under
 TCGA's open-access terms. The source cohorts keep their own licences, so cite their papers
 alongside GrapHist.
 
-This work was done by **Mahbod Tajdini** and **Tomás Gadea Alcaide** at
+This work was done by **Mahbod Tajdini** and **Tomás Gadea Alcaide**, supervised by members of
 [LTS4, EPFL](https://www.epfl.ch/labs/lts4/).