Include additional details (motivation, citation, provenance etc.)

README.md

@@ -252,12 +252,14 @@ An example of the `Aya Evaluation Suite` looks as follows:
 
 ## Statistics
 
+The toggled table below lists the breakdown of languages in each subset.
+
 ### Languages
 
 <details>
 <summary> <b>aya-human-annotated</b> </summary>
 
-  | ISO Code | Language | Resourcedness |
+  | ISO Code | Language | Resources |
   |----------|----------|---------------|
   | `tel` | Telugu | Low |
   | `yor` | Yorùbá | Low |
@@ -273,7 +275,7 @@ An example of the `Aya Evaluation Suite` looks as follows:
 <details>
 <summary> <b>dolly-machine-translated</b> </summary>
   
-  | ISO Code | Language | Resourcedness |
+  | ISO Code | Language | Resources |
   |----------|----------|-----------|
   |	`ace`  |	Achinese	|	Low	|
   |	`afr`  |	Afrikaans	|	Mid	|
@@ -381,7 +383,7 @@ An example of the `Aya Evaluation Suite` looks as follows:
 <details>
 <summary> <b>dolly-human-edited</b> </summary>
   
-  | ISO Code | Language | Resourcedness |
+  | ISO Code | Language | Resources |
   |----------|----------|-----------|
   | `arb` | Arabic | High |
   | `fra` | French | High |
@@ -390,4 +392,53 @@ An example of the `Aya Evaluation Suite` looks as follows:
   | `spa` | Spanish | High |
   | `srp` | Serbian | High |
 
-</details>
+</details>
+
+<br>
+
+# Motivations & Intentions
+
+- **Curation Rationale:** This evaluation suite is tailored to test the generation quality of multilingual models, with the aim of balancing language coverage and human-sourced quality.
+It covers prompts originally written in each language, as well as English-centric translated and manually curated or edited prompts for a linguistically broad but rich testbed.
+The list of languages was established from mT5 and aligned with the annotators’ language list and the NLLB translation model.
+
+---
+
+# Additional Information
+
+## Provenance
+- **Methods Used:** combination of original annotations by volunteers, automatic translation, and post-editing of translations by professional annotators.
+- **Methodology Details:**
+    -  *Source:* Original annotations and translations and post-edits of Dolly
+    - *Platform:* [Aya Annotation Platform](https://aya.for.ai/)
+    - *Dates of Collection:* Jun 2023 - Dec 2023
+
+
+## Dataset Version and Maintenance
+- **Maintenance Status:** Actively Maintained
+- **Version Details:**
+    - *Current version:* 1.0
+    - *Last Update:* 02/2024
+    - *First Release:* 02/2024
+- **Maintenance Plan:** No updates planned.
+
+
+## Authorship
+
+- **Publishing Organization:** [Cohere For AI](https://cohere.com/research)
+- **Industry Type:** Not-for-profit - Tech
+- **Contact Details:** https://aya.for.ai/
+
+
+## Licensing Information
+This dataset can be used for any purpose, whether academic or commercial, under the terms of the [Apache 2.0](https://opensource.org/license/apache-2-0) License.
+
+
+## Citation Information
+```bibtex
+@misc{ayadata2024,
+    title = {Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning},
+    author = {Shivalika Singh, Freddie Vargus, Daniel D'souza, Börje F. Karlsson, Abinaya Mahendiran, Wei-Yin Ko, Herumb Shandilya, Jay Patel, Deividas Mataciunas, Laura O'Mahony, Mike Zhang, Ramith Hettiarachchi, Joseph Wilson, Marina Machado, Luisa Souza Moura, Dominik Krzemiński, Hakimeh Fadaei, Irem Ergün, Ifeoma Okoh, Aisha Alaagib, Oshan Mudannayake, Zaid Alyafeai, Vu Minh Chien, Sebastian Ruder, Surya Guthikonda, Emad A. Alghamdi, Sebastian Gehrmann, Niklas Muennighoff, Max Bartolo, Julia Kreutzer, Ahmet Üstün, Marzieh Fadaee, Sara Hooker},
+    year = 2024,
+}
+```