added how to contribute and small changes

README.md

@@ -20,6 +20,7 @@ size_categories:
   - [Dataset Summary](#dataset-summary)
   - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
   - [How to use it](#how-to-use-it)
+  - [How to contribute](#how-to-contribute)
 - [Dataset Structure](#dataset-structure)
   - [Data Instances](#data-instances)
   - [Data Fields](#data-fields)
@@ -51,8 +52,8 @@ size_categories:
 |v0.1| Release of the Fondant-cc-25m dataset
 
 ### Dataset Summary
-Fondant-cc-25m contains 25 million image URLs available under different [Creative Commons](https://creativecommons.org/) 
-licenses collected from the [Common Crawl web corpus](https://commoncrawl.org/). 
+Fondant-cc-25m contains 25 million image URLs with their respective [Creative Commons](https://creativecommons.org/) 
+license information collected from the [Common Crawl web corpus](https://commoncrawl.org/). 
 The dataset was created using [Fondant](https://fondant.ai), an open source framework that aims to simplify and speed up 
 large-scale data processing by making self-contained pipeline components reusable across pipelines, infrastructures and shareable within the community.
 
@@ -62,7 +63,7 @@ This dataset can be used for training or fine-tuning image generation or compute
 
 ### How to use it
 
-We have prepared a sample fondant pipeline that limits the dataset to PNG files and downloads the images.
+We have prepared a sample Fondant pipeline for downloading the dataset or part of it.
 
 To execute the pipeline locally, you must have [docker compose](https://docs.docker.com/compose/),
 [Python](https://python.org) >=3.8 and [Git](https://git-scm.com/) installed on your system.
@@ -96,6 +97,24 @@ image data and file names, TODO XXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 
 To download the full dataset, TODO XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
 
+### How to contribute
+If you want to contribute to the dataset, the best way is to help us develop pipeline components for further processing. Components
+we are currently looking to add are the following ([GitHub issues](https://github.com/ml6team/fondant/issues?q=is%3Aissue+is%3Aopen+label%3A%22Component+Contribution%22)):
+- Image-based deduplication
+- Visual quality / aesthetic quality estimation
+- Automatic captioning
+- Not safe for work (NSFW) content detection
+- Watermark detection
+- Face detection
+- Personal Identifiable Information (PII) detection
+- Text detection
+- AI generated image detection
+- CLIP embedding generation
+- Image-text CLIP similarity
+- ...
+We are also looking for core framework contributors and users who are willing to give feedback on usability and suggest potential improvements
+
+
 ## Dataset Structure
 ### Data Instances
 Each data instance corresponds to one image. The URL of the image is in the `image_url` feature, and other features (`alt_text`, `webpage_url`, etc) provide some 
@@ -128,7 +147,9 @@ fondant-cc-25m is built from CommonCrawl dumps. These dumps are constructed from
 Permissive licenses have minimal restrictions on how the image can be copied, modified, and redistributed. 
 The full list of licenses can be found [here](https://creativecommons.org/about/cclicenses/).
 We examined HTML tags of the webpages for the presence of Creative Commons license URLs. A webpage was marked permissive only when a license URL was found in 
-its footer, aside or sidebar. This was the case in around 0.164% of images.
+its footer, aside or sidebar. This was the case only in around 0.164% of images which suggests that image generation models trained on a random sample from
+the public internet may be trained on up to 99.836% images that may be copyrighted.
+
 Subsequently, all the image URLs present on the web page were collected together with the license information.
 A manual test of 1032 randomly sampled images showed an accuracy of 96.32% in which case the image was actually released under a Creative Commons license.
 False positives could be due to parsing errors but also incorrect attributions: images indicated by the publisher to be CC which are not.
@@ -158,8 +179,8 @@ As toxic or biased data is prevalent on the internet, it is possible that our da
 
 ### Dataset Curators
 1. Sharon Grundmann, ML6, sharon.grundmann@ml6.eu
-2. Robbe Sneyders, ML6, robbe.sneyders@ml6.eu
-3. Matthias Richter, ML6, matthias.richter@ml6.eu
+2. Matthias Richter, ML6, matthias.richter@ml6.eu
+3. Robbe Sneyders, ML6, robbe.sneyders@ml6.eu
 
 ### Licensing Information
 Fondant-cc-25m is a collection of images with various Creative Commons and other public licenses. Any use of all or part of the images gathered in Fondant-cc-25m