First updated version of datasheet

datasheet.md

@@ -1,6 +1,6 @@
 # GerMS-AT Dataset Datasheet
 
-This file contains information about the GerMS-AT Dataset structured according to 
+This file contains information about the GerMS-AT Dataset partially structured according to 
 ["T. Gebru et.al. (2021): Datasheets for Datasets"](https://arxiv.org/abs/1803.09010)
 
 If there is a need for additional information or clarification, please feel free to contact any
@@ -8,35 +8,35 @@ of the the maintainers of this repository.
 
 ### Motivation
 
-* Purpose of dataset creation: 
+* Purpose of dataset creation: the corpus was created in the context of [project FemDwell](https://www.ofai.at/projects/femdwell)
+  in order to build a machine-learning based assistant to help human content moderators 
+  identify individual forum posts which may contain sexist or misogynist comments or whole fora, where an unusual large number of such posts
+  were created more easily. 
 * Dataset creators: 
+  * [Austrian Research Institue for Artificial Intelligence](https://ww.ofai.at)
+  * [Standard Verlagsgesellschaft](https://about.derstandard.at/impressum/)
 * Funding of dataset creation: 
+  * The project was sponsored by [Vienna Business Agency](https://wirtschaftsagentur.at/)
 
 ### Composition
 
-* Instance representation: 
-* Number of instances:
-* Completeness/sampling: 
+* Instance representation: JSON dictionary
+* Number of instances: 7984
 * Data per instance: 
+  * `id`: a unique ID
+  * `text`: the text of the forum comment posted, with user names and real person names replaced by the string "{USER}" and web addresses, email address and
+    the like replaced by the string "{URL}"
 * Label/target per instance:
-* Missing per-instance information:
-* Relationships between instances:
+  * for each instance there is a dictionary which contains the label assigned by each of the annotators who were presented the comment. Annotators are 
+    represented by anonymized annotator ids.
+  * the label assigned by each annotator is one of "0" (no sexism/misogyny present), "1" (mild), "2" (present), "3" (severe), "4" (extreme). 
 * Recommended data splits: 
-* Errors, sources of noise, redundancies: 
-* Self contained: 
-* Presence of confidential information: 
-* Presence of offensive or otherwise problematic data: 
-* Identifyability of subpopulations: 
-* Identifyability of individuals: 
-* Presence of sensitive information: 
-
-### Collection Process
-
-* Data associated with each instance:
-* Data collection procedure:
-* Sampling strategy:
-* People involved in the data collection process:
-* Collection period:
-* Ethical review processes:
-* Direct/indirect data collection:
+  * the data is made available as a train and a test file, with the same split that was used in the [GermEval2024 GerMS-Detect](https://ofai.github.io/GermEval2024-GerMS/) shared task
+* Presence of confidential information: there is no confidential information in the dataset
+* Presence of offensive or otherwise problematic data: comments will contain sexist and misogynist remarks and may also contain other forms 
+  of offensive or toxic remarks. 
+* Identifyability of subpopulations: comments have been made by readers of the online news web site
+* Identifyability of individuals: all information that could identify a user or person has been removed or replaced with placeholders
+* Presence of sensitive information: none
+