Datasets:

DoubleML
/

multimodal_confounding

@@ -93,94 +93,33 @@ The dataset contains the following columns:
 ### Dataset Sources
-The dataset is based on the three
 ## Uses
 The dataset should as a benchmark to compare different causal inference methods for observational data under multimodal confounding.
-### Direct Use
-<!-- This section describes suitable use cases for the dataset. -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-[More Information Needed]
 ## Dataset Structure
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 [More Information Needed]
-## Dataset Creation
-### Curation Rationale
-<!-- Motivation for the creation of this dataset. -->
-[More Information Needed]
-### Source Data
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-[More Information Needed]
-#### Who are the source data producers?
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-[More Information Needed]
-### Annotations [optional]
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-#### Annotation process
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-[More Information Needed]
-#### Who are the annotators?
-<!-- This section describes the people or systems who created the annotations. -->
-[More Information Needed]
-#### Personal and Sensitive Information
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
 ```
 @article{klaassen2024doublemldeep,
@@ -191,24 +130,50 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 }
 ```
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Dataset Card Authors [optional]
-[More Information Needed]
-## Dataset Card Contact
-[More Information Needed]

 ### Dataset Sources
+The dataset is based on the three commonly used datasets:
+ - [Diamonds dataset](https://www.kaggle.com/datasets/shivam2503/diamonds)
+ - [IMDB dataset](https://huggingface.co/datasets/imdb)
+ - [CIFAR-10 dataset](https://www.cs.toronto.edu/~kriz/cifar.html)
+The original citations can be found below.
 ## Uses
 The dataset should as a benchmark to compare different causal inference methods for observational data under multimodal confounding.
 ## Dataset Structure
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 [More Information Needed]
+## Limitations
+As the confounding is generated via original labels, completely removing the confounding might not be possible.
+## Citation Information
+### Dataset Citation
+If you use the dataset please cite this article:
 ```
 @article{klaassen2024doublemldeep,
 }
 ```
+### Dataset Sources
+The three original datasets can be cited via
+Diamonds dataset:
+```
+@Book{ggplot2_book,
+  author = {Hadley Wickham},
+  title = {ggplot2: Elegant Graphics for Data Analysis},
+  publisher = {Springer-Verlag New York},
+  year = {2016},
+  isbn = {978-3-319-24277-4},
+  url = {https://ggplot2.tidyverse.org},
+}
+```
+IMDB dataset:
+```
+@InProceedings{maas-EtAl:2011:ACL-HLT2011,
+  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
+  title     = {Learning Word Vectors for Sentiment Analysis},
+  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
+  month     = {June},
+  year      = {2011},
+  address   = {Portland, Oregon, USA},
+  publisher = {Association for Computational Linguistics},
+  pages     = {142--150},
+  url       = {http://www.aclweb.org/anthology/P11-1015}
+}
+```
+CIFAR-10 dataset:
+```
+@TECHREPORT{Krizhevsky09learningmultiple,
+    author = {Alex Krizhevsky},
+    title = {Learning multiple layers of features from tiny images},
+    institution = {},
+    year = {2009}
+}
+```
+## Dataset Card Authors
+Sven Klaassen