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---

dataset_info:
- config_name: animals
  features:
  - name: Filename
    dtype: string
  - name: full_species_name_DE
    dtype: string
  - name: full_species_name_EN
    dtype: string
  - name: family_name_DE
    dtype: string
  - name: family_name_EN
    dtype: string
  - name: acceptable_generalization
    dtype: string
  - name: Alias
    dtype: string
  - name: Remarks
    dtype: string
  - name: scientific_name
    dtype: string
  - name: scientific_family_name
    dtype: string
  - name: common_name_DE
    dtype: string
  - name: common_name_EN
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: subcategory
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 33800694.0
    num_examples: 347
  download_size: 33755238
  dataset_size: 33800694.0
- config_name: cars
  features:
  - name: Filename
    dtype: string
  - name: company
    dtype: string
  - name: model_name
    dtype: string
  - name: category_EN
    dtype: string
  - name: category_DE
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 31270976.0
    num_examples: 345
  download_size: 31240949
  dataset_size: 31270976.0
- config_name: celebrity
  features:
  - name: Filename
    dtype: string
  - name: first_name
    dtype: string
  - name: last_name
    dtype: string
  - name: alternative_name
    dtype: string
  - name: name
    dtype: string
  - name: subcategory
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: full_name
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 22656597.0
    num_examples: 674
  download_size: 22591665
  dataset_size: 22656597.0
- config_name: plants
  features:
  - name: alternative_name_DE
    dtype: string
  - name: Alias
    dtype: string
  - name: scientific_name
    dtype: string
  - name: common_name_EN
    dtype: string
  - name: common_name_DE
    dtype: string
  - name: Filename
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 16315782.0
    num_examples: 185
  download_size: 16313529
  dataset_size: 16315782.0
- config_name: products
  features:
  - name: Filename
    dtype: string
  - name: company_name
    dtype: string
  - name: product_name
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 12072018.0
    num_examples: 194
  download_size: 11900512
  dataset_size: 12072018.0
- config_name: sights
  features:
  - name: Filename
    dtype: string
  - name: name_DE
    dtype: string
  - name: name_EN
    dtype: string
  - name: location_name_DE
    dtype: string
  - name: location_name_EN
    dtype: string
  - name: language
    dtype: string
  - name: category
    dtype: string
  - name: self_collected
    dtype: string
  - name: full_path
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: test
    num_bytes: 12606317.0
    num_examples: 92
  download_size: 12606757
  dataset_size: 12606317.0
configs:
- config_name: animals
  data_files:
  - split: test
    path: animals/full-*
- config_name: cars
  data_files:
  - split: test
    path: cars/full-*
- config_name: celebrity
  data_files:
  - split: test
    path: celebrity/full-*
- config_name: plants
  data_files:
  - split: test
    path: plants/full-*
- config_name: products
  data_files:
  - split: test
    path: products/full-*
- config_name: sights
  data_files:
  - split: test
    path: sights/full-*
task_categories:
- visual-question-answering
language:
- en
- de
tags:
- factual-knowledge
- multi-lingual
- biology
- celebrities
- sights
- cars
- supermarket
- products
- ocr
size_categories:
- n<1K
---

# Dataset Card for Dataset Name

<!-- Provide a quick summary of the dataset. -->

This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->



- **Curated by:** Institute for Information Systems (iisys) of Hof University of Applied Sciences, Germany
- **Language(s) (NLP):** German (de), English (en)
- **License:** Images are owned by their creators, the collection of data is distributed under cc-by-nc 4.0 license. The data is provided as-is without any warranty or guarantee of fitness for a particular purpose. Please refer to the license file in the repository for more details.

### Dataset Sources 
- Images are collected from the Internet with a focus on images NOT featured on Wikipedia, because we expected those to be less likely to be part of existing training datasets. Images are filtered and downscaled to be within 400x300 as a minimum (except Celeb1k) and 1280x1024 as a maximum.

- **Paper :** currently under review for a scientific AI conference. Will be published in first half of 2025.

## Uses
Should be used to evaluate factual knowledge of Vision Language Models (VLMs) with a focus on image contents from Germany in contrast to internationally well-known image contents from English-speaking countries and others. 

### Out-of-Scope Use
Commercial use or any use that may lead to commercial gain is not permitted without explicit permission from the copyright holders.

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->


## Dataset Structure

The dataset consists of six parquet files, one for each category of images, namely animals, plants, celebrities, sights, cars and products from the supermarket (mainly food). Each file contains images with strong association to Germany and semantically similar counterparts from other countries, especially English-speaking ones. The names of the objects that should be identified from the images are given in English and German language. 
 

## Dataset Creation and Curation Rationale
The German-related images are self-collected from various sources in the internet, excluding Wikipedia. Images with English- or international focus are partly self-collected, partly filtered and reused contents from existing datasets like Stanford Cars (https://huggingface.co/datasets/tanganke/stanford_cars), Oxford Flowers (https://huggingface.co/datasets/dpdl-benchmark/oxford_flowers102) and Celeb1k (https://huggingface.co/datasets/tonyassi/celebrity-1000). German names are added by iisys.

#### Annotation process

Annotation was done manually by using Wikipedia and other online resources for verification of the names and Google image search for visual confirmation of the image names in case of doubt. The focus was on asking for common names as used by everyday people, not specialists in the respective field (e.g., not asking for the scientific name of a plant). For animals and plants some common names are rather coarse and refer to the animal or plant family rather than the species, because we expect most people not to know the exact species name and therefore getting the exact right answer would be less helpful than a litte coarser one. However, we accepted the exact species name in latin as a correct answer if the VLM gave this as an answer, but noted it as a deficit in German language if it could not give the German (or English) common name in addition. 

#### Who are the annotators?

René Peinl and Vincent Tischler, iisys, Hof University of Applied Sciences, Hof, Germany


## Bias, Risks, and Limitations

The selection of images was biased towards the background knowledge of the annotators and there is no guarantee that it is objectively representative for the respective categories.


## Citation

[coming soon]

**BibTeX:**

[coming soon]

## Dataset Card Authors

René Peinl 

## Dataset Card Contact

René Peinl