Update README.md

README.md

@@ -3,10 +3,10 @@ language:
 - da
 license: cc-by-4.0
 size_categories:
-- 10K<n<100K
+- 1K<n<10K
 task_categories:
 - image-to-text
-pretty_name: Danish Handwritten Text
+pretty_name: Danish Handwritten Text 1841-1939
 tags:
 - OCR
 - HTR
@@ -39,18 +39,11 @@ configs:
 
 ### Dataset Summary
 
-The Danish htr dataset is a Danish-language dataset containing around 4000 pages of proof-read handwritten text.
+The Danish handwriting dataset is a Danish-language dataset containing around 3200 pages of proof-read handwritten text.
 
-...written by journalists at CNN and the Daily Mail.
 ...its intended use and the supported tasks. Give an overview of how and why the dataset was created.
 ...The summary shoul describe the domain, topic, or genre covered.
 
-### Supported Tasks and Leaderboards
-
-For each of the tasks tagged for this dataset, give a brief description of the tag, metrics, and suggested models (with a link to their HuggingFace implementation if available). Give a similar description of tasks that were not covered by the structured tag set (repace the `task-category-tag` with an appropriate `other:other-task-name`).
-
-- `task-category-tag`: The dataset can be used to train a model for [TASK NAME], which consists in [TASK DESCRIPTION]. Success on this task is typically measured by achieving a *high/low* [metric name](https://huggingface.co/metrics/metric_name). The ([model name](https://huggingface.co/model_name) or [model class](https://huggingface.co/transformers/model_doc/model_class.html)) model currently achieves the following score. *[IF A LEADERBOARD IS AVAILABLE]:* This task has an active leaderboard which can be found at [leaderboard url]() and ranks models based on [metric name](https://huggingface.co/metrics/metric_name) while also reporting [other metric name](https://huggingface.co/metrics/other_metric_name).
-
 ### Languages
 
 All the text is in Danish. The BCP-47 code for Danish is da.
@@ -59,7 +52,9 @@ All the text is in Danish. The BCP-47 code for Danish is da.
 
 ### Data Instances
 
-Each data instance describes and represents a transcribed physical page contains a scanned image of the of original page, it's date and sequence within a given book or protocol, 
+Each data instance describes and represents a single scanned and transcribed physical page with handwritten text.
+
+contains a scanned image of the of original page, it's date and sequence within a given book or protocol, 
 
 Provide any additional information that is not covered in the other sections about the data here. In particular describe any relationships between data points and if these relationships are made explicit.
 
@@ -68,10 +63,8 @@ Provide any additional information that is not covered in the other sections abo
 List and describe the fields present in the dataset. Mention their data type, and whether they are used as input or output in any of the tasks the dataset currently supports. If the data has span indices, describe their attributes, such as whether they are at the character level or word level, whether they are contiguous or not, etc. If the datasets contains example IDs, state whether they have an inherent meaning, such as a mapping to other datasets or pointing to relationships between data points.
 
 - `image`: a scanned image of the physical page
-- `authority`: a string identifying the institution that is responsible for the page, the transcription and the proof-reading
 - `docId`: an integer representing the unique id of each page
 - `docTitle`: a string containing the title of the book/protocol that the page belongs to
-- `scriptType`: a string classifying the type of text
 - `sequence`: description of `example_field`
 - `alto`: an xml-encoded string containing layout and content information of the physical page, stored in [ALTO XML, version 4.2](https://www.loc.gov/standards/alto/v4/alto-4-2.xsd)
 - `page`: an xml-encoded string containing layout and content information of the physical page, stored in [PAGE XML, version 2013-07-15](https://www.primaresearch.org/schema/PAGE/gts/pagecontent/2013-07-15/pagecontent.xsd)
@@ -125,17 +118,13 @@ If annotations were collected for the source data (such as class labels or synta
 
 Describe the people or systems who originally created the annotations and their selection criteria if applicable.
 
-If available, include self-reported demographic or identity information for the annotators, but avoid inferring this information. Instead state that this information is unknown. See [Larson 2017](https://www.aclweb.org/anthology/W17-1601.pdf) for using identity categories as a variables, particularly gender.
-
 Describe the conditions under which the data was annotated (for example, if the annotators were crowdworkers, state what platform was used, or if the data was found, what website the data was found on). If compensation was provided, include that information here.
 
 ### Personal and Sensitive Information
 
 No efforts were made to anonymize the data.
 
-State whether the dataset uses identity categories and, if so, how the information is used. Describe where this information comes from (i.e. self-reporting, collecting from profiles, inferring, etc.). See [Larson 2017](https://www.aclweb.org/anthology/W17-1601.pdf) for using identity categories as a variables, particularly gender. State whether the data is linked to individuals and whether those individuals can be identified in the dataset, either directly or indirectly (i.e., in combination with other data).
-
-State whether the dataset contains other data that might be considered sensitive (e.g., data that reveals racial or ethnic origins, sexual orientations, religious beliefs, political opinions or union memberships, or locations; financial or health data; biometric or genetic data; forms of government identification, such as social security numbers; criminal history).  
+The dataset contains data that might be considered sensitive (e.g., data that reveals racial or ethnic origins, sexual orientations, religious beliefs, political opinions or union memberships, or locations; financial or health data; biometric or genetic data; forms of government identification, such as social security numbers; criminal history).  
 
 
 ## Considerations for Using the Data