Datasets:

ESVdatalabb
/

myndighetscrawl

@@ -9,6 +9,11 @@ tags:
 - internet-archive
 size_categories:
 - 1M<n<10M
 ---
 # Myndighetscrawl
@@ -23,6 +28,7 @@ Unfortunately, their decentralised nature and the lack of best open data practic
 Some agencies consistently publish their reports on a specific "Publications" page, but many do not. Some add metadata to the PDF files, many do not. In practice, the work of automatically fetching documents from hundreds of websites is too much and most organisations do not keep their old reports online.
 These publications are also archived by three organisations:
 - the Swedish National Library (*Kungliga biblioteket*), still partly in paper form
 - the Swedish National Archives (*Riksarkivet*), still partly in paper form and often with a delay of several years
 - the Government Offices of Sweden (*Regeringskansliet*) in their digital registry (*diariesystem*) for those documents sent to the government
@@ -44,11 +50,13 @@ The data made available is the raw list of links provided by the services.
 The data is in [archive_org.parquet](./archive_org.parquet).
 The Internet Archive provides:
 - *timestamp*, a timestamp for the time the document was archived
 - *original*, the URL at which the document was found
 - *length*, the size in bytes of the archived file
 The file also contains two fields generated by the data:
 - *archive*, the URL to access the file on the Wayback Machine, made with *timestamp* and *original*
 - *filename*, the filename extracted from the URL if possible
@@ -57,6 +65,7 @@ The file also contains two fields generated by the data:
 The data is in [common_crawl.parquet](./common_crawl.parquet).
 The Common Crawl Index API provides:
 - *Domain*, the base domain at which the file was fetched
 - *Period*, a monthly or yearly reference to when it was fetched
 - *URL*, the URL at which the document was found
@@ -64,10 +73,11 @@ The Common Crawl Index API provides:
 ## What's next?
 The two sources contain respectively 2.16 and 1.25 million rows. The next steps are to:
 - identify the documents that hold a high value, like reports
 - filter out duplicates
 - determine important metadata about the documents such as their title, register number and potentially other connections with important processes (government missions...)
 This can't only be done by looking at the URL of the document, they need to be downloaded and analysed. A script to do it using ML and LLM is in preparation.
-If you want to try and analyse the documents in this dataset, don't hesitate to reach out so we can join forces!

 - internet-archive
 size_categories:
 - 1M<n<10M
+configs:
+- config_name: archive.org
+  data_files: "archive_org.parquet"
+- config_name: commoncrawl.org
+  data_files: "common_crawl.parquet"
 ---
 # Myndighetscrawl
 Some agencies consistently publish their reports on a specific "Publications" page, but many do not. Some add metadata to the PDF files, many do not. In practice, the work of automatically fetching documents from hundreds of websites is too much and most organisations do not keep their old reports online.
 These publications are also archived by three organisations:
 - the Swedish National Library (*Kungliga biblioteket*), still partly in paper form
 - the Swedish National Archives (*Riksarkivet*), still partly in paper form and often with a delay of several years
 - the Government Offices of Sweden (*Regeringskansliet*) in their digital registry (*diariesystem*) for those documents sent to the government
 The data is in [archive_org.parquet](./archive_org.parquet).
 The Internet Archive provides:
 - *timestamp*, a timestamp for the time the document was archived
 - *original*, the URL at which the document was found
 - *length*, the size in bytes of the archived file
 The file also contains two fields generated by the data:
 - *archive*, the URL to access the file on the Wayback Machine, made with *timestamp* and *original*
 - *filename*, the filename extracted from the URL if possible
 The data is in [common_crawl.parquet](./common_crawl.parquet).
 The Common Crawl Index API provides:
 - *Domain*, the base domain at which the file was fetched
 - *Period*, a monthly or yearly reference to when it was fetched
 - *URL*, the URL at which the document was found
 ## What's next?
 The two sources contain respectively 2.16 and 1.25 million rows. The next steps are to:
 - identify the documents that hold a high value, like reports
 - filter out duplicates
 - determine important metadata about the documents such as their title, register number and potentially other connections with important processes (government missions...)
 This can't only be done by looking at the URL of the document, they need to be downloaded and analysed. A script to do it using ML and LLM is in preparation.
+If you want to try and analyse the documents in this dataset, don't hesitate to reach out so we can join forces!