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6 results for “EU legislation”
Exported Definitions, References, Document Structure from EU Legislations
<p>A sample corpus of definitions, references, and document structures extracted from the EUR-LEX corpus of EU Legislations.</p>
Data from: A prioritised list of invasive alien species to assist the effective implementation of EU legislation
1. Effective prevention and control of invasive species generally relies on a comprehensive, coherent and representative list of species that enables resources to be used optimally. European Union (EU) Regulation 1143/2014 on invasive alien species (IAS) aims to control or eradicate priority species, and to manage pathways to prevent the introduction and establishment of new IAS; it applies to species considered of Union concern and subject to formal risk assessment. So far, 49 species have been listed but the criteria for selecting species for risk assessment have not been disclosed and were probably unsystematic. 2. We developed a simple method to systematically rank invasive alien species according to their maximum potential threat to biodiversity in the EU. We identified 1323 species as potential candidates for listing, and evaluated them against their invasion stages and reported impacts, using information from databases and scientific literature. 3. 900 species fitted the criteria for listing according to IAS Regulation. We prioritised 207 species for urgent risk assessment, 59 by 2018 and 148 by 2020, based on their potential to permanently damage native species or ecosystems; another 336 species were identified for a second phase (by 2025), to prevent or reverse their profound impacts on biodiversity; and a further 357 species for assessment by 2030. 4. Policy implications. We propose a systematic, proactive approach to selecting and prioritising invasive alien species for risk assessment to assist European Union policy implementation. We assess an unprecedented number of species with potential to harm EU biodiversity using simple methodology that we developed, and recommend which species should be considered for risk assessment in a ranked order of priority along the timeline 2018-2030, based on their maximum reported impact and their invasion history in Europe.
EU legislation published between 1971-2022
<p><strong>EU Legislation Documents and Metadata from 1971 to 2022 (English language)</strong></p> <p>This is the set of full text regulation, decision and directive documents in <a href="https://en.wikipedia.org/wiki/PDF">PDF</a> and <a href="https://en.wikipedia.org/wiki/HTML">HTML</a> format, in the English language, downloaded from <a href="https://eur-lex.europa.eu/">EURLEX</a>, together with metadata in <a href="https://en.wikipedia.org/wiki/Comma-separated_values">CSV format</a> about these documents. The documents were downloaded using <a href="https://github.com/nature-of-eu-rules/data-extraction/blob/main/eu_rules_fulltext_extractor.py">this Python script</a>, and the metadata was extracted from the <a href="https://op.europa.eu/en/publication-detail/-/publication/658088eb-c071-11e8-9893-01aa75ed71a1/language-en/format-PDF/source-76875949">CELLAR</a> <a href="http://publications.europa.eu/webapi/rdf/sparql">SPARQL endpoint</a> using <a href="https://github.com/nature-of-eu-rules/data-extraction/blob/main/eu_rules_metadata_extractor.py">this Python script</a>.</p> <p>During the download process, HTML versions for the legislative documents were extracted if they were available. If there was no HTML version available for a particular document, the PDF version was downloaded (HTML versions were preferred because it is generally simpler to extract and process the text with software because of the added structure the format provides). If there was neither an HTML nor PDF version available, we made a note of the unique identifier (<a href="https://eur-lex.europa.eu/content/help/eurlex-content/celex-number.html">CELEX</a> number) for those documents. The archive in this <a href="https://zenodo.org/">Zenodo</a> repository which contains all the full text documents consists of three directories "htmls/", "pdfs/" and "problems/", which contain all the downloaded documents in that particular format. The "problems/" directory contains a list of blank <a href="https://en.wikipedia.org/wiki/Text_file">.txt</a> files where the name of each file is the CELEX number for a legislative document that was not available on EURLEX for download.</p> <p>For more information about the scripts and a description of the metadata extracted, please see <a href="https://github.com/nature-of-eu-rules/data-extraction">this Github repository.</a></p> <p>The data was extracted as part of the <a href="https://research-software-directory.org/projects/the-nature-of-eu-rules-strict-and-detailed-or-lacking-bite">Nature of EU Rules</a> project which seeks to analyse the "strictness" and density of EU regulations over time and by legal policy area.</p> <p> </p>
Data from: A prioritised list of invasive alien species to assist the effective implementation of EU legislation
Open the record for dataset details and reuse information.
Schönberg, J., Böhm-Beck, M., Trdan, Š., Grego, M., Knoblauch, D., Hinzmann, M., Dittmann, S., Knickmeier, K., Robič, U., Thiel, M., Kiessling, T., 2025. Public participation in EU legislation? Recommendations for involving citizen scientists in anthropogenic litter research within the Water Framework Directive.
<p>Research data and figures to the manuscript "Public participation in EU legislation? Recommendations for involving citizen scientists in anthropogenic litter research within the Water Framework Directive" by Schönberg et al. 2025</p>
Reproducibility data for a study of regulatory statements in EU legislation
<p><strong>Reproducibility data for a quantitative study on EU legislation</strong></p> <p>The files in this repository were generated or used in a pipeline of analysis operations on EU legislation published between 1971 and 2022. The project is called the <a href="https://research-software-directory.org/projects/the-nature-of-eu-rules-strict-and-detailed-or-lacking-bite">Nature of EU Rules</a> which seeks to analyse the "strictness" and density of EU regulations over time and by legal policy area. The data has been made available to help make the results of our study reproducible by other researchers. The underlying data used in the study has also been published in <a href="https://doi.org/10.5281/zenodo.8174175">this repository</a>.</p> <p><strong>File descriptions</strong></p> <ol> <li>complete_training_data.csv <ul> <li>This file is training data for binary classification of specific sentences in EU legislation as either regulatory in nature (constituting a legal obligation for some agent) or not (called a constitutive statement). The sentences have been labelled by EU law professors from Aarhus University in Denmark and Radboud University in the Netherlands</li> <li><strong>Note:</strong> The file also contains columns for identifying the specific agent being regulated (to which the legal obligation applies) in each sentence. However, this information has not been used in the study</li> </ul> </li> <li>extracted_sentences_classified_1971_2022.csv <ul> <li>List of sentences extracted from EU legislation documents</li> <li>Classification results for individual sentences whether each is regulatory or not. There are two columns recording the classification results, one for a rule-based approach (using <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/rule-based-classification.py">grammatical dependency parsing</a>) and one for a <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/inlegalbert-classification.py">LegalBERT classification</a> approach.</li> </ul> </li> <li>inlegal_bert_xgboost_classifier.json <ul> <li>Trained binary classification model for classifying sentences as regulatory or not (based on <a href="https://huggingface.co/law-ai/InLegalBERT">InlegalBERT</a>).</li> <li>Note: this model is trained on the file 'complete_training_data.csv' in this Zenodo repo</li> <li>Model was trained using <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/train_inlegalbert_xgboost.py">this script</a> and used by these scripts: <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/classify_text_with_inlegal_bert_xgboost.py">one</a>, <a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification/blob/main/inlegalbert-classification.py">two</a></li> </ul> </li> <li>metadata_enriched.csv <ul> <li>Metadata file from <a href="../record/8174176">this repository</a> but enriched with additional columns one of which is the count of regulatory sentences in each individual document</li> <li>File is generated by <a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis/blob/main/prepare-data-for-analysis.py">this script</a></li> <li>File is used by <a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis/blob/main/analysis.py">this script</a></li> </ul> </li> <li>classification_results_all_algorithms_test_set.csv <ul> <li>classification results of each sentence in the test set containing 1451 sentences (20% of training set)</li> <li>according to both the fine-tuned Legal-BERT model and the dependency parsing (rule-based) algorithm</li> <li>also contains the ground truth labels</li> </ul> </li> </ol> <p><strong>Github repositories relevant to this analysis</strong></p> <p>The Python scripts in the following Github repositories were responsible for generating the data files in this Zenodo repository. The first repository listed is the core one for running the pipeline to classify and quantitatively analyse legal obligations in EU legislation. The other listed Github repositories represent components or steps of the pipeline.</p> <ul> <li><a href="https://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis"><strong>http://github.com/nature-of-eu-rules/eu-legislation-strictness-analysis</strong></a> <ul> <li><a href="https://github.com/nature-of-eu-rules/data-extraction"><strong>http://github.com/nature-of-eu-rules/data-extraction</strong></a></li> <li><a href="https://github.com/nature-of-eu-rules/data-preprocessing"><strong>http://github.com/nature-of-eu-rules/data-preprocessing</strong></a></li> <li><a href="https://github.com/nature-of-eu-rules/regulatory-statement-classification"><strong>http://github.com/nature-of-eu-rules/regulatory-statement-classification</strong></a></li> </ul> </li> </ul> <p> </p>
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