{"status":"OK","data":{"id":285475,"identifier":"Q80QUE","persistentUrl":"https://doi.org/10.34894/Q80QUE","protocol":"doi","authority":"10.34894","separator":"/","publisher":"DataverseNL","publicationDate":"2022-04-23","storageIdentifier":"surf://10.34894/Q80QUE","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9996,"datasetType":"dataset","locks":[],"latestVersion":{"id":31609,"datasetId":285475,"datasetPersistentId":"doi:10.34894/Q80QUE","datasetType":"dataset","storageIdentifier":"surf://10.34894/Q80QUE","versionNumber":2,"internalVersionNumber":6,"versionMinorNumber":2,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionLink":"","lastUpdateTime":"2025-09-15T20:03:12Z","releaseTime":"2025-09-15T20:03:12Z","createTime":"2025-09-15T20:02:55Z","publicationDate":"2022-04-23","citationDate":"2022-04-23","effectiveDatasetFileCountLimit":10000,"datasetFileUploadsAvailable":9996,"termsOfUse":"<h2 id=\"license\">License</h2>\n<p>You are encouraged to use the Datasets to benefit yourself and others in creative ways. Therefore, you may extract, download, and make copies of the data contained in the Datasets, and you may share that data with third parties according to these terms of use.</p>\n<p><strong>1) Raw Data:</strong> Heritages the license from the original<br><strong>2) Complementary Data:</strong> These datasets are original creative work qualitatively generated by the researchers, and it&#39;s released under the same license<br><strong>3) Derived Data:</strong> These datasets are information processed by humans and machines and heritage the previous two license indications.  </p>\n<pre><code>Copyright (C) <span class=\"hljs-number\">2019</span><span class=\"hljs-number\">-2021</span>, European Union, Zahar Koretsky, Pedro V. Hernández Serrano, Seun Adekunle.\n</code></pre><p><a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by/4.0/\">Creative Commons Attribution 4.0 International License</a>.\nThis means that you can re-use the content provided you acknowledge the source and indicate any changes you have made. </p>\n<p>You may be required to clear additional rights if certain content depicts identifiable private individuals or includes third-party works.</p>\n","conditions":"<h2 id=\"conditions\">Conditions</h2>\n\n<p>Following the FAIR principles of research data management, the following datasets in this enclosed folder (&quot;the Datasets&quot;) are described and classified by their provenance nature.</p>\n<p><strong>1) Raw Data:</strong> Datasets that are precisely in their original state which were downloaded  </p>\n<ul>\n<li><code>cordis-h2020projects.xlsx</code>  </li>\n</ul>\n<p><strong>2) Complementary Data:</strong> These datasets are catalogues or lookup tables. Complementary data does not come from the source and does not form part of the results of the articles. Rather aid the results  </p>\n<ul>\n<li><code>mitigation-technology-catalogue.xls</code></li>\n<li><code>sample_tagged.xls</code></li>\n<li><code>table_priorities.xlsx</code></li>\n<li><code>tech_example.xls</code></li>\n</ul>\n<p><strong>3) Derived Data:</strong> These datasets are the table results after data processing methodologies. Datasets are outputs of the modelling process</p>\n<ul>\n<li><code>cordis-h2020projects-filtered-by-CleanTechTag-Final.xls</code></li>\n<li><code>not_invested_technologies.xlsx</code></li>\n<li><code>cleantechtag_deterministic_results.csv</code></li>\n<li><code>cleantechtag_joint_results.csv</code></li>\n<li><code>cleantechtag_probabilistic_results.csv</code></li>\n<li><code>not_invested_technologies.csv</code></li>\n<li><code>sample_to_tag.csv</code></li>\n</ul>\n<p>The Datasets are in machine-readable formats. Their Open Access nature makes them free of charge, subject to the terms of this agreement (these “Dataset Terms”), and subject to the general Terms and Conditions for using the original <a href=\"https://op.europa.eu/en/web/about-us/legal-notices/publications-office-of-the-european-union-copyright\">Copyright notice\nof the Publications Office of the European Union (OP Portal)</a>. Where these Dataset Terms conflict with the General Terms and Conditions, these Dataset Terms shall prevail. The use of data derived from the Datasets, which may appear in formats such as tables and charts, is also subject to these Dataset Terms.</p>\n","disclaimer":"<h2 id=\"disclaimer\">Disclaimer</h2>\n<p>You can use the data as you wish. For example, You can create application programming interfaces (“APIs”) to facilitate access to the Datasets. However, THE AUTHORS SHALL NOT BE RESPONSIBLE OR LIABLE TO YOU FOR ANY LOSS OR DAMAGE OF ANY SORT INCURRED BY YOU IN CONNECTION WITH YOUR USE OF THE DATASETS</p>\n<p>The datasets were created for scientific purposes. Therefore, if there are indications of any violation of these terms, we keep the right that at any to modify or discontinue, temporarily or permanently, the Datasets, the methods and any means of accessing or utilising the Datasets at our sole discretion with or without prior notice.</p>\n","termsOfAccess":"<h2 id=\"access-protocols-\">Access Protocols 🔐</h2>\n<p>All Digital Objects (DOs) contained in this repository (i.e. Software, Datasets) are <strong><a href=\"https://en.wikipedia.org/wiki/Open_access\">Open Access</a></strong>, meaning that they are retrievable with a standard HTTP request from any browser such as cloning the repository, curl the resource or sumply pressing the download bottom. 👆🏼  </p>\n<p><img src=\"https://s3.amazonaws.com/libapps/accounts/33900/images/OAlogo.jpg\" width=\"230\" height=\"80\"></p>\n<ul>","dataAccessPlace":"<li><p>The repository can also be downloaded in  Zenodo at <a href=\"https://zenodo.org/record/4657236/files/MaastrichtU-IDS/clean-technologies-nlp-1.0.zip?download=1\">zenodo.org/record/4657236</a> and at Dataverse at <a href=\"https://dataverse.nl/dataset.xhtml?persistentId=doi:10.34894/Q80QUE\">dataverse.nl/doi:10.34894/Q80QUE</a></p>\n</li>\n<li><p><strong>SPARQL Endpoint</strong><br>Unfortunately, this data does not have a data service available due to a lack of resources; however, the dataset <code>../data/joint_results_cleantechtag.csv</code> is semantically annotated following the standard vocabularies following the FAIR principles; therefore, you could easily set up a local SPARQL endpoint.</p>\n</li>\n<li>Open your terminal (you need Python installed)</li>\n<li>Install the following </li>\n</ul>\n<p><code>pip install rdflib-endpoint@git+https://github.com/vemonet/rdflib-endpoint@main</code></p>\n<ol>\n<li>Expose the RDF file to the local service </li>\n</ol>\n<p><code>rdflib-endpoint serve ../data/cordis-cleantechtag.nt</code></p>\n<ol>\n<li>Go to your localhost at <a href=\"http://0.0.0.0:8000\">http://0.0.0.0:8000</a></li>\n</ol>\n","originalArchive":"<h3 id=\"cordis-data\">CORDIS data</h3>\n<p>The original files (Raw Data) on which this study derives its results can be found on the EU Open Data Portal landing page. This data will always contain the last updated version: <a href=\"https://data.europa.eu/euodp/en/data/dataset/cordisref-data/resource/9840dedb-5abb-4724-a72c-6be08d3413f8\">H2020 programmes</a></p>\n","fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"A qualitative-computational cataloguing of the EU-level public research and innovation portfolio of clean energy technologies (2014–2020)"},{"typeName":"alternativeURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.5281/zenodo.4657236"},{"typeName":"otherId","multiple":true,"typeClass":"compound","value":[{"otherIdAgency":{"typeName":"otherIdAgency","multiple":false,"typeClass":"primitive","value":"Zenodo"},"otherIdValue":{"typeName":"otherIdValue","multiple":false,"typeClass":"primitive","value":"10.5281/zenodo.4657236"}}]},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Koretsky, Zahar"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Laboratoire Interdisciplinaire Sciences Innovations Sociétés (UMR LISIS)"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0002-9671-2867"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Hernández Serrano, Pedro"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Maastricht University"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0002-4646-4666"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Adekunle, Seun"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Maastricht University"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Dumontier, Michel"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Maastricht University"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0003-4727-9435"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Hernández Serrano, Pedro"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"Maastricht University"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"<h2 id=\"article-abstract\">Article Abstract</h2>\n<p>To better allocate funds in the new EU research framework programme Horizon Europe, an assessment of current and past efforts is crucial. In this paper <strong>we develop and apply a multi-method qualitative and computational approach to provide a catalogue of climate crisis mitigation technologies on the EU level between 2014 and 2020</strong>. Using the approach, we observed no public EU-level funding for multiple technologies prioritised by the EU, such as low-carbon production and use of cement and chemicals, electric battery, and a number of industrial decarbonisation processes. We observed a rising trend in the funding of solar power and onshore wind, the adjacent to them power-to-X technology, as well as recycling. At the same time, the shares of funding into fuel cell, biofuel, demand-side energy management, microgrids, and waste management show a decline trend. With note of the exploratory character of the present paper, we propose that the EU Horizon 2020 funding of clean technologies only partially reflected the expectations of key institutionalised EU actors due to the existence of many non-funded prioritised technologies.</p>"},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2021-04-01"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Agricultural Sciences","Computer and Information Science","Earth and Environmental Sciences","Social Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"CORDIS"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"EU Vocabularies"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://publications.europa.eu/resource/authority/corporate-body/CORDIS"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Policy analysis"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"EUROVOC"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://eurovoc.europa.eu/c_9829e6b7"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Horizon 2020"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"EU Vocabularies"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://publications.europa.eu/resource/authority/class-sum-leg/270401"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Clean technology"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"Semantic Web for Earth and Environment Technology Ontology"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://sweetontology.net/humanTechReadiness/Technology"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Sustainability"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"Semantic Web for Earth and Environment Technology Ontology"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://sweetontology.net/humanEnvirConservation/Sustainability"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Text mining"},"keywordVocabulary":{"typeName":"keywordVocabulary","multiple":false,"typeClass":"primitive","value":"Intelligence Task Ontology"},"keywordVocabularyURI":{"typeName":"keywordVocabularyURI","multiple":false,"typeClass":"primitive","value":"http://edamontology.org/operation_0306"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Zahar Koretsky, Pedro V. Hernández Serrano, Seun Adekunle, Michel Dumontier,\nA qualitative-computational cataloguing of the EU-level public research and innovation portfolio of clean energy technologies (2014–2020),\nCurrent Research in Environmental Sustainability,\nVolume 3,\n2021,\n100084,\nISSN 2666-0490"},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"doi"},"publicationIDNumber":{"typeName":"publicationIDNumber","multiple":false,"typeClass":"primitive","value":"10.1016/j.crsust.2021.100084"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.1016/j.crsust.2021.100084"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"<h2 id=\"dataset-description\">Dataset Description</h2>\n<p>The description and details of the methodology including the computational framework and data analysis together with the data and file usage is described in the original Github repository: <strong><a href=\"https://github.com/MaastrichtU-IDS/clean-technologies-nlp/tree/master/notebooks/README.md\">Data Analysis Description</a></strong></p>\n\n<p><strong>NOTE:</strong> Please mind that this repository only contains the resulting dataset that the article refers to additionally to its codebook. The analysis and all the data processing methods are in the original Github repository at:</p>\n<p><a href=\"https://github.com/MaastrichtU-IDS/clean-technologies-nlp\">github.com/MaastrichtU-IDS/clean-technologies-nlp</a></p>"},{"typeName":"language","multiple":true,"typeClass":"controlledVocabulary","value":["English"]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Hernández Serrano, Pedro"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2022-04-23"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2014-01-01"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2020-12-12"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["Policy Annotations","CORDIS data (Public projects funded by the EU within the H2020 programme)"]},{"typeName":"accessToSources","multiple":false,"typeClass":"primitive","value":"<p><strong>NOTE:</strong> Please mind that this repository is a mirror of the original Github repository:</p>\n<p><a href=\"https://github.com/MaastrichtU-IDS/clean-technologies-nlp\">github.com/MaastrichtU-IDS/clean-technologies-nlp</a></p>"}]},"dansDataVaultMetadata":{"displayName":"Data Vault Metadata","name":"dansDataVaultMetadata","fields":[{"typeName":"dansDataversePid","multiple":false,"typeClass":"primitive","value":"doi:10.34894/Q80QUE"},{"typeName":"dansDataversePidVersion","multiple":false,"typeClass":"primitive","value":"2.2"},{"typeName":"dansBagId","multiple":false,"typeClass":"primitive","value":"urn:uuid:1698fe2b-53a0-4f04-8080-7b47082f1a6f"},{"typeName":"dansNbn","multiple":false,"typeClass":"primitive","value":"urn:nbn:nl:ui:13-fcfbd9da-447e-4b2e-aadb-b939eac87aeb"}]}},"files":[{"label":"cleantechtag_joint_results.csv","restricted":false,"version":1,"datasetVersionId":31609,"dataFile":{"id":286678,"persistentId":"","filename":"cleantechtag_joint_results.csv","contentType":"text/csv","friendlyType":"Comma Separated Values","filesize":4074803,"storageIdentifier":"surf://store:18057dee169-71579a442ba9","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"c9b4a218560858b9acb9c6d72c7a282ab0d187b9"},"tabularData":false,"creationDate":"2022-04-23","publicationDate":"2022-04-23","lastUpdateTime":"2025-09-15T20:03:12Z","fileAccessRequest":true}},{"description":"something","label":"Clean-tech-v2.ipynb","restricted":false,"version":1,"datasetVersionId":31609,"dataFile":{"id":376307,"persistentId":"","filename":"Clean-tech-v2.ipynb","contentType":"application/x-ipynb+json","friendlyType":"Jupyter Notebook","filesize":38711,"description":"something","storageIdentifier":"surf://store:189307e2495-20b86d95e66e","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"e6189f448e95bca6bda801336d47a14594db6c3d"},"tabularData":false,"creationDate":"2023-07-07","publicationDate":"2023-08-02","lastUpdateTime":"2025-09-15T20:03:12Z","fileAccessRequest":true}},{"label":"cordis-cleantechtag.nt","restricted":false,"version":1,"datasetVersionId":31609,"dataFile":{"id":286680,"persistentId":"","filename":"cordis-cleantechtag.nt","contentType":"application/octet-stream","friendlyType":"Unknown","filesize":7370452,"storageIdentifier":"surf://store:18057dedd51-85a8c1ce3fb6","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"1dd8ee4f38d81aeec976f7b6673127ba7bce3bea"},"tabularData":false,"creationDate":"2022-04-23","publicationDate":"2022-04-23","lastUpdateTime":"2025-09-15T20:03:12Z","fileAccessRequest":true}},{"label":"cordis-h2020projects-filtered-by-CleanTechTag-Final.xls","restricted":false,"version":1,"datasetVersionId":31609,"dataFile":{"id":286679,"persistentId":"","filename":"cordis-h2020projects-filtered-by-CleanTechTag-Final.xls","contentType":"application/vnd.ms-excel","friendlyType":"MS Excel Spreadsheet","filesize":13824,"storageIdentifier":"surf://store:18057dede14-dfa7400997fd","rootDataFileId":-1,"checksum":{"type":"SHA-1","value":"2a323d7e65ce697751d66a70cda2e48765d182c8"},"tabularData":false,"creationDate":"2022-04-23","publicationDate":"2022-04-23","lastUpdateTime":"2025-09-15T20:03:12Z","fileAccessRequest":true}}]}}}