The first CRAN release 0.1.0
\nRegions is an offspring of the eurostat package. It started as a patch to the problematic transition of Eurostat's regional statistics from the NUTS2013 to the NUTS2016 regional typology, which made it impossible to create time series, data panels or data joins among different data tables. Eurostat's regional statistics is not tidy, because in the 'geo' ID it mixes together with incompatible identifiers from the NUTS2016 (current base case), and the NUTS2010 and often earlier typologies.
\nCurrent features:
\nan extended validation of country codes and European NUTS regional coding starting from 1999\nrecoding and relabelling across European NUTS typologies, and general functions that can work with any national, ISO 3166-2 or OECD typology as inputs.\nprojecting data from larger sub-national divisions to smaller ones\ntwo vignettes explaining this functionality.\nPlanned features:
\nIncorporation of new typologies, such as OECD's, Google's, and other major data sources.\nBetter coordination between rOpenGov packages, particularly eurostat and eurostat_geodata.\nNew imputation functionality based on re-aggregation, re-weighting.\nVignette on joining data from different typologies, such as Google Trends data with Eurostat data.\nThe main repo is rOpenGov/regions, where you can send pull requests to the devel branch. You can directly collaborate with the package author on antaldaniel/regions, too, but the core development will hopefully shift to rOpenGov.
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\r\n
\r\n- The data must be tidy, with all observations in rows, and all variables in columns.
\r\n- The data should be clearly described, and if possible, be reproducible with R or Python program code.
\r\n- If the dataset is not reproducible, we will try to make it reproducible with the author of the submitted dataset.
\r\n
Big data and automation create new inequalities and injustices and has a potential to create a jobless growth. Our Economy Data Observatory is a fully automated, open source, open data observatory that produces new indicators from open data sources and experimental big data sources, with authoritative copies and a modern API.
\r\n\r\nOur observatory is monitoring the European economy to protect the consumers and the small companies from unfair competition both from data and knowledge monopolization and robotization. We take a critical SME-, intellectual property policy and competition policy point of view automation, robotization, and the AI revolution on the service-oriented European social market economy.
\r\n\r\nWe would like to create early-warning, risk, economic effect, and impact indicators that can be used in scientific, business and policy contexts for professionals who are working on re-setting the European economy after a devastating pandemic and in the age of AI. We would like to map data between economic activities (NACE), antitrust markets, and sub-national, regional, metropolitian area data.
\r\n\r\nGet involved in services: our ongoing projects, team of contributors, open-source libraries and use our data for publications. See some use cases.
\r\n\r\nFollow news about us or the more comprehensive Data & Lyrics blog.
\r\n\r\nContact us .
\r\n\r\nOur data observatory is competing in the EU Datathon 2021. We believe that introducing Open Policy Analysis standards with open data, open-source software and research automation can help the economy that works for people, particulartly the challenge we are focusing on the Single market strategy. Our collaboration is open for individuals, citizens scientists, research institutes, NGOS, companies.
", "title": "Economy Data Observatory" }, "revision_id": 0, "slug": "economy_observatory", "updated": "2021-05-19T21:31:00.943918+00:00" }, { "access": { "member_policy": "open", "members_visibility": "public", "record_submission_policy": "open", "review_policy": "open", "visibility": "public" }, "children": { "allow": false }, "created": "2021-05-19T15:28:11.714526+00:00", "custom_fields": { "subjects": [ { "id": "euroscivoc:945" }, { "id": "euroscivoc:1715" }, { "id": "euroscivoc:1403" }, { "id": "euroscivoc:1791" } ] }, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "74b3126a-558f-40a1-b469-7b098181781e", "links": {}, "metadata": { "curation_policy": "We are going to publish here all curated data from the Digital Music Observatory, and we are looking for data related to the topic.
\n
\n- The data must be tidy, with all observations in rows, and all variables in columns.
\n- The data should be clearly described, and if possible, be reproducible with R or Python program code.
\n- If the dataset is not reproducible, we will try to make it reproducible with the author of the submitted dataset.
\n
\nOur aim is to create datasets that are periodically refreshed, and go through thorough unit testing.
The Digital Music Observatory is a fully automated, open source, open data observatory that links public datasets in order to provide a comprehensive view of the European music industry. The DMO produces key business and policy indicators that enable the growth of music business strategies and national music policies in a way that works both for music lover audiences and the creative enterprises of the sector.
\n\nIts data pillars are following the structure laid out in the Feasibility study for the establishment of a European Music Observatory:
\n\nThe Demo Music Observatory Pillars:
\n\n\n\n
Music is one of the most data-driven service industries where the majority of sales are already made by AI-driven autonomous systems. The DMO is a fully-functional service that can function as a testing ground of the European Data Strategy, showcasing the ways in which the music industry is affected by the problems that the Digital Services Act and the Trustworthy AI initiatives attempt to regulate. If these policies will work for the European microenterprise-dominated, complex and fragile European music ecosystem, then they are likely to make Europe fit for the digital age. We submit our automated observatory into the EU Datathon 2021 challenge.
We are going to publish here all curated data from the Green Deal Data Observatory, and we are looking for data related to the topic of the European Green Deal policies.
\r\n
\r\n- The data must be tidy, with all observations in rows, and all variables in columns.
\r\n- The data should be clearly described, and if possible, be reproducible with R or Python program code.
\r\n- If the dataset is not reproducible, we will try to make it reproducible with the author of the submitted dataset.
\r\n
Climate change and environmental degradation are an existential threat to Europe and the world. To overcome these challenges, the European Union created the European Green Deal strategic plan. It aims to make the EU’s economy sustainable by turning climate and environmental challenges into opportunities, and making the transition just and inclusive for all.
\r\n\r\nOur data observatory is competing in the EU Datathon 2021. We believe that introducing Open Policy Analysis standards with open data, open-source software and research automation can help the Green Deal policymaking process. Our collaboration is open for individuals, citizens scientists, research institutes, NGOS, companies.
\r\n\r\nGet involved in services: our ongoing projects, team of contributors, open-source libraries and use our data for publications. See some use cases.
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