Open access (OA) can be defined as the practice of providing on-line access to scientific information that is free of charge to the user and that is re-usable. A distinction is usually made between OA to scientific peer reviewed publications and research data. In Horizon 2020 open access to peer-reviewed scientific publications (primarily articles) is mandatory; however, researchers can choose between the open access route most appropriate to them.

For open access publishing (gold open access), researchers can publish in open access journals, or in journals that sell subscriptions and also offer the possibility of making individual articles openly accessible (hybrid journals). In that case, publishers often charge an article processing charge (APC). These costs are eligible for reimbursement during the duration of the Horizon 2020 grant. For APCs incurred after the end of the grant agreement, a mechanism for reimbursing some of these costs is being piloted and implemented through the OpenAIRE project. Note that in case of gold open access publishing, a copy must also be deposited in an open access repository.

For self-archiving (green open access), researchers deposit the final peer-reviewed manuscript in a repository of their choice. In this case, they must ensure open access to the publication within six months of publication (12 months in case of the social sciences and humanities).

This page provides an overview of the state of play as regards the uptake of open access to scientific publications in Horizon 2020 from 2014 to 2017, updating information from 2016.

Two datasets have been used for the analysis presented in this note: one dataset from the EU funded OpenAIRE project for FP7 and H2020 and one dataset from CORDA for H2020, which also provides supplementary information on article processing charges and embargo periods. The datasets are from September and August 2017 respectively.

The OpenAIRE sample includes primarily peer-reviewed scientific articles but also some other forms of publications such as conference papers, book chapters and reports or pre-prints. It is based on information obtained from Open Access repositories, pre-print servers, OA journals and project reports and contains some underreporting since OpenAIRE has difficulties tracking hybrid publications and publications in repositories which are not OpenAIRE compliant. The CORDA sample contains only peer-reviewed scientific articles and is based on project self-reporting. The figures in this note measure open access in a broad sense and not the compliance with the specifics of article 29.2. of the Model Grant Agreement.

The 2017 analysis of open access during the entirety of Horizon 2020 so far shows an overall open access rate of 63,2% from OpenAIRE data (+2,4% compared with the sample from 2016). Internal project reporting through SYGMA shows a total of 80,6% open access for Horizon 2020 scientific peer reviewed articles and 75% for all peer-reviewed publications (including also conference procedures, book chapter, monographs and the like); however, since this data is based on beneficiary self-reporting it may contain some over-reporting.

According to the OpenAIRE sample 75% of publications are green open access and 25% gold open access. Internal figures are similar although they show a slightly higher amount of gold OA with a split of 70% green and 30% gold.

For gold OA internal project reporting suggests than an average of 1500 € is spent per article (median: 1200 €), an increase from the average of 1006 € in the previous sample. A more detailed analysis reveals that 27% percent of articles have a price tag of between 1000 to 1999 €. It is also important to note that 26% of all publications are in gold OA but without any APC charges. Very high APCs of 4000€ or more only concerns a tiny fraction of Horizon 2020 publications (3%).

The average embargo period of green OA publications is 10 months, that is a decrease of 1 month from the 2016 sample. 40% of articles have an embargo period of 11-12 months, followed by 575 articles (or 33% with no embargo period at all. 302 articles, that is 17% have an embargo period of 12,1-24 months and 162 articles or 9% of 0,1 to 6 months. Finally, 12 articles, that is 1%, have an embargo period that is longer than 36 months.

This 2017 analysis thus broadly confirms the earlier findings from summer 2016, but is based on a larger and more robust sample. In the 2017 sample overall open access rates have gone up in all the datasets and cohorts. The distribution between gold and green open access remains similar to the 2016 dataset; for gold OA, average APCs have increased, for green OA embargo periods have slight decreased.

Please consult the background note for a more detailed analysis. Note also that these files only refer to open access to publications. Information on open access to research data is made available on the open data portal on a diffe

The following dataset provides information on the publication costs spent by the Austrian Science Fund (FWF) via the programmes Peer-reviewed Publications (https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/) and Stand-Alone Publications (https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/) in 2022.

Big Data and Society Publication fee - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Following the approach for the datasets in 2013 (http://dx.doi.org/10.6084/m9.figshare.988754), 2014 (https://dx.doi.org/10.6084/m9.figshare.1378610.v14) and 2015 (https://doi.org/10.6084/m9.figshare.3180166), the Austrian Science Fund (FWF) is making the publication costs spent in 2016 (esp. for Open Access) publically available.

The dataset includes payments for publications of authors funded by the Austrian Science Fund (FWF) via following programmes:

Peer-Reviewed Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/

Stand-Alone Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/

Revised data on funders and revenue for articles published by eLife and PLOS, and aggregated by BioOne for 2015, as part of a model for open access publishing in which funders and libraries (for unsponsored research) pay publishers directly. Data is used in article "If Research Libraries an Funders Finance Open Access.

Big Data and Society Abstract & Indexing - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Big Data and Society CiteScore 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Following the approach for the datasets in 2013 (http://dx.doi.org/10.6084/m9.figshare.988754) and 2014 (https://dx.doi.org/10.6084/m9.figshare.1378610.v14), the Austrian Science Fund (FWF) is making the publication costs spent in 2015 (esp. for Open Access) publically available.

The dataset includes payments for publications of authors funded by the Austrian Science Fund (FWF) via following programmes:

"Peer-Reviewed Publications": https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/

"Stand-Alone Publications": https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/

Big Data and Society Acceptance Rate - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Following the approach for the datasets in 2013 (http://dx.doi.org/10.6084/m9.figshare.988754), 2014 (https://dx.doi.org/10.6084/m9.figshare.1378610.v14), 2015 (https://doi.org/10.6084/m9.figshare.3180166) and 2016 (https://doi.org/10.5281/zenodo.810596), the Austrian Science Fund (FWF) is making the publication costs spent in 2017 (esp. for Open Access) publically available.

The dataset includes payments for publications of authors funded by the Austrian Science Fund (FWF) via following programmes:

Peer-Reviewed Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/

Stand-Alone Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/

The following data set provides information on the publication costs spent by the Austrian Science Fund (FWF) via the programmes Peer-reviewed Publications (https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/) and Stand-Alone Publications (https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/) in 2018.

Analysis of ‘Uptake of open access to scientific peer reviewed publications in Horizon 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/open-access-to-scientific-publications-horizon2020 on 10 January 2022.

--- Dataset description provided by original source is as follows ---

Open access (OA) can be defined as the practice of providing on-line access to scientific information that is free of charge to the user and that is re-usable. A distinction is usually made between OA to scientific peer reviewed publications and research data. In Horizon 2020 open access to peer-reviewed scientific publications (primarily articles) is mandatory; however, researchers can choose between the open access route most appropriate to them.

For open access publishing (gold open access), researchers can publish in open access journals, or in journals that sell subscriptions and also offer the possibility of making individual articles openly accessible (hybrid journals). In that case, publishers often charge an article processing charge (APC). These costs are eligible for reimbursement during the duration of the Horizon 2020 grant. For APCs incurred after the end of the grant agreement, a mechanism for reimbursing some of these costs is being piloted and implemented through the OpenAIRE project. Note that in case of gold open access publishing, a copy must also be deposited in an open access repository.

For self-archiving (green open access), researchers deposit the final peer-reviewed manuscript in a repository of their choice. In this case, they must ensure open access to the publication within six months of publication (12 months in case of the social sciences and humanities).

This page provides an overview of the state of play as regards the uptake of open access to scientific publications in Horizon 2020 from 2014 to 2017, updating information from 2016.

Two datasets have been used for the analysis presented in this note: one dataset from the EU funded OpenAIRE project for FP7 and H2020 and one dataset from CORDA for H2020, which also provides supplementary information on article processing charges and embargo periods. The datasets are from September and August 2017 respectively.

The OpenAIRE sample includes primarily peer-reviewed scientific articles but also some other forms of publications such as conference papers, book chapters and reports or pre-prints. It is based on information obtained from Open Access repositories, pre-print servers, OA journals and project reports and contains some underreporting since OpenAIRE has difficulties tracking hybrid publications and publications in repositories which are not OpenAIRE compliant. The CORDA sample contains only peer-reviewed scientific articles and is based on project self-reporting. The figures in this note measure open access in a broad sense and not the compliance with the specifics of article 29.2. of the Model Grant Agreement.

The 2017 analysis of open access during the entirety of Horizon 2020 so far shows an overall open access rate of 63,2% from OpenAIRE data (+2,4% compared with the sample from 2016). Internal project reporting through SYGMA shows a total of 80,6% open access for Horizon 2020 scientific peer reviewed articles and 75% for all peer-reviewed publications (including also conference procedures, book chapter, monographs and the like); however, since this data is based on beneficiary self-reporting it may contain some over-reporting.

According to the OpenAIRE sample 75% of publications are green open access and 25% gold open access. Internal figures are similar although they show a slightly higher amount of gold OA with a split of 70% green and 30% gold.

For gold OA internal project reporting suggests than an average of 1500 € is spent per article (median: 1200 €), an increase from the average of 1006 € in the previous sample. A more detailed analysis reveals that 27% percent of articles have a price tag of between 1000 to 1999 €. It is also important to note that 26% of all publications are in gold OA but without any APC charges. Very high APCs of 4000€ or more only concerns a tiny fraction of Horizon 2020 publications (3%).

The average embargo period of green OA publications is 10 months, that is a decrease of 1 month from the 2016 sample. 40% of articles have an embargo period of 11-12 months, followed by 575 articles (or 33% with no embargo period at all. 302 articles, that is 17% have an embargo period of 12,1-24 months and 162 articles or 9% of 0,1 to 6 months. Finally, 12 articles, that is 1%, have an embargo period that is longer than 36 months.

This 2017 analysis thus broadly confirms the earlier findings from summer 2016, but is based on a larger and more robust sample. In the 2017 sample overall open access rates have gone up in all the datasets and cohorts. The distribution between gold and green open access remains similar to the 2016 dataset; for gold OA, average APCs have increased, for green OA embargo periods have slight decreased.

Please consult the background note for a more detailed analysis. Note also that these files only refer to open access to publications. Information on open access to research data is made available on the open data portal on a different page.

--- Original source retains full ownership of the source dataset ---

The data set consists of the FWF publication cost data sets of the years 2013 to 2018 which are publicly available on Zenodo: https://zenodo.org/communities/fwf/?page=1&size=20

The data set includes payments for publications funded by the FWF programmes:

Peer-reviewed Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/peer-reviewed-publications/

and Stand-Alone Publications: https://www.fwf.ac.at/en/research-funding/fwf-programmes/stand-alone-publications/

Abstract from accompanying documentation article: This article documents Open access article processing charges (OA APC) Main 2016 available for download from the OA APC dataverse, an update and expansion of the preliminary 2015 dataset described in Data [1]. This dataset was gathered as part of Sustaining the Knowledge Commons (SKC), a research program funded by Canada’s Social Sciences and Humanities Research Council. The overall goal of SKC is to advance our collective knowledge about how to transition scholarly publishing from a system dependent on subscriptions and purchase to one that is fully open access. The OA APC Main 2016 dataset was developed as one of the lines of research of SKC, a longitudinal study of the minority (about a third) of the fully open access journals that use this business model. Data gathering and analyses will continue on an ongoing basis and will be published annually. We encourage others to share their data as well. In order to merge datasets, note that the two most critical elements for matching data and merging datasets are the journal title and ISSN.

Le fichier de données principal (dossier /input) est une version enrichie des données du Baromètre de la science ouverte (BSO), décrivant 1 032 517 articles de recherche (identifiés par leur DOI) publiés par des auteurs affiliés à des institutions françaises entre 2013 et 2020. L'enrichissement porte sur le pays des auteurs correspondant, la couleur OA de l'article (gold, hybride, diamant), le paiement d'un APC (article processing charges), le montant des APC, et la présence de la revue dans les accords Couperin. L'ensemble des variables est décrit dans le dictionnaire de variables : https://github.com/datactivist/etude_APC_public/blob/main/dictionary.md Les fichiers de données secondaires (dossier /output) sont les valeurs de sortie des analyses et des modèles de l'étude.

Northumbria University's report on usage of the RCUK Open Access block grant, and compliance with the RCUK Open Access policy, for the year 1st August 2014-31st July 2015.Publication data was gathered from Northumbria Research Link, the University's Open Access research repository. Information about article processing charges is recorded through the year in the Jisc APC template. Further information on research funding was obtained through reports extracted from the Agresso finance system.

Functional costs for APC payments at four Universities (anonymised).

Research data BPM APC FMPS UCPS DLPS SDPS PDPS ASTV MSTV ALTV MLTV Width Min Max NSP

Advanced Process Control Market Outlook

According to our latest research, the global Advanced Process Control (APC) market size reached USD 21.4 billion in 2024, driven by the increasing demand for process optimization across various industries. The market is experiencing robust expansion, exhibiting a CAGR of 9.2% over the forecast period. By 2033, the Advanced Process Control market is projected to reach USD 47.2 billion, reflecting the growing integration of automation and digitalization in industrial operations. This growth is primarily fueled by the imperative need for enhanced operational efficiency, cost reduction, and compliance with stringent regulatory standards, which are pushing organizations to adopt advanced control solutions across their production environments.

The primary growth driver for the Advanced Process Control market is the increasing complexity of industrial processes, which necessitates sophisticated control mechanisms to maintain product quality, reduce variability, and ensure safety. Industries such as oil and gas, chemicals, and pharmaceuticals are particularly reliant on APC systems to optimize their operations, minimize waste, and achieve consistent output. The integration of APC with Industrial Internet of Things (IIoT) and machine learning technologies is further amplifying its effectiveness, enabling real-time data analysis and predictive control. As industries strive to remain competitive, the adoption of APC solutions is becoming a strategic imperative, ensuring sustained productivity and profitability in the face of fluctuating market demands and resource constraints.

Another significant factor propelling the growth of the Advanced Process Control market is the rising focus on energy efficiency and sustainability. With global energy costs on the rise and increasing pressure to reduce carbon footprints, industries are investing heavily in technologies that can optimize energy consumption without compromising on output quality. APC systems play a pivotal role in achieving these objectives by enabling precise control over process variables, thereby reducing energy wastage and emissions. This trend is especially prominent in the energy and power sector, where the adoption of APC is helping utilities and manufacturers transition towards greener operations while maintaining regulatory compliance.

Additionally, the digital transformation wave sweeping across the industrial landscape is accelerating the deployment of APC solutions. The proliferation of cloud computing, big data analytics, and artificial intelligence is empowering organizations to implement more flexible and scalable APC architectures. Cloud-based APC deployments, in particular, are gaining traction due to their ability to offer centralized monitoring, remote access, and cost-effective scalability. This digital shift is not only enhancing the performance of existing control systems but also opening up new avenues for innovation in process automation and optimization. As a result, the Advanced Process Control market is poised for substantial growth, with organizations increasingly leveraging these technologies to drive operational excellence.

From a regional perspective, Asia Pacific is emerging as the fastest-growing market for Advanced Process Control, fueled by rapid industrialization, expanding manufacturing sectors, and government initiatives promoting smart factories. North America and Europe continue to be significant contributors, driven by early technology adoption and stringent regulatory frameworks. Meanwhile, the Middle East & Africa and Latin America are witnessing steady growth, supported by investments in energy and infrastructure development. The global landscape is thus characterized by a mix of mature and emerging markets, each contributing uniquely to the overall expansion of the Advanced Process Control market.

Component Analysis

The Advanced Process Control market by component is segmented into software, services, and hardware, each playing a critical role in the overall functionality and adoption of APC soluti

This spreadsheet lists the article level data detailing how the University of Leicester has used the Research Councils UK (RCUK) Open Access Block Grant between 01 April 2017 and 31 March 2018.