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description Publicationkeyboard_double_arrow_right Preprint 2020 EnglishZamani, Maryam; Tejedor, Alejandro; Vogl, Malte; Krautli, Florian; Valleriani, Matteo; Kantz, Holger;We investigated the evolution and transformation of scientific knowledge in the early modern period, analyzing more than 350 different editions of textbooks used for teaching astronomy in European universities from the late fifteenth century to mid-seventeenth century. These historical sources constitute the Sphaera Corpus. By examining different semantic relations among individual parts of each edition on record, we built a multiplex network consisting of six layers, as well as the aggregated network built from the superposition of all the layers. The network analysis reveals the emergence of five different communities. The contribution of each layer in shaping the communities and the properties of each community are studied. The most influential books in the corpus are found by calculating the average age of all the out-going and in-coming links for each book. A small group of editions is identified as a transmitter of knowledge as they bridge past knowledge to the future through a long temporal interval. Our analysis, moreover, identifies the most disruptive books. These books introduce new knowledge that is then adopted by almost all the books published afterwards until the end of the whole period of study. The historical research on the content of the identified books, as an empirical test, finally corroborates the results of all our analyses. Comment: 19 pages, 9 figures
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2020MDPI AG Authors: Gimena del Rio Riande; Erzsébet Tóth-Czifra; Ulrike Wuttke; Yoann Moranville;Gimena del Rio Riande; Erzsébet Tóth-Czifra; Ulrike Wuttke; Yoann Moranville;The digital transformation has initiated a paradigm shift in research and scholarly communication practices towards a more open scholarly culture. Although this transformation is slowly happening in the Digital Humanities field, open is not yet default. The article introduces the OpenMethods metablog, a community platform that highlights open research methods, tools, and practices within the context of the Digital Humanities by republishing open access content around methods and tools in various formats and languages. It also describes the platform’s technical infrastructure based on its requirements and main functionalities, and especially the collaborative content sourcing and editorial workflows. The article concludes with a discussion of the potentials of the OpenMethods metablog to overcome barriers towards open practices by focusing on inclusive, community sourced information based around opening up research processes and the challenges that need to be overcome to achieve its goals.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2018 English EC | ALEXANDRIA, EC | DESIR, EC | AFELAuthors: Hube, Christoph; Fetahu, Besnik;Hube, Christoph; Fetahu, Besnik;Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. Comment: The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2018 EnglishAuthors: Jacobs, Arthur M.;Jacobs, Arthur M.;This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot's poem 'How Lisa Loved the King' and James Joyce's 'Chamber Music', concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control. Comment: 27 pages, 4 figures
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2017 English EC | INDIGO-DataCloudAuthors: Collaboration, INDIGO-DataCloud; Salomoni, Davide; Campos, Isabel; Gaido, Luciano; +60 AuthorsCollaboration, INDIGO-DataCloud; Salomoni, Davide; Campos, Isabel; Gaido, Luciano; de Lucas, Jesus Marco; Solagna, Peter; Gomes, Jorge; Matyska, Ludek; Fuhrman, Patrick; Hardt, Marcus; Donvito, Giacinto; Dutka, Lukasz; Plociennik, Marcin; Barbera, Roberto; Blanquer, Ignacio; Ceccanti, Andrea; David, Mario; Duma, Cristina; López-García, Alvaro; Moltó, Germán; Orviz, Pablo; Sustr, Zdenek; Viljoen, Matthew; Aguilar, Fernando; Alves, Luis; Antonacci, Marica; Antonelli, Lucio Angelo; Bagnasco, Stefano; Bonvin, Alexandre M. J. J.; Bruno, Riccardo; Cetinic, Eva; Chen, Yin; Chiarello, Fabrizio; Costa, Alessandro; Pra, Stefano Dal; Davidovic, Davor; Dorigo, Alvise; Ertl, Benjamin; Fanzago, Federica; Fargetta, Marco; Fiore, Sandro; Gallozzi, Stefano; Kurkcuoglu, Zeynep; Lloret, Lara; Martins, Joao; Nuzzo, Alessandra; Nassisi, Paola; Palazzo, Cosimo; Pina, Joao; Sciacca, Eva; Segatta, Matteo; Sgaravatto, Massimo; Spiga, Daniele; Taneja, Sonia; Tangaro, Marco Antonio; Urbaniak, Michal; Vallero, Sara; Verlato, Marco; Wegh, Bas; Zaccolo, Valentina; Zambelli, Federico; Zangrando, Lisa; Zani, Stefano; Zok, Tomasz;This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications. Comment: 39 pages, 15 figures.Version accepted in Journal of Grid Computing
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description Publicationkeyboard_double_arrow_right Preprint 2020 EnglishZamani, Maryam; Tejedor, Alejandro; Vogl, Malte; Krautli, Florian; Valleriani, Matteo; Kantz, Holger;We investigated the evolution and transformation of scientific knowledge in the early modern period, analyzing more than 350 different editions of textbooks used for teaching astronomy in European universities from the late fifteenth century to mid-seventeenth century. These historical sources constitute the Sphaera Corpus. By examining different semantic relations among individual parts of each edition on record, we built a multiplex network consisting of six layers, as well as the aggregated network built from the superposition of all the layers. The network analysis reveals the emergence of five different communities. The contribution of each layer in shaping the communities and the properties of each community are studied. The most influential books in the corpus are found by calculating the average age of all the out-going and in-coming links for each book. A small group of editions is identified as a transmitter of knowledge as they bridge past knowledge to the future through a long temporal interval. Our analysis, moreover, identifies the most disruptive books. These books introduce new knowledge that is then adopted by almost all the books published afterwards until the end of the whole period of study. The historical research on the content of the identified books, as an empirical test, finally corroborates the results of all our analyses. Comment: 19 pages, 9 figures
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2020MDPI AG Authors: Gimena del Rio Riande; Erzsébet Tóth-Czifra; Ulrike Wuttke; Yoann Moranville;Gimena del Rio Riande; Erzsébet Tóth-Czifra; Ulrike Wuttke; Yoann Moranville;The digital transformation has initiated a paradigm shift in research and scholarly communication practices towards a more open scholarly culture. Although this transformation is slowly happening in the Digital Humanities field, open is not yet default. The article introduces the OpenMethods metablog, a community platform that highlights open research methods, tools, and practices within the context of the Digital Humanities by republishing open access content around methods and tools in various formats and languages. It also describes the platform’s technical infrastructure based on its requirements and main functionalities, and especially the collaborative content sourcing and editorial workflows. The article concludes with a discussion of the potentials of the OpenMethods metablog to overcome barriers towards open practices by focusing on inclusive, community sourced information based around opening up research processes and the challenges that need to be overcome to achieve its goals.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2018 English EC | ALEXANDRIA, EC | DESIR, EC | AFELAuthors: Hube, Christoph; Fetahu, Besnik;Hube, Christoph; Fetahu, Besnik;Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. Comment: The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2018 EnglishAuthors: Jacobs, Arthur M.;Jacobs, Arthur M.;This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot's poem 'How Lisa Loved the King' and James Joyce's 'Chamber Music', concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control. Comment: 27 pages, 4 figures
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint 2017 English EC | INDIGO-DataCloudAuthors: Collaboration, INDIGO-DataCloud; Salomoni, Davide; Campos, Isabel; Gaido, Luciano; +60 AuthorsCollaboration, INDIGO-DataCloud; Salomoni, Davide; Campos, Isabel; Gaido, Luciano; de Lucas, Jesus Marco; Solagna, Peter; Gomes, Jorge; Matyska, Ludek; Fuhrman, Patrick; Hardt, Marcus; Donvito, Giacinto; Dutka, Lukasz; Plociennik, Marcin; Barbera, Roberto; Blanquer, Ignacio; Ceccanti, Andrea; David, Mario; Duma, Cristina; López-García, Alvaro; Moltó, Germán; Orviz, Pablo; Sustr, Zdenek; Viljoen, Matthew; Aguilar, Fernando; Alves, Luis; Antonacci, Marica; Antonelli, Lucio Angelo; Bagnasco, Stefano; Bonvin, Alexandre M. J. J.; Bruno, Riccardo; Cetinic, Eva; Chen, Yin; Chiarello, Fabrizio; Costa, Alessandro; Pra, Stefano Dal; Davidovic, Davor; Dorigo, Alvise; Ertl, Benjamin; Fanzago, Federica; Fargetta, Marco; Fiore, Sandro; Gallozzi, Stefano; Kurkcuoglu, Zeynep; Lloret, Lara; Martins, Joao; Nuzzo, Alessandra; Nassisi, Paola; Palazzo, Cosimo; Pina, Joao; Sciacca, Eva; Segatta, Matteo; Sgaravatto, Massimo; Spiga, Daniele; Taneja, Sonia; Tangaro, Marco Antonio; Urbaniak, Michal; Vallero, Sara; Verlato, Marco; Wegh, Bas; Zaccolo, Valentina; Zambelli, Federico; Zangrando, Lisa; Zani, Stefano; Zok, Tomasz;This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications. Comment: 39 pages, 15 figures.Version accepted in Journal of Grid Computing
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