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  • DARIAH EU
  • 2022-2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Gnadt, Timo; Morselli, Francesca;
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    Authors: Leone, Claudio;
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publikationenserver ...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ulrich Schwardmann; Tibor Kálmán;

    FAIR Digital Objects (FDOs) are typed by a well described set of attributes, where attributes are key value pairs with a key, which refers to a syntactic description of the value. Often the description of the set of attributes is called also profile. The exact description of the attribute keys is obviously crucial for machine actionability on one hand. On the other hand an exact description of attributes can be a way to allow also human readability of the used keys. Furthermore it can often integrate legacy attribute sets that are provided inside repositories for the description of their digital objects. In the following we show two examples of FDO types with their attributes from different viewpoints. The two examples are: the Persistent Identifiers (PID) for Instruments example and the DARIAH (see https://de.dariah.eu) use case. In both cases the Handle system is used for the persistent identifiers, the FDO record is provided by the Handle record of the PID and the attributes can be found here as type-data pairs in the phrasing of the Handle system. 1 Example 1: PID for Instruments The PID for instrument example goes back to the development of kernel metadata, which is seen as minimally required to reference and describe scientific instruments Stocker et al. 2020. The value space for the attributes here often contains hierarchical objects and can also be lists of attributes. An example of such an attribute definition is that of a single manufacturer of an instrument that occurs in a list of manufacturers here: http://dtr-test.pidconsortium.eu/#objects/21.T11148/7adfcd13b3b01de0d875. 1.1. The Handle Record for a Full PID for Instruments In this case one uses the references to the attribute definitions as keys for the values, which are often lists or objects. The Handle Record for a full attribute list of a PID for Instruments can be obtained from the Handle Proxy with https://hdl.handle.net/21.T11998/0000-001A-3905-1?noredirect The structure of this FDO record is defined as a type definition at the ePIC Date Type Registry Schwardmann 2020 with http://dtr-test.pidconsortium.eu/objects/21.T11148/17ce618137e697852ea6 . This way we can also refer to this structure definition in a qualified key value pair like TYPE/0.TYPE and then use as keys in the FDO record the names as they are given for keys in this structure. This way an FDO record becomes a human readable form without loosing any machine readability. For further details see: https://hdl.handle.net/21.T11998/0000-001A-3905-8?noredirect In both cases the full instrument descriptions are completely stored in the Handle database of the Handle PID service. The PID itself is a metadata object and can be seen as an FDO of its own. 1.2. Type for a PID4Inst based on Attributes The type for such FDOs is given via proxy https://hdl.handle.net/21.T11148/17ce618137e697852ea6 in the ePIC DTR 1.3. PID4Inst in a Repository Another option is to store the metadata objects of instrument descriptions in repositories. In this case a schema is needed to describe the metadata elements that are needed for the description. The existing attribute definitions could be bundled here into a single complex definition, which is syntactically almost identical to the type definition for instruments. From such a complex definition one could derive a schema for the repository entries. In this case the schema was directly derived from the type, which is conceptually different from attribute definitions, but syntactically similar and therefore exploitable by the same services. The result of the schema derivation can then be directly fed into the ingest module of repositories, in the following figure for example into the CORDRA schema module for the definition of attribute types: https://hdl.handle.net/21.T11148/c2c8c452912d57a44117 An example of such a PID for instrument object in a repository is given at https://vm11.pid.gwdg.de:8445/objects/21.11145/8fefa88dea40956037ec 2. Example 2: The DARIAH Use Case This example evolved in the humanities in the DARIAH project about five years ago with the DARIAH repository (Kálmán et al. 2016, DARIAH-DE 2016). The Handle record structure was created far before FDO records have been discussed. It uses key value pairs with human readable keys as the type and provides relatively atomic values. For humans the key here is a description for the value space that can be expected: https://hdl.handle.net/21.11113/0000-000B-CA4C-D?noredirect The use of human readable keys does however not match the goal of machine readability of this description. Additionally it has the risk of uncertainty and ambiguity. 2.1. Attribute Definitions In order to make these attributes machine readable, attribute definitions for the allowed value spaces were needed and can be found in the ePIC data type registries. The following basic information type for an email address can be used as the reference key for the value space given for the 'RESPONSIBLE' type above for instance: https://dtr-test.pidconsortium.eu/#objects/21.T11148/e117a4a29bfd07438c1e Attribute definitions for all attributes used in the DARIAH example are given in the ePIC data type registrie. This way one is able to define a type for the DARIAH Handle records. 2.2. An FDO Type of Legacy Repository Records Such a type definition is given at: https://dtr-test.pidconsortium.eu/#objects/21.T11148/f1eea855587d8b1f66da If this type is the known type of all objects in the DARIAH repository, the references to the keys are named very similar the human readable form of the Handle record. Usually and as we have seen in the previous PID4Inst example the type of the FDO would be another attribute of the FDO. This would require an adaption of the attributes of all digital objects of the DARIAH repository. But since all digital objects of the DARIAH repository follow the same profile and all its digital objects have the same PID prefix, it would be sufficient to implement this additional attribute at the prefix level. Together with a rule that attributes on a lower level dominate attributes on a higher level, this additional prefix attribute makes FDOs out of legacy digital objects that have been defined a long time ago. 3. Presentation In the presentation we will describe based on the two examples above how machine and human readability can be supported at the same time by FDO types and discuss the implementation of hierarchical type definitions as the basic infrastructure for FAIRness of data in more detail.

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    ZENODO; Research Ideas and Outcomes
    Article . 2022 . Peer-reviewed
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    Research Ideas and Outcomes
    Article . 2022
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  • Authors: Gouet-Brunet, Valérie; Kosti, Ronak; Weng, Li;
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    Authors: Czerniak, Andreas;

    OpenAIRE Research Graph as an aggregator of CRIS systems is held during the "DARIAH Bibliographical Data WG Open Online Workshop" with the topic: Databases and information systems for research output: digital humanities outlook on September, 30th 2022. This invited talk presents the OpenAIRE Research Graph as an aggregator of Current Research Information Systems (CRIS) in a nutshell.

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    Publications at Bielefeld University
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Arnold, Matthias;

    Academic research about digital non-Latin script (hereafter: NLS) research data can pose a number of challenges just because the material is from a region where the Latin alphabet was not used. Not all of them are easy to spot. In this paper, I introduce two use cases to demonstrate different aspects of the complex tasks that may be related to NLS material. The first use case focuses on metadata standards used to describe NLS material. Taking the VRA Core 4 XML as example, I will show where we found limitations for NLS material and how we were able to overcome them by expanding the standard. In the second use case, I look at the research data itself. Although the full-text digitization of western newspapers from the 20th century usually is not problematic anymore, this is not the case for Chinese newspapers from the Republican era (1912–1949). A major obstacle here is the dense and complex layout of the pages, which prevents OCR solutions from getting to the character recognition part. In our approach, we are combining different manual and computational methods like crowdsourcing, pattern recognition, and neural networks to be able to process the material in a more efficient way. The two use cases illustrate that data standards or processing methods that are established and stable for Latin script material may not always be easily adopted to non-Latin script research data.Des recherches académiques sur les recherches de textes numériques qui ne sont pas en alphabet latin (désormais NLS) peuvent poser plusieurs défis, car le matériel vient d’une région où l’alphabet latin n’était pas utilisé. Ils ne sont pas tous faciles à trouver. Dans cet article, je vais présenter deux cas d’utilisation pour démontrer les différents aspects des tâches complexes qui pourraient être reliées au matériel NLS. Le premier cas d’utilisation focus sur les standards de métadonnées utilisés pour décrire le matériel NLS. En prenant comme exemple le VRA Core 4 XML, je montre où se trouvent les limitations pour le matériel NLS et comment nous sommes capables de les surmonter en augmentant les standards. Pour le deuxième cas d’utilisation, je regarde les données de recherches elles-mêmes. Même si la numérisation de textes complets de journaux occidentaux du 20e siècle n’est plus problématique, ce n’est pas le cas pour les journaux chinois de l’ère républicaine (1912-1949). Un obstacle majeur est la densité et la complexité de la mise en page, ce qui empêche les solutions OCR (reconnaissance optique de caractères) de se rendre à la partie de reconnaissance des caractères. Dans notre approche, nous avons combiné des méthodes manuelles et computationnelles différentes comme l’externalisation ouverte (crowdsourcing), la reconnaissance de motifs, et le réseau neuronal pour procéder au matériel de manière plus efficace. Les deux cas d’utilisations démontrent que les données standards ou les méthodes de traitement qui sont établies et stables pour le matériel en alphabet latin ne peuvent être utilisées facilement pour des données qui ne sont pas en alphabet latin. 

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    Digital Studies
    Article . 2022 . Peer-reviewed
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      Digital Studies
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    Authors: Umerle, Tomasz; Colavizza, Giovanni; Herden, Elżbieta; Jagersma, Rindert; +15 Authors

    This report has been prepared by the “Bibliographical Data” Working Group of the DARIAH-ERIC consortium, which develops public digital research infrastructure for the arts and humanities. The Group consists of more than 30 members from 15 countries, most of whom are researchers and curators in the public sector who are engaged in bibliographical data (“bibliodata”) research and curation. This report is aimed at all active stakeholders in the humanities bibliodata landscape,especially public sector entities who may benefit from the Group’s insights and engage in cooperation to identify common interests, shape joint agendas, and achieve common goals. Those goals include creating shared infrastructure solutions, harmonising existing standards, and building partnerships to meet major challenges for contemporary bibliodata stakeholders. The bibliodata landscape is a dynamic ecosystem including the many stakeholders who produce, process, and use diverse bibliographical resources (datasets, tools, services). Following the digital revolution, this landscape has been reconfigured and a critical era is now upon us that demands closer investigation. This report analyses the state of the art by defining current bibliodata (Chapter 1), mapping the contemporary landscape (Chapter 2), identifying crucial stakeholder challenges and opportunities (Chapter 3), and offering recommendations for future cooperation (Chapter 4). This report presents an overview of issues in the bibliodata landscape. It is intended to provide a foundation for more detailed reports and case studies on the issues identified in this document.

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    Authors: Jannidis, Fotis; Pernes, Stefan; Pielström, Steffen; Reger, Isabella; +2 Authors

    The DARIAH-DKPro-Wrapper Output Format (DOF) is a tab-separated file format, designed to be easily accessible by various analysis tools and scripting languages. It is based on a modular linguistic processing pipeline, which includes a range of analysis capabilities and has been fitted to book-length documents. Both processing pipeline and output format have been developed in cooperation by the Department of Literary Computing, Würzburg (“Lehrstuhl Für Computerphilologie Und Neuere Deutsche Literaturgeschichte. Universität Würzburg” 2016) and the Ubiquitous Knowledge Processing Lab, Darmstadt (“Ubiquitous Knowledge Processing Lab. Technische Universität Darmstadt” 2016) as part of DARIAH-DE, Digital Research Infrastructure for the Arts and Humanities (“DARIAH-DE” 2016).

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    Authors: Klaffki, Lisa; Schmunk, Stefan; Stäcker, Thomas;

    Digitale Forschungsansätze gewinnen zunehmend an Bedeutung. In den vergangenen Jahren wurden zahlreiche Werkzeuge und Methoden entwickelt, um die traditionellen Herangehensweisen der Geistesund Kulturwissenschaften zu ergänzen oder neue Fragestellungen zu ermöglichen. Allerdings benötigen diese Werkzeuge und Methoden eine verfügbare breite Datenbasis als Input und zwar in Form von digitalisierten Objekten des kulturellen Erbes, etwa Texte, Bilder und audio-visuelle Medien. Dieser Artikel soll zeigen, wie durch eine programmatische, nachhaltig geförderte Digitalisierung eine kritische Masse in angemessener Qualität erreicht werden kann und welche Anforderungen an diese Qualität gestellt werden müssen, damit sie den Forschungsprozessen gerecht wird. Dazu erfolgt zunächst eine Erhebung des Status Quo: einerseits zur bisherigen Digitalisierung in den Gedächtnisinstitutionen und den (fehlenden) Kennzahlen, andererseits zu den Förderaktivitäten und dem politischen Diskurs auf Bundesund Länderebene. Anschließend werden konkrete Handlungsvorschläge aus fachwissenschaftlicher und institutioneller Perspektive zu Umfängen und Herangehensweise gemacht. Aus fachwissenschaftlicher Sicht gehen die Handlungsvorschläge von den zu erforschenden Medientypen aus, daher werden zunächst konkrete Anforderungen an text- und bildbasierte Digitalisate sowie audio-visuellen Medien formuliert, aber auch Anforderungsklassen für eine medienunabhängige, allgemeine Digitalisierung abstrahiert. Da die Zweige der Gedächtnisinstitutionen – Bibliotheken, Archive sowie Museen – ganz eigene Voraussetzungen mitbringen, was die Objekte selbst, aber auch den Stand ihrer Erschließung und Digitalisierung angeht, werden diese jeweils getrennt betrachtet. Ergänzt wird dieser Teil um einige Use Cases, die beispielhaft das Potential solch einer programmatischen Digitalisierung und damit einhergehend der Erschließung von Kulturgut herausstellen.

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    Authors: Barbot, Laure; Gray, Edward J.; Fischer, Frank; Durco, Matej; +14 Authors

    Dating back to premodern times, marketplaces were community centres and hubs of activity. Merchants, officials, and regular citizens gathered not only to exchange goods, but stories - representing a multifaceted vision of what was going on in the community and the world at large. Thanks to active contributions from its national nodes, DARIAH, together with CLARIN and CESSDA, has built the SSH Open Marketplace - marketplace.sshopencloud.eu/ -, a discovery portal which pools and contextualises resources for Social Sciences and Humanities research communities: tools, services, training materials, datasets, publications and workflows. As one of the flagship DARIAH services, the SSH Open Marketplace is the result of a vision long told by different actors of the DARIAH and DH communities. Its creation has been included in the DARIAH Strategic Plan 2019-2026 and funded under the SSHOC project - sshopencloud.eu/ -, becoming as such a key component of the SSH branch of the European Open Science Cloud (EOSC) and involving partners beyond the initial scope. What kind of common story can we continue to collectively develop and tell now that the service is up and running? How can the SSH Open Marketplace support DARIAH research community storytelling and sharing while welcoming others? What are the technical choices behind the visible output that are supporting the initial vision, enabling discoverability and enhancing storytelling? These are some of the questions that the poster and demo of the SSH Open Marketplace would like to open and discuss with the DARIAH Annual Event audience. Our contribution will present how research communities can share, discover and re-use existing resources via the SSH Open Marketplace, and will demonstrate how research infrastructure services can support collective narratives. SSH Open Marketplace (meta)data With around 5 000 items at the time of its final release, the SSH Open Marketplace aggregates resources coming from or curated by the DARIAH, CLARIN and CESSDA networks and beyond. Thanks to this discovery portal, these three ERICs can showcase the productions of their national nodes, letting their story be seen in a new and contextualised way. DARIAH in-kind contributions, CLARIN Switchboard tools and Resource Families items, or CESSDA training resources are sources populating the Marketplace. Exploring, curating and re-using Thanks to its Application Programming Interface (API) and to a Python Library developed to complement its use - gitlab.gwdg.de/sshoc/marketplace-curation -, exploring, curating or re-using the SSH Open Marketplace (meta)data set takes another dimension. With a set of Jupyter notebooks accompanying the library, it is easy to analyse and to improve the data quality of the Marketplace. Context is queen! One of the added values of the SSH Open Marketplace is the contextualisation layer offered to create relations between the resources. One tool can easily be connected to a training material or a related publication. Furthermore, workflows can be used to showcase tools and standards use based on a step-by-step description of real research use-cases. Event’s participants interested in bringing their voices into the SSH Open Marketplace will be guided during the poster and demo sessions. With many thanks to TRUST-IT for the initial design of the poster.

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    Authors: Gnadt, Timo; Morselli, Francesca;
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    Authors: Leone, Claudio;
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    Authors: Ulrich Schwardmann; Tibor Kálmán;

    FAIR Digital Objects (FDOs) are typed by a well described set of attributes, where attributes are key value pairs with a key, which refers to a syntactic description of the value. Often the description of the set of attributes is called also profile. The exact description of the attribute keys is obviously crucial for machine actionability on one hand. On the other hand an exact description of attributes can be a way to allow also human readability of the used keys. Furthermore it can often integrate legacy attribute sets that are provided inside repositories for the description of their digital objects. In the following we show two examples of FDO types with their attributes from different viewpoints. The two examples are: the Persistent Identifiers (PID) for Instruments example and the DARIAH (see https://de.dariah.eu) use case. In both cases the Handle system is used for the persistent identifiers, the FDO record is provided by the Handle record of the PID and the attributes can be found here as type-data pairs in the phrasing of the Handle system. 1 Example 1: PID for Instruments The PID for instrument example goes back to the development of kernel metadata, which is seen as minimally required to reference and describe scientific instruments Stocker et al. 2020. The value space for the attributes here often contains hierarchical objects and can also be lists of attributes. An example of such an attribute definition is that of a single manufacturer of an instrument that occurs in a list of manufacturers here: http://dtr-test.pidconsortium.eu/#objects/21.T11148/7adfcd13b3b01de0d875. 1.1. The Handle Record for a Full PID for Instruments In this case one uses the references to the attribute definitions as keys for the values, which are often lists or objects. The Handle Record for a full attribute list of a PID for Instruments can be obtained from the Handle Proxy with https://hdl.handle.net/21.T11998/0000-001A-3905-1?noredirect The structure of this FDO record is defined as a type definition at the ePIC Date Type Registry Schwardmann 2020 with http://dtr-test.pidconsortium.eu/objects/21.T11148/17ce618137e697852ea6 . This way we can also refer to this structure definition in a qualified key value pair like TYPE/0.TYPE and then use as keys in the FDO record the names as they are given for keys in this structure. This way an FDO record becomes a human readable form without loosing any machine readability. For further details see: https://hdl.handle.net/21.T11998/0000-001A-3905-8?noredirect In both cases the full instrument descriptions are completely stored in the Handle database of the Handle PID service. The PID itself is a metadata object and can be seen as an FDO of its own. 1.2. Type for a PID4Inst based on Attributes The type for such FDOs is given via proxy https://hdl.handle.net/21.T11148/17ce618137e697852ea6 in the ePIC DTR 1.3. PID4Inst in a Repository Another option is to store the metadata objects of instrument descriptions in repositories. In this case a schema is needed to describe the metadata elements that are needed for the description. The existing attribute definitions could be bundled here into a single complex definition, which is syntactically almost identical to the type definition for instruments. From such a complex definition one could derive a schema for the repository entries. In this case the schema was directly derived from the type, which is conceptually different from attribute definitions, but syntactically similar and therefore exploitable by the same services. The result of the schema derivation can then be directly fed into the ingest module of repositories, in the following figure for example into the CORDRA schema module for the definition of attribute types: https://hdl.handle.net/21.T11148/c2c8c452912d57a44117 An example of such a PID for instrument object in a repository is given at https://vm11.pid.gwdg.de:8445/objects/21.11145/8fefa88dea40956037ec 2. Example 2: The DARIAH Use Case This example evolved in the humanities in the DARIAH project about five years ago with the DARIAH repository (Kálmán et al. 2016, DARIAH-DE 2016). The Handle record structure was created far before FDO records have been discussed. It uses key value pairs with human readable keys as the type and provides relatively atomic values. For humans the key here is a description for the value space that can be expected: https://hdl.handle.net/21.11113/0000-000B-CA4C-D?noredirect The use of human readable keys does however not match the goal of machine readability of this description. Additionally it has the risk of uncertainty and ambiguity. 2.1. Attribute Definitions In order to make these attributes machine readable, attribute definitions for the allowed value spaces were needed and can be found in the ePIC data type registries. The following basic information type for an email address can be used as the reference key for the value space given for the 'RESPONSIBLE' type above for instance: https://dtr-test.pidconsortium.eu/#objects/21.T11148/e117a4a29bfd07438c1e Attribute definitions for all attributes used in the DARIAH example are given in the ePIC data type registrie. This way one is able to define a type for the DARIAH Handle records. 2.2. An FDO Type of Legacy Repository Records Such a type definition is given at: https://dtr-test.pidconsortium.eu/#objects/21.T11148/f1eea855587d8b1f66da If this type is the known type of all objects in the DARIAH repository, the references to the keys are named very similar the human readable form of the Handle record. Usually and as we have seen in the previous PID4Inst example the type of the FDO would be another attribute of the FDO. This would require an adaption of the attributes of all digital objects of the DARIAH repository. But since all digital objects of the DARIAH repository follow the same profile and all its digital objects have the same PID prefix, it would be sufficient to implement this additional attribute at the prefix level. Together with a rule that attributes on a lower level dominate attributes on a higher level, this additional prefix attribute makes FDOs out of legacy digital objects that have been defined a long time ago. 3. Presentation In the presentation we will describe based on the two examples above how machine and human readability can be supported at the same time by FDO types and discuss the implementation of hierarchical type definitions as the basic infrastructure for FAIRness of data in more detail.

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  • Authors: Gouet-Brunet, Valérie; Kosti, Ronak; Weng, Li;
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    Authors: Czerniak, Andreas;

    OpenAIRE Research Graph as an aggregator of CRIS systems is held during the "DARIAH Bibliographical Data WG Open Online Workshop" with the topic: Databases and information systems for research output: digital humanities outlook on September, 30th 2022. This invited talk presents the OpenAIRE Research Graph as an aggregator of Current Research Information Systems (CRIS) in a nutshell.

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    Authors: Arnold, Matthias;

    Academic research about digital non-Latin script (hereafter: NLS) research data can pose a number of challenges just because the material is from a region where the Latin alphabet was not used. Not all of them are easy to spot. In this paper, I introduce two use cases to demonstrate different aspects of the complex tasks that may be related to NLS material. The first use case focuses on metadata standards used to describe NLS material. Taking the VRA Core 4 XML as example, I will show where we found limitations for NLS material and how we were able to overcome them by expanding the standard. In the second use case, I look at the research data itself. Although the full-text digitization of western newspapers from the 20th century usually is not problematic anymore, this is not the case for Chinese newspapers from the Republican era (1912–1949). A major obstacle here is the dense and complex layout of the pages, which prevents OCR solutions from getting to the character recognition part. In our approach, we are combining different manual and computational methods like crowdsourcing, pattern recognition, and neural networks to be able to process the material in a more efficient way. The two use cases illustrate that data standards or processing methods that are established and stable for Latin script material may not always be easily adopted to non-Latin script research data.Des recherches académiques sur les recherches de textes numériques qui ne sont pas en alphabet latin (désormais NLS) peuvent poser plusieurs défis, car le matériel vient d’une région où l’alphabet latin n’était pas utilisé. Ils ne sont pas tous faciles à trouver. Dans cet article, je vais présenter deux cas d’utilisation pour démontrer les différents aspects des tâches complexes qui pourraient être reliées au matériel NLS. Le premier cas d’utilisation focus sur les standards de métadonnées utilisés pour décrire le matériel NLS. En prenant comme exemple le VRA Core 4 XML, je montre où se trouvent les limitations pour le matériel NLS et comment nous sommes capables de les surmonter en augmentant les standards. Pour le deuxième cas d’utilisation, je regarde les données de recherches elles-mêmes. Même si la numérisation de textes complets de journaux occidentaux du 20e siècle n’est plus problématique, ce n’est pas le cas pour les journaux chinois de l’ère républicaine (1912-1949). Un obstacle majeur est la densité et la complexité de la mise en page, ce qui empêche les solutions OCR (reconnaissance optique de caractères) de se rendre à la partie de reconnaissance des caractères. Dans notre approche, nous avons combiné des méthodes manuelles et computationnelles différentes comme l’externalisation ouverte (crowdsourcing), la reconnaissance de motifs, et le réseau neuronal pour procéder au matériel de manière plus efficace. Les deux cas d’utilisations démontrent que les données standards ou les méthodes de traitement qui sont établies et stables pour le matériel en alphabet latin ne peuvent être utilisées facilement pour des données qui ne sont pas en alphabet latin. 

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    Digital Studies
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    Authors: Umerle, Tomasz; Colavizza, Giovanni; Herden, Elżbieta; Jagersma, Rindert; +15 Authors

    This report has been prepared by the “Bibliographical Data” Working Group of the DARIAH-ERIC consortium, which develops public digital research infrastructure for the arts and humanities. The Group consists of more than 30 members from 15 countries, most of whom are researchers and curators in the public sector who are engaged in bibliographical data (“bibliodata”) research and curation. This report is aimed at all active stakeholders in the humanities bibliodata landscape,especially public sector entities who may benefit from the Group’s insights and engage in cooperation to identify common interests, shape joint agendas, and achieve common goals. Those goals include creating shared infrastructure solutions, harmonising existing standards, and building partnerships to meet major challenges for contemporary bibliodata stakeholders. The bibliodata landscape is a dynamic ecosystem including the many stakeholders who produce, process, and use diverse bibliographical resources (datasets, tools, services). Following the digital revolution, this landscape has been reconfigured and a critical era is now upon us that demands closer investigation. This report analyses the state of the art by defining current bibliodata (Chapter 1), mapping the contemporary landscape (Chapter 2), identifying crucial stakeholder challenges and opportunities (Chapter 3), and offering recommendations for future cooperation (Chapter 4). This report presents an overview of issues in the bibliodata landscape. It is intended to provide a foundation for more detailed reports and case studies on the issues identified in this document.

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    Authors: Jannidis, Fotis; Pernes, Stefan; Pielström, Steffen; Reger, Isabella; +2 Authors

    The DARIAH-DKPro-Wrapper Output Format (DOF) is a tab-separated file format, designed to be easily accessible by various analysis tools and scripting languages. It is based on a modular linguistic processing pipeline, which includes a range of analysis capabilities and has been fitted to book-length documents. Both processing pipeline and output format have been developed in cooperation by the Department of Literary Computing, Würzburg (“Lehrstuhl Für Computerphilologie Und Neuere Deutsche Literaturgeschichte. Universität Würzburg” 2016) and the Ubiquitous Knowledge Processing Lab, Darmstadt (“Ubiquitous Knowledge Processing Lab. Technische Universität Darmstadt” 2016) as part of DARIAH-DE, Digital Research Infrastructure for the Arts and Humanities (“DARIAH-DE” 2016).

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    Authors: Klaffki, Lisa; Schmunk, Stefan; Stäcker, Thomas;

    Digitale Forschungsansätze gewinnen zunehmend an Bedeutung. In den vergangenen Jahren wurden zahlreiche Werkzeuge und Methoden entwickelt, um die traditionellen Herangehensweisen der Geistesund Kulturwissenschaften zu ergänzen oder neue Fragestellungen zu ermöglichen. Allerdings benötigen diese Werkzeuge und Methoden eine verfügbare breite Datenbasis als Input und zwar in Form von digitalisierten Objekten des kulturellen Erbes, etwa Texte, Bilder und audio-visuelle Medien. Dieser Artikel soll zeigen, wie durch eine programmatische, nachhaltig geförderte Digitalisierung eine kritische Masse in angemessener Qualität erreicht werden kann und welche Anforderungen an diese Qualität gestellt werden müssen, damit sie den Forschungsprozessen gerecht wird. Dazu erfolgt zunächst eine Erhebung des Status Quo: einerseits zur bisherigen Digitalisierung in den Gedächtnisinstitutionen und den (fehlenden) Kennzahlen, andererseits zu den Förderaktivitäten und dem politischen Diskurs auf Bundesund Länderebene. Anschließend werden konkrete Handlungsvorschläge aus fachwissenschaftlicher und institutioneller Perspektive zu Umfängen und Herangehensweise gemacht. Aus fachwissenschaftlicher Sicht gehen die Handlungsvorschläge von den zu erforschenden Medientypen aus, daher werden zunächst konkrete Anforderungen an text- und bildbasierte Digitalisate sowie audio-visuellen Medien formuliert, aber auch Anforderungsklassen für eine medienunabhängige, allgemeine Digitalisierung abstrahiert. Da die Zweige der Gedächtnisinstitutionen – Bibliotheken, Archive sowie Museen – ganz eigene Voraussetzungen mitbringen, was die Objekte selbst, aber auch den Stand ihrer Erschließung und Digitalisierung angeht, werden diese jeweils getrennt betrachtet. Ergänzt wird dieser Teil um einige Use Cases, die beispielhaft das Potential solch einer programmatischen Digitalisierung und damit einhergehend der Erschließung von Kulturgut herausstellen.

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    Authors: Barbot, Laure; Gray, Edward J.; Fischer, Frank; Durco, Matej; +14 Authors

    Dating back to premodern times, marketplaces were community centres and hubs of activity. Merchants, officials, and regular citizens gathered not only to exchange goods, but stories - representing a multifaceted vision of what was going on in the community and the world at large. Thanks to active contributions from its national nodes, DARIAH, together with CLARIN and CESSDA, has built the SSH Open Marketplace - marketplace.sshopencloud.eu/ -, a discovery portal which pools and contextualises resources for Social Sciences and Humanities research communities: tools, services, training materials, datasets, publications and workflows. As one of the flagship DARIAH services, the SSH Open Marketplace is the result of a vision long told by different actors of the DARIAH and DH communities. Its creation has been included in the DARIAH Strategic Plan 2019-2026 and funded under the SSHOC project - sshopencloud.eu/ -, becoming as such a key component of the SSH branch of the European Open Science Cloud (EOSC) and involving partners beyond the initial scope. What kind of common story can we continue to collectively develop and tell now that the service is up and running? How can the SSH Open Marketplace support DARIAH research community storytelling and sharing while welcoming others? What are the technical choices behind the visible output that are supporting the initial vision, enabling discoverability and enhancing storytelling? These are some of the questions that the poster and demo of the SSH Open Marketplace would like to open and discuss with the DARIAH Annual Event audience. Our contribution will present how research communities can share, discover and re-use existing resources via the SSH Open Marketplace, and will demonstrate how research infrastructure services can support collective narratives. SSH Open Marketplace (meta)data With around 5 000 items at the time of its final release, the SSH Open Marketplace aggregates resources coming from or curated by the DARIAH, CLARIN and CESSDA networks and beyond. Thanks to this discovery portal, these three ERICs can showcase the productions of their national nodes, letting their story be seen in a new and contextualised way. DARIAH in-kind contributions, CLARIN Switchboard tools and Resource Families items, or CESSDA training resources are sources populating the Marketplace. Exploring, curating and re-using Thanks to its Application Programming Interface (API) and to a Python Library developed to complement its use - gitlab.gwdg.de/sshoc/marketplace-curation -, exploring, curating or re-using the SSH Open Marketplace (meta)data set takes another dimension. With a set of Jupyter notebooks accompanying the library, it is easy to analyse and to improve the data quality of the Marketplace. Context is queen! One of the added values of the SSH Open Marketplace is the contextualisation layer offered to create relations between the resources. One tool can easily be connected to a training material or a related publication. Furthermore, workflows can be used to showcase tools and standards use based on a step-by-step description of real research use-cases. Event’s participants interested in bringing their voices into the SSH Open Marketplace will be guided during the poster and demo sessions. With many thanks to TRUST-IT for the initial design of the poster.

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