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| dc.identifier.uri | http://dx.doi.org/10.15488/16287 | |
| dc.identifier.uri | https://www.repo.uni-hannover.de/handle/123456789/16414 | |
| dc.contributor.author | Curry, Edward
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| dc.contributor.author | Zillner, Sonja
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| dc.contributor.author | Metzger, Andreas
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| dc.contributor.author | Berre, Arne J.
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| dc.contributor.author | Auer, Sören
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| dc.contributor.author | Walshe, Ray
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| dc.contributor.author | Despenic, Marija
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| dc.contributor.author | Petkovic, Milan
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| dc.contributor.author | Roman, Dumitru
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| dc.contributor.author | Waterfeld, Walter
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| dc.contributor.author | Seidl, Robert
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| dc.contributor.author | Hasan, Souleiman
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| dc.contributor.author | ul Hassan, Umair
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| dc.contributor.author | Ojo, Adegboyega
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| dc.contributor.editor | Curry, Edward
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| dc.contributor.editor | Metzger, Andreas
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| dc.contributor.editor | Zillner, Sonja
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| dc.contributor.editor | Pazzaglia, Jean-Christophe
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| dc.contributor.editor | García Robles, Ana
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| dc.date.accessioned | 2024-02-13T08:26:16Z | |
| dc.date.available | 2024-02-13T08:26:16Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | Curry, E.; Zillner, S.; Metzger, A.; Berre, A.J.; Auer, S. et al.: Technical Research Priorities for Big Data. In: Curry, Edward; Metzger, Andreas; Zillner, Sonja; Pazzaglia, Jean-Christophe; García Robles, Ana (Eds.): The Elements of Big Data Value : Foundations of the Research and Innovation Ecosystem. Cham : Springer International Publishing, 2021, S. 97-126. DOI: https://doi.org/10.1007/978-3-030-68176-0_5 | |
| dc.description.abstract | To drive innovation and competitiveness, organisations need to foster the development and broad adoption of data technologies, value-adding use cases and sustainable business models. Enabling an effective data ecosystem requires overcoming several technical challenges associated with the cost and complexity of management, processing, analysis and utilisation of data. This chapter details a community-driven initiative to identify and characterise the key technical research priorities for research and development in data technologies. The chapter examines the systemic and structured methodology used to gather inputs from over 200 stakeholder organisations. The result of the process identified five key technical research priorities in the areas of data management, data processing, data analytics, data visualisation and user interactions, and data protection, together with 28 sub-level challenges. The process also highlighted the important role of data standardisation, data engineering and DevOps for Big Data. | eng |
| dc.language.iso | eng | |
| dc.publisher | Cham : Springer International Publishing | |
| dc.relation.ispartof | The Elements of Big Data Value : Foundations of the Research and Innovation Ecosystem | |
| dc.rights | CC BY 4.0 Unported | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
| dc.subject | Data analytics | eng |
| dc.subject | Data ecosystem | eng |
| dc.subject | Data management | eng |
| dc.subject | Data processing | eng |
| dc.subject | Data protection | eng |
| dc.subject | Data standardisation | eng |
| dc.subject | Data visualisation | eng |
| dc.subject | Research challenges | eng |
| dc.subject | User interactions | eng |
| dc.subject.ddc |
020 | Bibliotheks- und Informationswissenschaft
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| dc.subject.ddc |
004 | Informatik
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| dc.title | Technical Research Priorities for Big Data | eng |
| dc.type | BookPart | |
| dc.type | Text | |
| dc.relation.isbn | 978-3-030-68175-3 | |
| dc.relation.isbn | 978-3-030-68178-4 | |
| dc.relation.isbn | 978-3-030-68176-0 | |
| dc.relation.doi | https://doi.org/10.1007/978-3-030-68176-0_5 | |
| dc.bibliographicCitation.firstPage | 97 | |
| dc.bibliographicCitation.lastPage | 126 | |
| dc.description.version | publishedVersion | |
| tib.accessRights | frei zug�nglich |
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