Academic Journal
Big Earth Data / Innovative Analysis Ready Data (ARD) product andprocess requirements, software system design,algorithms and implementation at the midstreamas necessary-but-not-sufficient precondition of thedownstream in a new notion of Space Economy 4.0- Part 1: Problem background in Artificial GeneralIntelligence (AGI)
| العنوان: | Big Earth Data / Innovative Analysis Ready Data (ARD) product andprocess requirements, software system design,algorithms and implementation at the midstreamas necessary-but-not-sufficient precondition of thedownstream in a new notion of Space Economy 4.0- Part 1: Problem background in Artificial GeneralIntelligence (AGI) |
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| المؤلفون: | Baraldi, Andrea, Sapia, Luca D., Tiede, Dirk, Sudmanns, Martin, Augustin, Hannah L., Lang, Stefan |
| بيانات النشر: | Taylor & Francis |
| سنة النشر: | 2022 |
| المجموعة: | ePLUS - Open Access Publikationsserver der Universität Salzburg |
| مصطلحات موضوعية: | Analysis Ready Data, Artificial General Intelligence, Artificial Narrow Intelligence, big data, cognitive science, computer vision, Earth observation, essential climate variables, Global Earth Observation System of (component) Systems, inductive, deductive, hybrid inference, Scene Classification Map, Space Economy 4.0, radiometric corrections of optical imagery from atmospheric topographic, adjacency and bidirectional reflectance distribution function effects, semantic content-based image retrieval, 2D spatial topology-preserving, retinotopic image mapping, world ontology (synonym for conceptual, mental, perceptual model of the world) |
| جغرافية الموضوع: | PLUS:IFFB:ZGIS |
| الوصف: | Aiming at the convergence between Earth observation (EO) Big Data and Artificial General Intelligence (AGI), this two-part paper identifies an innovative, but realistic EO optical sensory image-derived semantics-enriched Analysis Ready Data (ARD) product-pair and process gold standard as linchpin for success of a new notion of Space Economy 4.0. To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers, it is regarded as necessary-but-not-sufficient “horizontal” (enabling) precondition for: (I) Transforming existing EO big raster-based data cubes at the midstream segment, typically affected by the so-called data-rich information-poor syndrome, into a new generation of semantics-enabled EO big raster-based numerical data and vector-based categorical (symbolic, semi-symbolic or subsymbolic) information cube management systems, eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery. (II) Boosting the downstream segment in the development of an ever-increasing ensemble of “vertical” (deep and narrow, user-specific and domain-dependent) value–adding information products and services, suitable for a potentially huge worldwide market of institutional and private end-users of space technology. For the sake of readability, this paper consists of two parts. In the present Part 1, first, background notions in the remote sensing metascience domain are critically revised for harmonization across the multi-disciplinary domain of cognitive science. In short, keyword “information” is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed information-as-data-interpretation. Moreover, buzzword “artificial intelligence” is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of AGI. Second, based on a better-defined and better-understood vocabulary of ... |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | text/html |
| اللغة: | English |
| تدمد: | 2574-5417 |
| Relation: | vignette : https://eplus.uni-salzburg.at/titlepage/urn/urn:nbn:at:at-ubs:3-27224/128; urn:nbn:at:at-ubs:3-27224; https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-27224; local:99147059237403331; system:AC16703779 |
| DOI: | 10.1080/20964471.2021.2017549 |
| الاتاحة: | https://doi.org/10.1080/20964471.2021.2017549 https://eplus.uni-salzburg.at/doi/10.1080/20964471.2021.2017549 https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-27224 |
| Rights: | cc-by-nc_4 |
| رقم الانضمام: | edsbas.4009E6D9 |
| قاعدة البيانات: | BASE |
| تدمد: | 25745417 |
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| DOI: | 10.1080/20964471.2021.2017549 |