Data Science Around the Indexed Literature Perspective
Conceptually, data science burdened with many other terms that refer to various interests about data. The terms calls the subject of learning and study as scientific fields that categorized as the basis of science, implications, and various applications a
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Data Science Research Group, Pusat Unggulan Sistem Penginderaan, Universitas Sumatera Utara, Padang Bulan, 20155 USU, Medan, Indonesia [email protected] 2 Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Sumatera Utara, Padang Bulan, 20155 USU, Medan, Indonesia Teknik Elektro, Fakultas Teknik, Universitas Sumatera Utara, Padang Bulan, 20155 USU, Medan, Indonesia Abstract. Conceptually, data science burdened with many other terms that refer to various interests about data. The terms calls the subject of learning and study as scientific fields that categorized as the basis of science, implications, and various applications about concepts, theories, or technologies related to data science. The term has a broad impact and affects the scope of work of data scientists. This paper aims to express some of the interests of the three things from the point of that literature for generating consequences. Keywords: Big data · Mathematics · Statistics Data mining · Scopus · Conditional probability
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· Computer science ·
Introduction
According to the old phrase, the past determines present, and the past and present determine the future [1,2]. All of that is related to historically recorded data [3]. Therefore, data science becomes the extraction of knowledge from high volume data [4] by using skills in computational science [5], statistics [6,7], and specialist domain knowledge of experts [8] is as a result of ongoing dissemination or a discussion that continues until today about data [9,10]. In particular, information spaces such as the internet and the Web record dissemination outcomes, and then becomes knowledge source [11]. A collection of documents, as an online corpus, is big data, where both data and information become issues in data science [12]. Scientific documents are kinds of literature [13,14], which have recorded information conveying as well as phenomena and paradigms about data or big data [15]. The track record of something in literature reveals many things: ideas, issues, spirit, and possibilities of scientific growth about that something [16], in addition to study that embrace all aspects of it in the form of reviews, which c The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 R. Silhavy et al. (Eds.): CoMeSySo 2020, AISC 1294, pp. 1051–1065, 2020. https://doi.org/10.1007/978-3-030-63322-6_91
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reveal discourse about other ideas [17]. Therefore, this paper intends to briefly express its track record as an initial review of data science starting from the basis of science, implications, applications, and consequences. The document source is the literature based on the Scopus reputable indexing database.
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Background
There are many documents on the internet. Among scientific documents that are published and then indexed have a reputation as research performance. The publication is the outcome of the research, i.e., “no research without publication.” Scopus is a reputable database indexing scient
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