Situngkir, Hokky (2015): Indonesia embraces the Data Science. Published in: SEAMS 7th Conference, Jogjakarta, Indonesia
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Abstract
The information era is the time when information is not only largely generated, but also vastly processed in order to extract and generated more information. The complex nature of modern living is represented by the various kind of data. Data can be in the forms of signals, images, texts, or manifolds resembling the horizon of observation. The task of the emerging data sciences are to extract information from the data, for people gain new insights of the complex world. The insights may come from the new way of the data representation (function of R(x) over data x), be it a visualizations, mapping, or other. The insights may also come from the implementation of mathematical analysis and/or computational processing (function A(x) over data x) giving new insights of what the states of the nature represented by the data. Both ways implement the methodologies reducing the dimensionality of the data. The relations between the two functions, R(x) and A(x) are the heart of how information in data is transformed mathematically and computationally into new information. The paper discusses some practices, along with various data coming from the social life in Indonesia becoming the variables within R(x) and A(x) to gain new insights about Indonesia in the emerging data sciences. The data sciences in Indonesia has made Indonesian Data Cartograms, Indonesian Celebrity Sentiment Mapping, Ethno-Clustering Maps, social media community detection, and a lot more to come, become possible. All of these are depicted as the exemplifications on how “data science” has become integral part of the technology bringing data closer to people.
Item Type: | MPRA Paper |
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Original Title: | Indonesia embraces the Data Science |
English Title: | Indonesia embraces the Data Science |
Language: | English |
Keywords: | data science, complexity, big data, indonesia, network, cartogram, social media, econophysics |
Subjects: | B - History of Economic Thought, Methodology, and Heterodox Approaches > B4 - Economic Methodology C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics C - Mathematical and Quantitative Methods > C5 - Econometric Modeling C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C54 - Quantitative Policy Modeling C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C55 - Large Data Sets: Modeling and Analysis C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs G - Financial Economics > G0 - General I - Health, Education, and Welfare > I2 - Education and Research Institutions M - Business Administration and Business Economics ; Marketing ; Accounting ; Personnel Economics > M0 - General Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology |
Item ID: | 66048 |
Depositing User: | Hokky Situngkir |
Date Deposited: | 31 Aug 2015 08:50 |
Last Modified: | 30 Sep 2019 03:42 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/66048 |