Abstract
The big data concept was introduced with the description and enumeration of online data sources. The importance of the big data was highlighted to help professionals and beginners to plan field work and research. The techniques that apply numerical methods to analyze huge dataset set were shown with adequate examples. The process of developing indigenous environmental model using computational techniques was explained with a C++ exercise.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Networks and Systems |
| Publisher | Springer |
| Pages | 79-155 |
| Number of pages | 77 |
| DOIs | |
| Publication status | Published - 2020 |
| Externally published | Yes |
Publication series
| Name | Lecture Notes in Networks and Systems |
|---|---|
| Volume | 58 |
| ISSN (Print) | 2367-3370 |
| ISSN (Electronic) | 2367-3389 |
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Lecture Notes in Networks and Systems. Springer, 2020. p. 79-155 (Lecture Notes in Networks and Systems; Vol. 58).
Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
TY - CHAP
T1 - Modeling Big Data and Further Analysis
AU - Emetere, Moses Eterigho
AU - Akinlabi, Esther Titilayo
N1 - Funding Information: profit University Corporation for Atmospheric Research (UCAR) and funded by the National Science Foundation (NSF) was intended to furnish the climatic research network with the mutual assets important to take a shot at the most imperative logical issues of the day. The job specification of NCAR include: Funding Information: DATA.GOV—Environmental Data Sources (https://catalog.data.gov/dataset/ environmental-data-sources). This database incorporates measuring stations, climatic server farms, and storet destinations. The sources of its information are sourced from: KGSWL—Water level wells in the KGS and USGS databases; National Climatic Data Center (NCDC)—Weather information gathering locations; EPAKS—All STORET (EPA database) that accounts for STORET database in 25 locations. STORET is a user-maintained database; USGSSW— USGS Surface Water measuring/gauging stations; NOAA—where the U.S. Hourly Precipitation Data can be found. UN Environment—has different sites where environmental data can be found. The State of Food and Agriculture can be found in the link—http://www.fao. org/faostat/en/. This site has the most recent dataset of seventy-four countries. The second site borders on the Advancement on sanitation and drinking— drawn from MICS and DHS studies in 25 sub-Saharan African nations and other parts of the world (http://mics.unicef.org/surveys). The third environment site in the ambient air pollution dataset for the continents of the world. It can be found in the web link—http://www.who.int/phe/health_topics/outdoorair/ databases/AAP_BoD_results_March2014.pdf?ua=1. Centre for Environmental Data Analysis (CEDA) is a United Kingdom association that serves the environmental science network by arrangement of data center, information examination, information access and research venture interest. CEDA obligation incorporates three datacentres mutually supported by the Natural Environment Research Council (NERC) and the Science and Technology Facilities Council (STFC). CEDA is in charge of giving access to investigate data. The link to the data is given as http://www.ceda.ac.uk/. Chinese Ecosystem Research Network (CERN) is an ecosystem research network with field stations throughout China covering the fields of agriculture, forest, grassland, lake and marine ecosystems. The link to the data is given as http://www.cern.ac.cn/0index/index.asp. The objectives of the CERN include Publisher Copyright: © 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - The big data concept was introduced with the description and enumeration of online data sources. The importance of the big data was highlighted to help professionals and beginners to plan field work and research. The techniques that apply numerical methods to analyze huge dataset set were shown with adequate examples. The process of developing indigenous environmental model using computational techniques was explained with a C++ exercise.
AB - The big data concept was introduced with the description and enumeration of online data sources. The importance of the big data was highlighted to help professionals and beginners to plan field work and research. The techniques that apply numerical methods to analyze huge dataset set were shown with adequate examples. The process of developing indigenous environmental model using computational techniques was explained with a C++ exercise.
UR - http://www.scopus.com/inward/record.url?scp=85078113393&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-36207-2_4
DO - 10.1007/978-3-030-36207-2_4
M3 - Chapter
AN - SCOPUS:85078113393
T3 - Lecture Notes in Networks and Systems
SP - 79
EP - 155
BT - Lecture Notes in Networks and Systems
PB - Springer
ER -