Home > Computer Science > Data Processing > Volume-4 > Issue-4 > Extract the Analyzed Information from Dark Data

Extract the Analyzed Information from Dark Data

Call for Papers

Volume-5 | Innovative Development on Academic Research and Development during Covid 19

Last date : 27-Apr-2021

Best International Journal
Open Access | Peer Reviewed | Best International Journal | Indexing & IF | 24*7 Support | Dedicated Qualified Team | Rapid Publication Process | International Editor, Reviewer Board | Attractive User Interface with Easy Navigation

Journal Type : Open Access

Processing Charges : 700/- INR Only OR 25 USD (for foreign users)

First Update : Within 7 Days after submittion

Submit Paper Online

For Author

Research Area

Extract the Analyzed Information from Dark Data

Rahul P | Ganeshan M

Rahul P | Ganeshan M "Extract the Analyzed Information from Dark Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4, June 2020, pp.26-29, URL: https://www.ijtsrd.com/papers/ijtsrd30842.pdf

The world is surrounded by data and data, the data may be structured, unstructured, or semi-structured; every organization generates enormous data daily, only the tip of data is analyzed, and the larger the data is ignored from the utilizable analysis. This paper focuses on a particularly unstructured and bothersome class of data, termed Dark data. Dark data is not attentively analyzed, indexed, and stored, so it becomes nearly imperceptible to potential users and therefore is more likely to last neutralized and eventually lost. This paper discusses how the concepts of long-term specifically use of analyzed for all intents and purposes dark data can be used to generally understand the very possible solutions for better curation of dark data in a major way. This paper describes why this class of data is so critical to scientific progress, some of the properties of this dark data, as well as the technical difficulties to useful management of this class of data. Many probable useful institutional and technical solutions are under development which will show in this paper in the last section, but these solutions are mainly conceptual and require additional research during lack of resources.

Dark Data; Big Data Analytics, Structured Data, Unstructured Data, and Semi-Structure Data

Volume-4 | Issue-4, June 2020
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

Thomson Reuters
Google Scholer