Ontologies of combining structured and unstructured data
Proposal, Research Project
Plan X to be presented on [presentation date]
[Student Name]
Option: XXXXXXXXXXXXXX
Advisor: XXXXX
This proposal is submitted to the Computer and Information Science faculty in partial fulfillment for the degree
Master of Science in Computer and Information Science.
TABLE OF CONTENTS
1. Introduction 1
1.1 Background RESEARCH 1
1.2 IDENTIFY THE PROBLEM AREA 1
2. REsearch APPROACH 2
2.1 HYPOTHESIS 2
2.2 JUSTIFICATION of research APPROACH 2
2.3 ANALYSIS APPROACH 2
3. EXPECTED RESEARCH ACCOMPLISHMENT 2
3.1 Evaluation plan of research approach 2
3.2 Significance of study 2
4. Schedule 2
REFERENCES 2
1. Introduction
Structured data is an organised data structured into rows and columns. The purpose of this is to enable machines that apply limited logic, to be able to understand and process information. The most well-known example of storing structured data and to apply operation is SQL meanwhile unstructured data is the complete opposite of this. It is everything else that isn’t in a structured format. It was never meant to be understood by machines, as this type of information has been created specifically for the purpose of being understood by a human mind. Examples would include: emails, books, letters, social media posts, images, audio & video files, etc. The most common and expensive operation on structured data is cascading and a defined schema of tables that can’t allow
The first step in finding a credible article is looking for credentials and qualifications of the authors. Each of the three authors of this article has the credentials and qualifications to write about this subject. The three researchers of this article are Zhengchuan Xu, Qing Hu, and Chenghong Zhang. Zhengchuan Xu has a Ph. D in computer software and theory. He is also an associate professor in the Department of Information Management and
The excessive use of computers has drastically changed the lives of many users. As a multifaceted tool, the computer is used for tasks to include research, homework, business related
Laudon, K. L. a. J. Management Information Systems, 12/e for DeVry University (12th ed). Pearson Learning Solutions. Retrieved from http://devry.vitalsource.com/books/9781256399933/id/ch02fig07
The Case for this module centers on an organization implementing a new computer-based information processing system. Thousands of organizations go through the same kind of process every day—you yourself may have been involved in one or more such "technology transformations." Despite this body of experience; the advice of thousands of consultants, researchers, and computer gurus; and the leverage of multibillion-dollar corporations such as Microsoft, Google, and Oracle; a large proportion of these
Data is information that is stored and organized by fields and records. A field which can also be known as an attribute is a single unit of information, like a surname of an IBM employee. A record or tuple is a collection of related fields. For example, an employee record contains all information fields that are relevant to a specific IBM employee. Additionally, a file (also known as a table) has multiple records that are pertaining to a specific topic. “To signify, an employee file of a hotel contains all employee records (Rob, 2010). Lastly, a database comprises all related files. A hotel database, among others, consists of employee files, room files, customer files, and payment files.”
Presented to Professor Michael Palley Stevens Institute of Technology MGT 772 SB Analysis and Development of Information Systems
Metadata present a more complete picture of the data in the database than the data itself.
The weakness of the relational database was unfolded by the rise of web-driven application (Lake and Crowther, 2013; Dede et al., 2013), whereas
Stair, R. & Reynolds, G. (2006). Fundamentals of Information Systems, Third ed. Chapter 1, pg. 35. Thomson Course Technology.
Submitted in partial fulfillment of the requirements for the degree of Bachelor of Engineering in Computer Engineering
Fatima Alsaleh and Samir Elmasri PhD College of Computer and Information Systems, King Saud University, Saudi Arabia
Unstructured data are the data that do not have a recognized structure, they usually contain large amount of Texts. These types of data increase the level of difficulty to
In some sense, the unstructured information is the intriguing information, however it 's hard to syn the Big information is a generally new term yet the definition demonstrates that it has been around for quite a while. Huge information is can be summed up by the three V 's, Volume, Velocity and Variety. Volume is when associations gather information from an assortment of sources, including business exchanges, online networking and data from sensor or machine-to-machine information. Prior to recent advances data storage was not the problem, but the rate at which they could process the data. For example the company Hadoop, an open source software, has combined the processes of storying the data and processing it. “Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed.”(Wiki 1) The speed of information streams in at a remarkable speed and is managed in an efficient way that is necessary in today’s world. RFID labels, sensors and keen metering are driving the need to manage deluges of information in close ongoing. The diverse assortment of Data comes in a wide range of organizations – from organized, numeric information in conventional databases to unstructured content reports, email, video, sound, stock ticker information and money related exchanges. ("What Is Big Data?"; 1)
This article is taken from the journal titled Information Technology and Libraries (ITAL). ITAL is the official scholarly peer reviewed journal of the Library and Information Technology Association (LITA), a division of the American Library Association (ALA). This journal reviews and publishes articles in the following areas related to library automation, the Internet and other aspects of information technology (American Library Association, 2015).
Department of Information Technology, Oriental Institute of Science & Technology, Thakral Nagar, Opp. Patel Nagar, Raisan Road, Bhopal. E-mail:- dhananjaykumar08083@gmail.com