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Kansas State University

Beach Museum Web Application

Abstract

dc:description.abstract

This project involves in developing a responsive web application for Beach Museum at Manhattan, Kansas. Application is built on development boxes using Amazon web services. Project is built on MVC architecture that helps user to search images, create their own collection from the images and include an admin module. Migrating the current existing SQL database to couchDB for better performance of the available data. Integrated Apache Lucene to support text search in the couch database writing different indexes to retrieve the results. Implementing core functionalities like basic search, advanced search, filter objects with respective to artist, decade, object type and relevance using different indexes and Mango queries in the couchDB. Search Results are further chunked and displayed to the user. Web storage API’s were used to provide the functionality for a user to create their own collection (set of Images). Built an Admin module to perform CRUD operations the database. Admin module involves in creating exhibitions, adding/editing works and artists in the couch DB.

Degree

thesis:*
Grantor dc:publisher
Kansas State University
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kakkireni, Nithin Kumar

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • © the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/2097/38797

Chain of custody

source
Harvested from
Kansas State University
Base URL
krex.k-state.edu/server/oai/request
Last updated
2026-08-21
Source record
OAI-PMH GetRecord
citation

Kakkireni, Nithin Kumar. Beach Museum Web Application. Kansas State University, 2018. http://hdl.handle.net/2097/38797