OceanMappingDataframe - Scalable multi-indexed dataframe for hydrography

dc.contributor.advisorChurch, Ian
dc.contributor.advisorRay, Suprio
dc.contributor.authorGandhi Kalidasan, Vishwa Barathy
dc.date.accessioned2023-10-26T18:14:09Z
dc.date.available2023-10-26T18:14:09Z
dc.date.issued2023-02
dc.description.abstractOcean data constitutes one of the largest geospatial datasets. Due to developments in the field of multibeam sonar, the amount of data gathered from hydrographic surveys is growing, causing the data to fall into the category of massive spatial data. Dataframe is a popular data model used to represent the data and is widely used in data science applications. Due to the lack of a suitable dataframe that can load large volumes of multibeam sonar data and support advanced analytics libraries, in this thesis, a new multi-indexed dataframe, OceanMappingDataframe, is introduced that can be used to load, store, and analyze multibeam sonar data. The multi-indexed dataframe was implemented using the MODIN dataframe library. The multi-indexed dataframe can load the hydrography files in Generic Sensor Format (GSF) or CSV file format, and save the results in partitioned Parquet files. The multi-indexed dataframe can also support advanced AI libraries such as OpenAI. This has been demonstrated by applying the Reinforcement Learning (RL) algorithm to an outlier detection problem in hydrography.
dc.description.copyright© Vishwa Barathy Gandhi Kalidasan, 2023
dc.format.extentxiv, 101
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC)1419291325en
dc.identifier.otherThesis 11145en
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37508
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.relationUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.subject.lcshOcean.en
dc.subject.lcshSonar.en
dc.subject.lcshGeospatial data.en
dc.subject.lcshHydrography.en
dc.subject.lcshDatabase management.en
dc.titleOceanMappingDataframe - Scalable multi-indexed dataframe for hydrography
dc.typemaster thesis
oaire.license.conditionother
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Vishwa Barathy Gandhi Kalidasan - Thesis.pdf
Size:
7.24 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.13 KB
Format:
Item-specific license agreed upon to submission
Description: