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On the development of an application for the compilation of global sea level changes

Mihir Odhavji, Maria Alexandra Oliveira, João Nuno Silva

TL;DR

This work tackles the fragmentation and inaccessibility of global mean sea level variation data. It presents a web-based, relational, georeferenced application with a REST API to ingest, store, and visualize proxy data, map observations, and generate area-specific plots. The data model captures Areas, Publications, Observations, Indicators, and Vertical Land Movement, with an age-handling module that converts BP ages to AD/BC using $1950 - age$, and supports spatial queries via PostGIS. The tool enables cross-area comparisons, data export, and correction workflows for vertical land movement, offering a scalable platform for global sea level analyses.

Abstract

There is a lot of data about mean sea level variation from studies conducted around the globe. This data is dispersed, lacks organization along with standardization, and in most cases, it is not available online. In some instances, when it is available, it is often in unpractical ways and different formats. Analyzing it would be inefficient and very time-consuming. In addition to all of that, to successfully process spatial-temporal data, the user has to be equipped with particular skills and tools used for geographic data like PostGIS, PostgreSQL and GeoAlchemy. The presented solution is to develop a web application that solves some of the issues faced by researchers. The web application allows the user to add data, be it through forms in a browser or automated with the help of an API. The application also assists with data querying, processing and visualization by making tables, showing maps and drawing graphs. Comparing data points from different areas and publications is also made possible. The implemented web application permits the query and storage of spatial-temporal data about mean sea level variation in a simplified, easily accessible and user-friendly manner. It will also allow the realization of more global studies.

On the development of an application for the compilation of global sea level changes

TL;DR

This work tackles the fragmentation and inaccessibility of global mean sea level variation data. It presents a web-based, relational, georeferenced application with a REST API to ingest, store, and visualize proxy data, map observations, and generate area-specific plots. The data model captures Areas, Publications, Observations, Indicators, and Vertical Land Movement, with an age-handling module that converts BP ages to AD/BC using , and supports spatial queries via PostGIS. The tool enables cross-area comparisons, data export, and correction workflows for vertical land movement, offering a scalable platform for global sea level analyses.

Abstract

There is a lot of data about mean sea level variation from studies conducted around the globe. This data is dispersed, lacks organization along with standardization, and in most cases, it is not available online. In some instances, when it is available, it is often in unpractical ways and different formats. Analyzing it would be inefficient and very time-consuming. In addition to all of that, to successfully process spatial-temporal data, the user has to be equipped with particular skills and tools used for geographic data like PostGIS, PostgreSQL and GeoAlchemy. The presented solution is to develop a web application that solves some of the issues faced by researchers. The web application allows the user to add data, be it through forms in a browser or automated with the help of an API. The application also assists with data querying, processing and visualization by making tables, showing maps and drawing graphs. Comparing data points from different areas and publications is also made possible. The implemented web application permits the query and storage of spatial-temporal data about mean sea level variation in a simplified, easily accessible and user-friendly manner. It will also allow the realization of more global studies.
Paper Structure (27 sections, 5 figures)

This paper contains 27 sections, 5 figures.

Table of Contents

  1. introduction
  2. Background
  3. Building and Interpreting Sea levelCurves
  4. Data Representation Libraries
  5. Geographical Databases
  6. ORM
  7. Implementation
  8. Requirements
  9. Data Model
  10. Architecture
  11. Support System
  12. REST End Points
  13. Software Organization
  14. Results
  15. The application should be remotely accessible
  16. ...and 12 more sections

Figures (5)

  • Figure 1: Example of a map with coordinates of observations points (a) and the code to do represent them (b)
  • Figure 2: Example of a graph plotted with error bars (a) and the code to do represent them (b)
  • Figure 3: Unified Modelling Language of the data structures.
  • Figure 4: Graph plotted with data from only one area.
  • Figure 5: Form utilized to introduce an observation into the database.