This code creates a dashboard where users are able to visualize data from ACAP-St. John's Community-Based Water Monitoring Program Dataset. It allows users to visualize trends for multiple sites in the Water Monitoring Program per parameter. Users get to choose the parameter and the sites they want to visualize. Additionally, users can also access the ArcGIS embeddment of this data which shows fish species sightings for most of the sites from the Program and heatmaps for the water quality parameters. The last functionality of this dashboard explains scientific terms and the evaluation of various visualizations for one site (Cold Brook) in the dataset.
The code is written in Python, with implementation from the Plotly library for graphical implementation and Dash for HTML/CSS bindings through Python.
We hope to incorporate further graphical visualizations, especially for fish data, and have record counts shown for each site and parameter. We also hope to be able to give access to data from specific sites and parameters that are chosen by users. We also want to connect our platform with DataStream and other datahubs so users are able to pull data from these sites and visualize them on our platform. We also hope to have Water Quality Reports generated for all sites and show data pulled from other datahubs on our ArcGIS feature.
To start this dashboard, clone or download this repository as is and run the dashboard.py file in the terminal. A local version of the dashboard will open on your localhost:8050, which can be copied to your browser's search tab and used. This dashboard is also hosted to be publicly available at https://ridhee.pythonanywhere.com/.
To know how to use this dashboard, please follow this video link that gives a detailed demo:
Demovid.ELA.mp4
This project was created by Nick Cheng, Ridhee Gupta, and Manuel Ron Lleras as part of IISD-ELA's Hackathon: Hacking the World's Freshwater Laboratory. The following website, titled, Develop Data Visualization Interfaces in Python with Dash, by Real Python, was also used as a reference to build the dashboard: https://realpython.com/python-dash/. There were other sources used to aggregate fish data. These sources can be found in the reference list below.
Castillo, D. (2023, Feb 20). Develop Data Visualization Interfaces in Python with Dash. Real Python. https://realpython.com/python-dash/
Clark, D., Emberley, J. (2021). MARITIMES SPRING RESEARCH VESSEL SURVEY [Data Set]. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/fecf045a-95a2-4b69-8a40-818649a62716
Ecosystems and Oceans Science, Fisheries and Oceans Canada. (2020). Stock Status Update of 4VWX Herring for the 2019/2020 Fishing Season. https://publications.gc.ca/collections/collection_2020/mpo-dfo/fs70-7/Fs70-7-2020-050-eng.pdf
Fishing Spots, Fishing Reports and regulations in Saint John River. (n.d.). Fishbrain. Retrieved October 30, 2023 from https://fishbrain.com/fishing-waters/OceZhYGP/saint-john-river
Science, Fisheries and Oceans Canada. (2009). Use of the Lower Saint John River, New Brunswick, as Fish Habitat During the Spring Freshet. https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/338079.pdf
St. John River. (n.d.). Angler's Atlas. Retrieved October 30, 2023 from https://www.anglersatlas.com/place/724844/st-john-river
The Saint John River Basin Board. (1973). Fishes of the Upper and Middle St. John River. https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/21510.pdf
This project is covered under MIT Open License.