Welcome to the Great Lakes Aquatic Tissue Analysis Repository (GLATAR)

This toolbox allows you to explore, visualize, and manage energy density, proximate composition, stable isotope, thiamine, fatty acid, mercury and PCB data for fish and aquatic invertebrates throughout the Great Lakes and North America.

How to Use GLATAR

1. Working with Existing Data

First, determine if you want to summarise existing data in a table ( Summarize Tab ), visualize raw data ( Scatter Plot ), or view raw data ( View Raw Data ).

Summary Statistics

1. Select a theme (e.g. calorimetry, fatty acids). For all pulldowns, hover your mouse over the box and options appear. As you become more familiar with GLATAR you can begin typing relevant text and it will autofill.
2. Select the data fields of interest for the tabular summary (e.g. ¹⁵N, total length, etc.).
3. Select the data field of interest for the frequency histogram (e.g. ¹⁵N). Only one variable can be selected at a time.
4. Apply data filters , if you wish:
   • Organism type: fish, invertebrate, other, all.
   • Species (default is all species). You can select an unlimited number of species. Begin typing relevant text and options will appear.
   • Grouping variables (e.g. water body, common name).
   • Data type: point estimates, composite samples, reported averages, coefficients from equations, or all data (data type will be reported in the summary table).
   • Waterbody (e.g. Lake Ontario, Middle Fork River, etc.). The list is constrained to locations available in the database for the above selected criteria.
5. As each selection is made the available data will be displayed in both the table and the histogram to the right.
6. You can export the tabular results from your search to Excel using the button at the bottom of the menu.

Scatter Plot

1. Select a theme (e.g. calorimetry, fatty acids). Hover your mouse over the box for options, or begin typing to autofill.
2. Select up to four grouping variables (e.g. waterbody, sex, month, etc.).
3. Select the x-variable of interest (e.g. percent water (%), total length, etc.).
4. Select the y-variable of interest (e.g. energy density, weight, etc.).
5. Apply data filters , if you wish:
   • Organism type: fish, invertebrate, other, all.
   • Species (default is all species). You can select an unlimited number of species. Begin typing relevant text and options will appear.
   • Data type: point estimates, composite samples, reported averages, coefficients from equations, or all data.
   • Waterbody (e.g. Lake Ontario, Middle Fork River, etc.). The list is constrained to locations available in the database for the above selected criteria.
6. As each selection is made the available data will be displayed in both the table and the histogram to the right.

View Raw Data

1. Select a theme (e.g. calorimetry, stable isotopes, etc.). This view also allows you to explore metadata tables (e.g. data source, location, etc.).
2. Use the search tool to query specific terms within the chosen table (e.g. a specific author or waterbody).

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2. Map

1. The map tool is a convenient way to visualise the spatial extent of data currently contained within GLATAR.
2. The viewable area of the map can be easily scaled using the buttons in the upper left .
3. Clicking on a specific dot will display the geographic name and species recorded for that location.

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3. Searching by Taxon or Source

1. A user can search GLATAR for records on a specific taxon using virtually any level of taxonomic classification (e.g. class, order, family, genus, species, common name). The search box uses smart text so as you enter characters, matching records appear. For example, typing “Alo” will list records for Alosa pseudoharengus , Ictiobus cyprinellus (Bigmouth buffalo), and Goldeneye ( Hiodon alosoides ).
2. Similarly, a user can search by data source (e.g. author, institution, journal, etc.). The more complete the entry in the search field, the more refined the result.
3. These search tools are a convenient way to quickly check if data exist for a species or by a specific author — helpful when entering new data to avoid duplication.

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4. Uploading Data

a. Data Entry Templates

Data upload uses one of two pre-defined templates. It is important not to alter the templates (e.g. add or delete fields), nor to exclude any of the underlying data tables.

1. The simple data entry template only accepts calorimetry, proximate composition, and stable isotope data with all related metadata.
2. The extended data entry template also allows the user to upload data on fatty acids, amino acids, thiamine / thiaminase, mercury, and PCBs, again with related metadata.

The following instructions apply to both templates. Fields highlighted in green are mandatory and cannot be left blank; all other fields can be left blank if no information is available.

1. The first tab is the data dictionary — fully describing all data fields with definitions, examples, and constraints.
2. The second tab is the submission record — recording who entered the data and their affiliation and contact information.
3. The third tab is the source record — including authors, institutional affiliation, publication name, related fields (volume, pages, publisher, etc.), and the DOI or ISBN.
4. The final tab is the sample record — linking back to the source record and containing both the data and a broad array of metadata fields to facilitate database queries.
5. For all tables, copy and paste of existing rows can expedite data entry where multiple records share common metadata. Where possible, enter all data types in a given row (e.g. proximate composition, stable isotope, and fatty acid data together).
6. Once data have been entered, save the file (MS Excel) to your computer.

b. Uploading Data to GLATAR

1. From the Upload Data tab in the menu, follow the on-screen instructions.
2. Use the Browse button to select the pre-populated data entry template you wish to upload. A status message will confirm the file was successfully read.
3. Click the Upload and Process button . This may take a moment depending on file size. GLATAR will validate the data against pre-defined entry standards. If a conflict is found (e.g. an unrecognised species), a message will identify the row in your template and suggest possible corrections. Taxonomic information relies on the International Taxonomic Information System (ITIS) .
   • If you encounter conflicts you cannot resolve, follow the contact information provided in the comment box at the bottom of each validation report.
4. Once your data have been validated, click the Upload button to append your data to GLATAR. Note: you will need to exit and re-enter GLATAR to see your appended data alongside pre-existing records.

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5. Additional Resources

Documentation

The Documentation pane provides brief narratives and key citations for each of the themes included in GLATAR.

About

The About pane provides information on funding, contributors, contacts, and how to cite GLATAR.

Home

The Home page provides general orientation to menus, a clickable visual taking you to related documentation pages, and general information about GLATAR.

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6–7. Interface Tips

• The three horizontal lines in the header bar hide / reveal the menu on the left side of the page.
• The fox icon on the right side of the header bar takes you to the source code on GitHub. The code is publicly available to encourage the community to explore and suggest enhancements for future incorporation into GLATAR.

Map of Locations

This panel provides an interactive map displaying the sample locations for data in GLATAR. To use, explore the map and click on each location to view the waterbody, site, species collected (i.e., common and scientific name), the name of the collector, and the data in GLATAR that was collected. The colour of each location indicates whether the sample was derived from a wild or lab organism.

Search Taxa in the Database

Use the search bar to look up the taxa that are in the database. This tab servers two purposes 1) to let the user know what species exist in the database and 2) when uploading new data, the user can check validation errors to match what species are in the database.

Upload Excel File

Instructions

1. Go to the Documentation tab or download them from the links below for either the Basic or Extended Data Template (in Excel format)


• Basic Data Entry Template - collects energy density, proximate composition, and stable isotope data.
• Basic Data Entry Template (v21)
• Extended Data Entry Template - additional fields to collect thiamine, fatty and amino acid, mercury, and PCB data.
• Extended Data Entry Template (v21)


2. Please enter your data and associated information in the data template file. This file contains multiple sheets, with the "data_dictionary” sheet defining the fields (including units and format) that you will find on other sheets. Once oriented to file format, enter your data and other information on the three remaining sheets. These sheets are the following, "tbl_submission" which collects the name of the submitter, their associated email and affiliation. All fields on this sheet are required to successfully upload to the database. The next two sheets, "tbl_sources" and "tbl_samples", first collect metadata on the source material supporting the data that is collected which can be entered in "tbl_samples."


3. Once complete, select the Excel file you would like to upload.


4. Click 'Upload & Process'. The system will run a series of validation checks and process the data to adhere to database standards.


5. Review any validation errors — these will identify the specific rows, columns, and descriptions of any issues found.


6. If the upload is successful, verify your sampling locations using the interactive map that appears.


7. Click 'Submit to Database' to finalize the upload. A confirmation message (displayed in green) will appear and you will receive a confirmation email.

Upload & Process Submit to Database

About

Funding

• This database and toolbox are funded by the Great Lakes Fishery Commission through grant number 2025_JOH_460024.

Contributors

• The following individuals provided thoughts, critiques, and design for this project with the core group being Timothy B. Johnson, James E. Breck, Steven R. Chipps, David Deslauriers, Mark W. Kershner, Charles P. Madenjian, Brent W. Metcalfe, Steven A. Pothoven, Michael D. Rennie, and Benjamin L. Hlina.


• The following individuals contributed to the database design and thoughts on the programming of the toolbox: Benjamin L. Hlina, Michael H.P. O’Brien, and Jonathan D. Pye


• The following people have assisted in testing the database and toolbox: Carolyn J. Foley, Kate M.J. Storey, Andrew Welbourne, and Mark J. Wuenschel

Code & Maintenance

• The database and toolbox are authored and maintained by Benjamin L. Hlina.


• The source code is available on GitHub: View Repository


• This app has used LLMs as a tool to assist in development, however, any code that has been generated by LLMs has been meticulously screened, edited and redeveloped. If you would like to contribute to the code that generates the toolbox, please fork the repository, create a branch within your fork, implement your suggestions, and create a pull request on the main repository for the maintainer to review. This repository will not be accepting LLM submitted PRs nor PRs that contain directly copy and pasted code from LLMs that has not be vetted and edited. Issues that are submitted by LLMs and/or copied and pasted from LLMs will be deleted and ignored, as the issuer needs to have the ability to be able to write their own issues.

Citation

• If you use this toolbox in your research, please cite appropriately using the following: [INSERT CITATION].