You can build a useful wildlife archive with HTML, CSS, and JavaScript by starting with a small, clearly defined set of records, then adding filters and—if it helps—an interactive map. The key is to make each entry understandable and traceable: show what it represents, where its data came from, and what reuse terms apply to any image.
Choose what an archive entry represents
Decide whether each entry is an individual observation, a species profile, or a collection of sightings. These are different kinds of information; if your archive includes more than one, label them clearly rather than presenting them as equivalent records.
Keep the first version narrow—for example, observations from one place or records for one species group. Before adding visual effects, define a consistent set of fields. A useful starting model is:
- Identification: common name and scientific name, when available.
- Observation: date and location. If exact coordinates should not be public, use a generalized location instead.
- Provenance: the source record link and original source identifier, so readers can trace an entry back to where it came from.
- Credits and reuse: observer credit when available, image credit, and the applicable license for each image.
Not every source will provide every field. Decide how the archive handles missing information, and only offer filters for fields that are present and represented consistently.
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Choose a source and start with a small sample
GBIF and iNaturalist both document ways to access records, but their data and services are not interchangeable. Pick a source based on which records suit your archive, which fields and queries you need, and whether the relevant reuse terms allow your planned display. Start with a modest sample so you can shape the data model and interface before requesting more.
| Consideration | GBIF | iNaturalist |
|---|---|---|
| Record access | Occurrence records are documented in the GBIF occurrence API reference. | Observation queries, filters, pagination, and response formats are documented in the iNaturalist API. |
| Map support | The GBIF Maps API provides web map tiles and names Leaflet as a compatible client. | The cited iNaturalist API documentation describes observation access; the material cited here does not establish an equivalent map-tile service. |
| Reuse checks | Check the terms for the specific record and any media before reuse; an occurrence record does not itself establish image permission. | The API includes photo-license filters, but verify the current license on each item and the applicable terms before displaying its media. |
| Scale and requests | The cited GBIF materials describe API access; the material cited here does not establish a request-rate figure for this comparison. | Developer guidance says the service throttles at a maximum of 100 requests per minute and asks applications to try to remain at or below 60; for large-scale data needs, it says bulk datasets may be preferable to API use. |
For the relevant documentation, see the GBIF API introduction, GBIF API reference, iNaturalist developer guidance, and iNaturalist API recommended practices. Service guidance can change, so check it again before deployment.
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Build the record list before adding a map
Render your sample as readable cards or a table. Each entry should give readers enough context to understand the record and include a link back to its source. Add filters such as species, date, or place only when those fields are available and consistently represented.
Keep the list available even if you add a map. Readers should be able to browse and understand records without relying on map interactions. Use the W3C WAI tutorials for task-oriented guidance on accessible images, tables, and interactive controls.
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Add a map as an enhancement
A map can help readers explore where observations were recorded, but it should complement—not replace—the textual or tabular archive. The GBIF Maps API supplies web map tiles and explicitly mentions Leaflet as a compatible client.
Explain what a marker represents and how its location was obtained or generalized. A visible pattern on a map does not, by itself, prove species abundance or absence; the records shown depend on the archive’s data and coverage.
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Check attribution and image licenses record by record
Observation information and photographs can have different licensing terms. iNaturalist says content remains the creator’s intellectual property and describes CC BY-NC as its default license for photos and sounds. That is not blanket permission for commercial reuse: follow the applicable license conditions, preserve attribution, and check the current license for each item before displaying its image. Public visibility or API access does not establish permission to reuse a photo. See iNaturalist’s licensing guidance and its API documentation.
Store the source and license alongside each displayed asset. This makes it easier to show credits in context and to revisit an item if its terms or your intended use require a different decision.
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Keep API use appropriate to the project
For iNaturalist, the developer guidance states a maximum of 100 requests per minute and asks users to try to stay at or below 60. It also says bulk datasets may be a better choice than API use for large-scale data needs. These are iNaturalist-specific guidelines, not general limits for every wildlife data service; review the relevant source’s current guidance before launch.
Optional learning resource
If you want a structured introduction to the mapping layer, Michael Dorman’s Introduction to Web Mapping covers HTML, CSS, JavaScript, Leaflet, GeoJSON, and interactive web mapping. Routledge describes it as teaching readers to develop interactive web maps and applications using standard web technologies. Google Books describes the book as intended for beginners without a background in web technologies or programming. It is optional; the official API documentation can be used without buying a book. See the Routledge publisher listing and Google Books catalog entry.
A 2024 paper on BioTrove describes a research dataset containing 161.9 million images spanning approximately 366,600 species. That is a figure about the dataset discussed in the paper, not a count of images available for your project or permission to reuse them. See the BioTrove paper.
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