- Google Timeline Visualizer turns exported location files into maps, routes, visits, and activity views.
- Privacy-first processing keeps visualization in your browser unless you choose an optional cloud import.
- Supported files include Records.json, Semantic Location History, and newer phone timeline exports.
- Best workflow is export, verify the file format, upload locally, filter by year, and review the map.
- Video output can transform selected journeys into cinematic route animations without preserving the source file.
What the Google Timeline Visualizer Does
The google timeline visualizer is a browser-based tool for exploring Google location history after the data has been exported. Instead of relying on a Google account or the discontinued web timeline interface, you load JSON files from your own device and inspect them through a calendar, map, and day-by-day activity view.
The tool is designed for retrospective analysis. It can reveal daily commutes, place visits, walking routes, driving segments, cycling activity, transit patterns, and long-distance travel. A year filter helps separate older records from recent activity, while map markers and paths make raw coordinate data easier to understand.
Video Highlights:
- Local parsing of fragmented Google Timeline export formats
- Coordinate normalization for older and newer JSON structures
- Noise filtering for inaccurate GPS spikes
- Great-circle interpolation for long-distance routes
- Cinematic rendering for selected travel histories
The visualizer is especially useful because Google moved Timeline data toward on-device storage by 2026. Users who still have historical exports can recover a readable view of their own movement history, even when the browser version is unavailable.
| Capability | What it provides | Best use |
|---|---|---|
| Calendar view | Date-based browsing and daily summaries | Finding a specific trip or day |
| Interactive map | Points, routes, and visited places | Reviewing geographic movement |
| Activity filters | Walking, driving, cycling, and transit segments | Comparing travel modes |
| Year filter | Year-by-year data selection | Studying long-term patterns |
| Route rendering | Animated travel visualization | Creating a private travel video |
Explore
Review individual points, paths, place visits, arrival times, and departure times from exported history.
Filter
Narrow large archives by year or selected periods to keep the browser responsive and improve readability.
Preserve
Use local files to inspect personal location history without depending on a continuing Google web interface.
Begin with one small JSON export before loading a multi-year archive. This confirms that your file format is recognized and makes troubleshooting easier.
Supported Google Timeline File Formats
Google Timeline data has changed structure over time, so a successful workflow starts with recognizing the file you have. Older exports may contain a large flat array of raw GPS records, while newer phone exports organize information into semantic segments and timeline paths.
The visualizer can detect multiple formats and can accept several files at once. Uploading related monthly or device exports together may help rebuild a broader history, but keep the original files unchanged so you always have a clean backup.
| File type | Typical contents | Useful for |
|---|---|---|
| Records.json | Raw GPS records using E7 coordinate values | Detailed point-by-point location review |
| Semantic Location History | Monthly place visits, addresses, and activity segments | Readable trips and activity summaries |
| Phone Timeline Export | Newer timeline paths and semanticSegments data | Recent mobile-generated history |
| Settings | Export preferences and supporting metadata | Context for the archive |
| TimelineEdits | Manual corrections and edited timeline details | Reviewing changes to recorded places |
Records.json Versus Semantic History
Records.json is often the largest file because it may contain individual location pings across a long period. These records can be precise but noisy. A phone indoors, near tall buildings, or in an area with weak reception may generate an inaccurate point far from the actual location.
Semantic Location History is more descriptive. It may identify places, addresses, and activity segments rather than presenting every raw coordinate. This makes it easier to understand a day’s movement, although the available detail depends on what Google captured and what survived in the export.
Newer phone exports may combine both concepts through nested arrays, timeline paths, and semantic segments. The automatic format detector reduces the need to manually convert every file before viewing it.
| Format characteristic | Older export pattern | Newer export pattern |
|---|---|---|
| Coordinates | Flat E7 integer values | Nested location and path structures |
| Time values | Legacy timestamps | Standard ISO-style timestamps |
| Activity data | Fewer semantic labels | Place visits and activity segments |
| File organization | Large consolidated records | Monthly or phone-generated files |
| Processing need | Coordinate parsing and cleanup | Schema detection and normalization |
Do not edit or overwrite exported JSON files before visualization. Keep an untouched backup, because manual changes can remove fields needed for parsing or later migration.
Privacy, Browser Processing, and Network Details
Privacy is a central reason to use an independent visualizer. The referenced browser tool states that visualization happens locally in JavaScript, so the uploaded files remain on the device during ordinary viewing and are discarded when the browser tab is closed. The optional “Save to my Dawarich account” action is different because it uploads the selected file for cloud import.
Local processing does not mean that every network request disappears. Map tiles may come from an external map server so the application can draw roads, borders, and geographic context beneath your routes. A tile request can expose an IP address and the approximate region represented by the requested map area.
| Privacy area | Local visualizer behavior | User action |
|---|---|---|
| JSON parsing | Performed in the browser | Use a trusted device and updated browser |
| Source file storage | Not retained after ordinary tab use, according to the tool description | Close the tab after reviewing sensitive data |
| Optional cloud import | Sends the chosen file to the associated cloud account | Use only when persistent import is intended |
| Map tiles | May require requests to an external tile provider | Read the consent notice before loading maps |
| Video rendering | Can occur locally in device memory or local software | Save the final video only where appropriate |
The practical privacy model is therefore “local-first,” not “offline in every respect.” Users should review consent notices before the first map loads and understand whether the selected tool requests third-party map imagery.
For highly sensitive archives, consider these precautions:
- Use a personal computer rather than a shared or public machine.
- Keep browser extensions that inspect page content to a minimum.
- Avoid cloud-import controls unless you specifically want persistent storage.
- Disconnect from unrelated accounts while reviewing the archive.
- Delete temporary videos and duplicate exports when the project is finished.
The safest routine is to inspect files locally, avoid optional cloud import, review map-tile consent, and close the session when your analysis is complete.
Step-by-Step Visualization Workflow
Follow this workflow to turn a raw Google export into a readable map or travel animation. The process works best when you separate data preservation from experimentation: keep the archive safe, then use copies for filtering and rendering.
Export Your Timeline Data
Use an available Google export method in 2026. Options may include Google Takeout, the Google Maps Timeline export flow on Android, or the corresponding export setting on iOS. Save every resulting JSON file in a clearly labeled folder.
Create a Backup Copy
Make an untouched backup before opening or modifying anything. Work from a duplicate so failed conversions, accidental edits, or incomplete downloads do not affect the original archive.
Load the JSON Files
Open the visualizer in a modern browser and drop one or more supported JSON files into the upload area. The tool detects older Records.json files, semantic monthly files, and newer phone timeline structures.
Filter and Inspect the Map
Choose a year or date range, then review points, paths, places, and activity segments. Check suspicious spikes against nearby records before treating them as real travel.
Render or Preserve the Result
Use the map for interactive review, or create a route video when you want a shareable visual record. Keep the source archive separate from the finished MP4 and remove temporary copies when appropriate.
The tool is designed to handle large datasets in batches. The referenced implementation has been tested with more than 630,000 location points spanning over 15 years, although processing time depends on hardware, browser memory, file size, and the complexity of the export.
For long-distance flights or other gaps between points, a cinematic renderer may use great-circle interpolation. This calculates a curved shortest path over the globe rather than drawing an exaggerated straight line across a flat map. A stable camera boundary can also reduce abrupt map movement while a route marker travels through the scene.
| Workflow stage | Main output | Quality check |
|---|---|---|
| Export | JSON archive | Confirm files finish downloading |
| Backup | Untouched source copy | Store separately from working files |
| Detection | Recognized schema | Check that dates and coordinates appear |
| Filtering | Focused map view | Look for GPS spikes and missing periods |
| Rendering | Interactive map or MP4 | Verify route direction and timing |
Before You Start:
- Save an untouched copy of every exported JSON file
- Confirm the browser recognizes the selected file format
- Review privacy and map-tile consent notices
- Filter by year before analyzing a large archive
- Check unusual GPS jumps against surrounding records
For a large archive, begin with a single year or month. Once the format and browser performance look correct, add more files in batches.
Troubleshooting, Alternatives, and FAQ
A visualizer is ideal for retrospective viewing, but it is not a permanent tracking database. After the data is read and a result is rendered, the session is intended to remain temporary. It does not automatically collect new daily movements or append future GPS records.
If you need continuous storage and long-term analytics, a self-hosted spatial database such as Dawarich follows a different model. It can act as persistent infrastructure for ongoing location logging, browser analytics, heat maps, distance calculations, and migration utilities. A practical setup may use persistent storage for daily history and the local visualizer for selected cinematic journeys.
| Need | Recommended approach | Reason |
|---|---|---|
| Inspect an old export | Browser visualizer | Fast, local-first retrospective review |
| Find a forgotten place | Year filter and place markers | Easier than reading raw JSON |
| Create a travel animation | Route video renderer | Produces a visual journey record |
| Track future movement | Self-hosted spatial database | Supports persistent collection |
| Convert or merge archives | Dedicated migration utilities | Helps manage schema differences |
Common Problems
The map is blank: Confirm that the file contains recognized coordinates and that map tiles are permitted to load. A valid JSON file can still use an unsupported structure or contain metadata without location records.
The route jumps across the map: Inspect raw GPS points for signal noise. Indoor positioning, urban density, and weak reception can create isolated spikes. Filter the display rather than changing the original file.
Some dates are missing: Check whether you exported all monthly files, whether a phone migration was completed, and whether older cloud data remained available. A visualizer can display what exists in the archive, but it cannot recreate deleted records.
The browser slows down: Start with a smaller date range, close unnecessary tabs, and load files in batches. Large archives require more memory, especially when many paths and markers are visible together.
For additional context, see the Google Timeline Visualizer tool for its supported formats, browser-processing explanation, export instructions, and large-file guidance.
A viewer can restore access to exported history, but it cannot recover data that was never backed up or was removed before the export was created.
Q: What is a Google Timeline Visualizer?
It is a browser-based tool that reads exported Google location-history JSON files and displays routes, places, activity segments, dates, and map views without requiring the Google web timeline.
Q: Is it safe to upload Google Timeline data?
The referenced visualizer processes ordinary visualization in the browser, keeping the file on your device during the session. The optional cloud-import action is different because it uploads the selected file. Review privacy notices and use the local workflow when privacy is the priority.
Q: What files can I use?
Supported data can include Records.json, Semantic Location History monthly files, newer Phone Timeline Export files, and related Settings or TimelineEdits metadata. The tool can detect multiple formats and combine several files.
Q: Can I view years of location history at once?
Yes, large archives can be processed in batches, and the referenced tool has been tested with more than 630,000 points spanning over 15 years. Start with a smaller year range if your browser becomes slow.
Before sharing a map screenshot or MP4, check whether it reveals home addresses, workplaces, recurring routines, or other sensitive location patterns.