> ## Documentation Index
> Fetch the complete documentation index at: https://docs.siftstack.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Step 3: Import rover data and visualize it
export const SiftIcon = ({className}) => ;
## Overview
Now that you understand how Sift organizes time-series data using Assets, Channels, and Runs, it's time to bring the preprocessed dataset into the platform and begin working with it. In this step, you will upload the Mars environmental telemetry file, define a new Asset to contain the signals, and open the data for visualization. This is your first hands-on interaction with the dataset in Sift, setting the stage for deeper inspection and analysis.
## Upload data
Start by uploading the preprocessed telemetry dataset. This step creates a new Asset in Sift that represents the Mars Environmental Monitoring Station and links it to the Channels. Once complete, Sift will index the data and make it available for exploration.
1. In **Sift**, click .
2. Click **Import data**.
3. Upload the **mars-environmental-telemetry.csv** file.
4. Click **New Asset**.
5. In the **Asset** box, enter:
```
fl_mars_env_monitoring_station
```
6. Replace `fl` with your initials (first and last name). This helps avoid naming conflicts if others are also completing the tutorial on the same Sift instance.
7. In the **Run** box (New), edit the Run name with the following:
```
fl_env_telemetry_two_thousand_twenty_one
```
8. Again, replace `fl` with your initials to ensure the Run name is unique within your workspace.
9. Click **Upload**.
10. Click **Close**
* **Timestamp column**: To prepare this dataset for analysis in Sift, the `earth_date_time` values were reformatted to follow the **rfc3339** timestamp format. Originally, entries looked like `Earth, 2022-01-26 UTC`. These were converted to a machine-readable format like `2021-12-20T00:00:00Z`, which Sift recognizes and uses for aligning time-series data.
## Visualize data
With the data uploaded and organized, you can now explore the signals visually. By selecting specific Channels like temperature and weather classification, you'll view the telemetry in both chart and table formats. This quick check helps confirm that your data imported correctly and gives you an initial sense of what’s happening across the recorded time period.
1. In the **Run name or description** box, enter the name of the Run you created earlier:
```
fl_env_telemetry_two_thousand_twenty_one
```
2. Remember to replace `fl` with your own initials if you used something different.
3. Click your Run from the search results to open it.
4. Click **Explore**.
5. In the **Channels** tab, click the following Channels:
1. **min\_ground\_temp(C)**
2. **max\_air\_temp(C)**
3. **max\_ground\_temp(C)**
4. **min\_air\_temp(C)**
5. **weather**
* **Explore**: This workspace, where the data is displayed and interacted with, is called Explore.
**Share**: The Share feature in Explore allows you to generate a link that captures the current state of the workspace. This includes selected Channels, plotted Runs, chart layout, time range, and visualization settings. Share links can be sent to others so they can open Explore with the exact same configuration, making collaboration easier and more consistent. To share the current state of Explore via a URL:
1. Click **Share**.
2. Click **Copy**