diff --git a/.env b/.env
deleted file mode 100644
index 1a63eef..0000000
--- a/.env
+++ /dev/null
@@ -1,2 +0,0 @@
-USER_ID=1000
-GROUP_ID=1000
diff --git a/README.md b/README.md
index f8b8487..1a974cc 100644
--- a/README.md
+++ b/README.md
@@ -46,7 +46,7 @@ install [docker][docker] and [docker-compose][compose].
 If you **don't want to use docker** and install `puma` locally you might want
 to visit the [Installation Instructions](./INSTALL.md)
 
-### 1) Datasets
+### 1) Setting up the environment
 
 First, you need to indicate where are all your datasets, for doing so just:
 
@@ -61,6 +61,14 @@ So far we've only tested our approach on the [KITTI Odometry
 benchmark][kitti] dataset and the [Mai city dataset][mai-city]. Both
 datasets are using a 64-beam Velodyne like LiDAR.
 
+Then you need to expose your `user id` and `group id` to have access to the
+artifacts of the pipelines:
+
+```sh
+export UID
+export GID
+```
+
 ### 2) Converting from `.bin` to `.ply`
 
 All our apps use the [PLY][ply] which is also binary but has much
diff --git a/docker-compose.yml b/docker-compose.yml
index 9a2589a..a628895 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -11,8 +11,8 @@ services:
       context: .
       dockerfile: docker/apps/Dockerfile
       args:
-        USER_ID: ${USER_ID:-0}
-        GROUP_ID: ${GROUP_ID:-0}
+        USER_ID: ${UID:-1000}
+        GROUP_ID: ${GID:-1000}
     working_dir: /apps
     volumes:
       - ./apps/:/apps:rw