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Your first Task

Four steps in an we still haven't performed anything useful on our data. But that's about to change. In this section we will:

  • Convert our first File
  • Inspect the result on the webpage
  • Mark a ROI (Region of Interest) in our Image

Convert our first File​

We will start by converting our first file, utilizing our just reserved "Convert Omero" node. Lets perform this conversion on our first file. The one we uploaded in the previous section.

  1. Navigate to our data in the Data tab

Lets inspect our data in the Data tab. We should see our data in the Data tab. (If you are doing this part of the tutorial, on another day you might need to open the "Home", sidebar and step back one day to see your data.)

  1. Drag and Drop or right click the file we want to convert

This time in our Action menu, a new option should appear: Convert Omero. This is our first Tool Action. Lets drop on it (or click it).

  1. You are prompted with a dialog.

This dialog is our first encounter with an Arkitekt assign dialog. Assign Dialogs help us define the parameters of our analysis.This parameters will then be sent to the tool when it is executed. For our initial conversion we will not specify any parameters. So just click Assign. And lets see what happens.

  1. Inspect the progress and result.

After a few seconds you should now be prompted with a popup in the bottom right that will show you your converted image. Also an Image should have appeared in the Data tab. If you click on it you should see the image in its detail view.

What just happened?

We just performed our first conversion. We took a file from our Server and converted it to the internal Arkitekt format based on Zarr, again storing it on our server. In practicallity this meant that our "Omero" PluginApp streamed the file from the server, converted it and then uploaded the converted zarr dataset again to the server. More on that in How Assignment Works. You will notice that first conversion takes a bit longer. This is because we only start the Java process that performs the conversion when we need it. On subsequent conversions this process will already be running and the conversion should be much faster.

Lets inspect our image​

Lets inspect our image. You can do that in different ways. Either you can click on the just generated image in the Data tab. Or directly by clicking on the image when it popups in the bottom right. Additionality because Arkitekt kept track about our relationship with the old file we can also inspect the old file. And click on created image from that pane.

In this steps you will for the first time see the Arkitekt image tab. In this tab you can explore the image and associated metadata, as well as perform some really basic 2D visualitaizon of the image. You can choose different channels, and different z-planes.

Visualization within Orkestrator

Orkestrator is not meant to be a dedicated visualization tool and would rather like to integrate with other tools. For example we will later see how we can use Napari to visualize our data. We would love to integrate Viv into Orkestrator, if you are interested in that please let us know.

On Mikro next

After some lessons learned about metadata handling in Arkitekt we are currently working on a new version of "Mikro" (the storage service) that will be able to handle metadata in a more flexible way. This will also allow us to provide more advanced visualization options in the future..

Lets comment and Mark a ROI​

Besides just converting our data we can also perform some basic operations on our data. Lets start by marking a ROI on our image. Just click on the rectangle icon in the bottom left corner of the image and draw a rectangle on the image. You should see this ROI appear. This roi is now also part of our datagraph. And we can use it in the next few steps.

A few words about the Data Graph in Arkitekt:

  1. The Data Graph is a graph that describes the relationship between different data elements within Arkitekt and their metadata. As Arkitekt is designed as a modular system you are currently exploring the Data Graph of the Mikro Service. Mikro is the service that stores our microscopy data, and metadata centrally in a database and provides a unified interface to access it. You could also explore the Data Graph of the Fluss Service. This would show you how your workflows relate to each other.

  2. The Data Graph lives from interlinking data points. Here we created already a few points of interest. We have our original file, our converted file and our ROI. Currently they are linked in the following way

This graph is currently not very interesting. But you will see later how we can use this graph to perform more complex analysis.

A bit technical

The Mikro Data Graph is a graph that is backed by a relational database, and is exposed via the GraphQL API. This means that you can also query the Data Graph directly via GraphQL.

Before we start our analysis!​

Looking at our Data on the Website might be fun. But lets first inspect our Image in a GUI app of our choice. We prefer Napari, but you can also use Fiji.