Project Data Collection - Protocols

Last Updated: May 01, 2018 09:04AM PDT

Summary: This article provides a high-level overview of the protocols available in the Project Data collection.

Covered Topics

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Protocols Overview

Note: From the Protocols tab in Pipeline Pilot Client, these protocols are available in the Examples/ScienceCloud/Project Data folder.

The example protocols for this collection are grouped into two subfolders – Tutorials and Use Cases. To get familiar with the basic concepts, run the tutorial protocols in sequence. Then, experiment with the other protocols when you have a particular use case to solve. The example protocols can easily be adapted for your particular kind of problem. If you are not able to solve your use case with any of the existing examples, let us know, so we can add other protocols in the future.


The Tutorial protocols are the first protocols you should run to familiarize yourself with the basic concepts of the Project Data collection. These examples offer a quick tour through the most common concepts of Project Data.

The protocols include:

  • 01 Connection – Protocols need to start by making a connection to the cloud. Run this example to test your cloud-based connection.
  • 02 Projects – All data is stored in some Project.
  • 03 Project to Batches – Converter components can be used to convert one type of data record to many others.
  • 04 Compounds from Batches – Given Batch objects, easily get their related compound data.
  • 05 Querying – Query Project Data to retrieve existing data.
  • 06 Register New Batches using Molecules – Registration is the process of adding new objects to Project Data. Register new batches using molecular data.
  • 07 Hit Lists – Automate the manipulation of groups of batches.


Work with the Examples protocols when you have a particular use case you need to solve. If you can find an example of your use case scenario, you can easily adapt the protocol example to help solve your problem.

The examples are grouped into several functional areas including:

  • Defining Objects – Create data records that represent new or existing Project Data objects. These can later be used for registration and updating.
  • Editing – Edit an existing data record for later update.
  • External IDs – Manage batches with external IDs (for example, third-party corporate IDs).
  • Hit Lists – Automate the manipulation of groups of batches.
  • Import and Export – Entire libraries or projects can be exported, and then re-imported as new batches.
  • Querying – Query Project Data to retrieve existing data.
  • Registering and Updating – Data is added or changed in Project Data using register and update.
  • Reporting – Each data type has a Reporting component.
  • Sample Attachments: – Analytical trace files can be attached to samples as Sample Attachments.
  • Utilities – Create export protocols that can be added to the Project Data web interface.


The Templates protocols offer solutions that can be edited and reused as sequential subtasks for defining your processes. They are configured so they can be provided to users as a Web Task or run as a protocol. The templates are grouped into two subfolders, Chemistry (for chemistry-related tasks) and Assay Results (for assay result management).

The typical template has a protocol interface with the following parameters:

  • SC Username – ScienceCloud user name.
  • SC Password – ScienceCloud password.
  • Project – Project name.
  • Library – Library name.

Project Data Collection Components

Connecting to ScienceCloud with Project Data Components

Project Data Collection Overview

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