Overview

Introduction, Purpose and Scope of this Policy

This Scientific Data Policy for DECTRIS CLOUD describes the policies we apply to any type of scientific data within https://www.dectris.cloud, and/or through any of its associated applications (“Service”).

We see scientific data as the foundation for evidence based research. As such, we see it as our highest priority to safeguard scientific data by any means reasonably possible - irrespective if the user is of proprietary nature, registered or anonymous.

Furthermore, we strive to make all scientific data within our Service FAIR, that is Findable, Accessible, Interoperable and Reusable, while at the same time honoring intellectual property rights of the investigating institutions. At the same time, we make sure that industrial scientific data is treated as proprietary data and cannot be made publicly available.

In this effort, we are committed to continuously improving our practices, products and services. We have hence designated the dedicated role of a Scientific Data Officer (SDO) in order to receive feedback, improvement suggestions, address your concerns and answer questions you may have regarding this policy. You may contact our SDO at any point via our Web Application or via SDO@dectris.cloud.

This Scientific Data Policy (hereinafter the "Policy") aims to provide you with simple and clear information on how we handle scientific data, what safeguards we have in place to protect it, who is allowed to access, change and delete the data and what retention policies we have in place.

Summary of the Policy

Who owns the Scientific Data?

The Principal Investigator of an Experiment acts as legal owner or delegate of the legal owner of the respective Scientific Data. More information can be found at Scientific Roles and Responsibilities.

How long is Scientific Data stored?

Data is stored according to the chosen storage or archiving option. If data is archived, we provide options for 1, 5 or 10 years of guaranteed availability. This means that we guarantee accessibility of data over the given period - even if the DECTRIS CLOUD license is canceled. After this period it is the responsibility of the Principal Investigator to decide on extending the storage period for raw and processed data. Regardless of this decision, Metadata of Experiments will remain accessible. More information can be found at Experiment Data Lifecycle.

Who can access Scientific Data?

Any user of our Service that is linked to a specific Experiment can access all respective data. In case that data is archived Open Access, the Experiment Data is made publicly accessible via the open data portal. At this point, any public (non-registered) user can retrieve Metadata of the Experiment Data and any registered user can access the full Experiment Data (read only). Open Access is only available for Academic Data, see more information at Experiment Data Accessibility.

Is data access free?

Access to Scientific Data is free for all users, regardless of the subscription type.

How do we protect Scientific Data?

We have a range of safeguarding measures in place to ensure protection, encryption, authenticity and persistence of Scientific Data. Examples are access control, multi-location storage, data-versioning, etc. A full list of our safeguarding measures can be found at Data Safeguarding.

What are the underlying data types?

All experiment data on DECTRIS CLOUD are either academic or proprietary data. While setting up an Experiment, the data type must be chosen. Academic Data can be turned into Proprietary Data at any time, however not vice versa. The Proprietary Data type is intended for any data that is, will or may be used for commercial purposes.

How do we handle proprietary data?

Proprietary data is only accessible by users assigned by the Principal Investigator. This type of data can never be made open accessible, can not be viewed by the facility’s staff scientists 30 days after the experiment and never by any employee from DECTRIS. Read more in the according chapter Proprietary Data Handling.

Here is a brief overview of the difference in policies between academic and proprietary data:

Questions? Reach out to us here!