Note:
UMCs may well provide their own local tools/software and may not need HRI for basic onboarding in the HRI Catalogue.
If HRI does want to offer a tool for filling in the Metadata schema (core/petals):
CEDAR will not be used (discussed 24-10-2023, Marianne)
Data Stewardship Wizard (DSW) could maybe be used (Suggestion Rob Hooft).
Keep in mind that if the scenarios mention the DSW this could be another tool. No choice has been made.
Question for UMC: What do you expect from HRI regarding 1) onboarding of datasets in the HRI Catalogue and 2) generally making data FAIR.
Maybe this works:
General Guidance Scenarios
Actor needs information / knowledge
Involves HRI reference pages (such as metroline) and knowledge bases
If more help is needed, the actor contacts HRI Servicedesk
It then becomes a Targeted Guidance Scenario
Targeted Guidance Scenarios - Involves HRI Servicedesk / experts
Someone contacts HRI Servicedesk with a request for help
General Guidance Scenarios
Onboarding Datasets in the Health-RI Catalogue
Publish the information about the dataset - Metadata: Core, Core+Petals, Core(+Petals)+Custom
Using a form-based system
Core
Core + Petals
Technical semi-automated (running scripts etc)
Core
Core + Petals
Core (+ Petals) + Custom
Making Data FAIR - Starting from Scratch
Clinical Data - How do you make your Clinical Data FAIR from Scratch?
Build Clinical Dataset in Castor EDC and Publish it in Castor's FAIR Data Point
V1: Simple, couple of fields
V2: How about we show the steps involved in setting up VASCA?
V3: Build Cancer Clinical Dataset using some form of predefined items (Plateau 2 if I recall correctly)?
Some other ideas:
Publish the metadata it in a different FDP? Data in some triple-store?
Multi-lingual - build an English and a Dutch dataset in Castor, publish them both, query them
Different EDC, e.g. REDCap? Does it need a scenario or perhaps we can list relevant changes if there are few?
Omics Data - How do you make Omics data FAIR from Scratch?
Build Simple Omics Dataset
Genomics, Proteomics, etc. These could all have a separate scenario if necessary and we could then link to metroline pages for e.g. recipes on how to tackle the specific problem.
Imaging Data
No Idea how this works
… Data
Build Simple …
Transform …
Making Data FAIR - Existing Data
Clinical Data - How do you transform existing non-FAIR Clinical Data to be (more) FAIR?
Make an existing non-FAIR clinical dataset more FAIR
Omics - How do you transform existing non-FAIR Omic data to be (more) FAIR?
Make an existing non-FAIR omics dataset more FAIR
Imaging Data - How do you transform existing non-FAIR Imaging data to be (more) FAIR?
…
… Data
Transform …
Targeted Guidance Scenarios
This will probably follow this type of structure:
User contacts Servicedesk via a Form on the HRI website
Servicedesk does some form of intake
(maybe confirm whether the solution is not already available as general guidance)
Necessary HRI experts get involved
Necessary next steps are decided
etc
(We need to keep track of the question / solution to see whether the question+solution occur more often and could be turned into a general guidance)
Stop reading here… Below is information which probably has to be incorporated in the above. It also serves as scratch and contains previous ideas.
Scenarios - Making data Findable in the National Health-RI Catalogue
The first set of scenarios aim at a Researcher making an existing research dataset Findable in the Health-RI catalogue.
Proposal: have two main solutions. To stick with the Metroline Analogy: a Basic and an Advanced Track:
Basic Track - A fillable form-based solution, such as CEDAR or the DSW
Most researchers will probably want to have a solution that takes little effort, but does meet the requirements imposed by employers, funders, etc.
Health-RI provides easy to use forms with mandatory and optional fields as required by (initially) the core metadata schema and (later) extended metadata schemas
Forms must have guidance to help researchers properly fill in the necessary data. Guidance could e.g. be (sections of) metroline pages
Output should be something suitable for a FAIR Datapoint or Catalog (harvestable by Health-RI)
Maybe provide the output directly to an FDP as an export option?
E.g. You’re an Amsterdam UMC researcher it could suggest an Amsterdam UMC preferred FDP
It would need some form of quality control / permission before the “ok, send it” button could be pressed?
Advanced Track - A manual solution [Dena: Advance track cannot be fully manual]] So I am wondering as we previously discussed we need to have a scenario where we define semi-automatic approach for extracting data, mapping and transformation and api creation]]
The Basic Track does not meet your demands or you just prefer to do it manually
Health-RI provides guidance (knowledge, references, recipes, perhaps scripts/software where possible)
Core can probably have a follow-along example; for extended maybe pick one extension for a follow-along example
Metadata elements outside of the core and extensions should have clear guidance where possible with also recipes for domain specific problems.
If custom things can be generalised to apply to e.g. more domains, that would be better
Also, it may be useful to keep track of custom items? If lots of projects add the same custom item, it could be useful to add it to a new version of core.
Scenario List
Basic Track
BT1 - Make Simple Dataset Findable using Datastewardship Wizard - Core
BT2 - Make Simple Dataset Findable using Datastewardship Wizard - Core + Extension
BT3 - Make Simple Dataset Findable using Datastewardship Wizard - Core (+ Extension) + Custom
Probably Unfeasible: custom does not seem realistic in a DSW approach as HRI would need to create new forms for every project with custom items
Advanced Track
AT1 - Make Simple Dataset Findable using Semi-automatic approach - Core
AT2 - Make Simple Dataset Findable using Semi-automatic approach - Core + Extension
AT3 - Make Simple Dataset Findable using Semi-automatic approach - Core (+ Extension) + Custom
Some of these scenarios are probably too big for being contained in a single scenario. Potentially the current titles should become chapters with each containing multiple scenarios. We could illustrate working with some of the Sunflower Leafs, e.g. for AT2 and BT2 we could consider:
AT2.1 - Clinical
AT2.1.1 - Cancer
AT2.2 - Omics
AT2.2.1 - Proteomics
AT2.3 - Funders
AT2.3.1 - ZonMW
AT2.4 - Rare Diseases
Other types of Scenarios
What does a researcher have to do if he/she wants to find data and then gain access to it?
Probably Architecture has this covered? TBD
Q: how does https://health-ri.atlassian.net/wiki/spaces/FSD/pages/107806721/Data+onboarding+on+the+national+catalogue#3.-How-to-onboard-your-information-to-the-catalogue%3F 3a, 3b and 3c affect the scenarios?