1st part

# Duration Agenda Item
Build controlled vocabularies
1 0:10 Welcome - motivations and practicalities
Summary: Short introduction about the workshop
2 0:20 Introduction to linked (meta)data and machine-actionability
Summary: Non technical introduction to linked (meta)data and machine-actionability. In this presentation we will present and highlight key mechanisms and components that make (meta)data machine-actionable and linked to other resources out in the Web.
Slides on zenodo
3 0:30 How to build machine-actionable controlled vocabularies?
Summary: Controlled terminologies, such as vocabularies and ontologies, are one of the most essential components in achieving machine-actionability and (meta)data linking. Without them we are left with free text inputs which are difficult if not impossible to be understood by machines, and often lead to false interpretation by humans. Since often existing controlled terminologies aren’t sufficient to cover needs of particular domains, we will learn how to build them.
Slides on zenodo
0:15 Break
4 2:45 Building domain specific controlled vocabularies of variables and research topics
Summary: What differentiate one research domain from another are variables contained in data and what research topics they are investigating with data. Therefore, in this hands-on exercise we will start to build the corresponding controlled vocabularies and publish them on OntoStack and BioPortal. On the second day we will use these vocabularies to update a generic metadata template to be domain specific.
5 0:15 Round-off and what happens next?
Summary: A quick summary of what we did during the first day of M4M and a prelude to day 2 of M4M.

2nd part

# Duration Agenda Item
Build machine-actionable metadata template
1 0:45 How to build machine-actionable metadata templates?
Summary: We will introduce an approach in developing machine-actionable metadata templates. Also, we will present Generic Dataset Metadata Template (GDMT) as an example of a configurable machine-actionable template. Furthermore, we will show how to configure this template to be domain specific by means of introducing the two vocabularies created in day 1 of M4M.
Slides on zenodo
2 0:15 Exercise 1: Create a copy of Generic Dataset Metadata Template (GDMT)
Summary: Participants will make a copy of the GDMT template in CEDAR workbench in a designated CEDAR folder that will be shared among them.
3 0:15 Exercise 2: Create metadata fields
Summary: Participants will make metadata fields which will be used to modify the GDMT template, thus turning it to be domain specific template. Specifically participants will create two fields, one that will be used to configure for domain specific variables and another one for domain specific research topics (i.e. subjects).
0:15 Break
4 0:15 Exercise 3: Assign controlled vocabularies to metadata fields
Summary: Participants will configure previously derived fields to source their values from the two controlled vocabularies that were created in day 1 of M4M.
5 0:15 Exercise 4: Add fields to metadata elements and configure RDF properties
Summary: Participants will create elements which will contain the previously created fields. Additionally, participants will add RDF properties to the fields making them fully machine-actionable semantic artifacts and configure occurence of fields.
6 0:15 Exercise 5: Replace elements in template
Summary: Participants will edit their copy of the GDMT template, remove existing generic variable and subject elements and insert the corresponding domain specific elements.
7 1:00 Exercise 6: Make machine-actionable metadata
Summary: Participants will instantiate previously configured domain specific GDMT (i.e., metadata template), thus creating machine-actionable metadata.
8 0:15 Round-off and what happens next?
Summary: A quick summary of what we did during M4M and discuss next steps.