# #ipofcc summary
During the workshop **In pursuit of fair co-creation** at #DINAcon18, we discussed time-bounded collaborative events, like ...
<small>(turn to next page)</small>
# ... Hackathons!
Every weekend, masses of people take part in hackathons around the world. From corporate innovation labs to chaotic co-creation jams, from competitive coding to cooperative making, from nondisclosure to open license, there are hackathons for everyone's taste.
Yet, despite common labels, such as 'hackathon' or ‘hackday’, their goals vary greatly. This creates ambiguity that is exploited for work precarization.
These types of events are common to many technical communities. We are part of the following networks which organize events around the year:
<a href="https://hack.opendata.ch" target="_blank" style="font-weight:600">
<img src="https://datalets.ch/dribdat/res/Make.OpenData.ch-Logo1.png" height="60" alt="HackOpendata">
<a href="http://now.makezurich.ch/" target="_blank" style="font-weight:600">
<img src="https://datalets.ch/dribdat/res/MakeZurich.svg" height="60" alt="MakeZurich">
<a href="https://dinacon.ch/en/hacknight/" target="_blank" style="font-weight:600">
<img src="https://datalets.ch/dribdat/res/DINAcon.png" height="60" alt="DINAcon">
<a href="http://hack.twist2018.ch/" target="_blank" style="font-weight:600">
<img src="https://datalets.ch/dribdat/res/TWIST.png" height="60" alt="TWIST">
To set up the grounds for a discussion, we put together a reading list together with researchers from the Bern University of Applied Science:
You'll find this and more in our workshop outline:
We also proposed an ‚open data driven model‘ for time-bounded events:
- Events are data sources themselves.
- Events are self-describing using a metadata scheme.
- Event meta-data contains classifiers to describe different event typologies.
- Event meta-data describes and links to event data (i.e. projects).
- Event data becomes an integral part of the data source.
You can read more about this on GitHub: [dribdat issue #112](https://github.com/datalets/dribdat/issues/112) .. or just look at how it is implemented on these sites:
**[hacknight.dinacon.ch](http://hacknight.dinacon.ch/hackathon.json) | [now.makezurich.ch](http://now.makezurich.ch/hackathon.json) | [hack.opendata.ch](http://hack.opendata.ch/hackathon.json)**
At the [DINAcon workshop](http://bit.ly/ipofcc), we covered fundamentals:
- Defining the scope (hackathons, exploitation, precarization)
- Who are the actors involved (organizers, challengers/sponsors, participants)
- What projects we can support (hackathon platform, research project, conferences)
And together with participants, we built *(in a collaborative manner, of course!)* a list of **attractors** and **detractors** for participation in hackathons.
This inspired us to, during the [#hacknight](https://hacknight.dinacon.ch/) later that day, to start putting the list into a flowchart.
![Zoom in on flowchart](https://blog.datalets.ch/workshops/2018/dinacon/flowchart-zoom1.png)
The [flowchart](https://hacknight.dinacon.ch/project/23) is a playful* way to describe the metadata that we believe should be exposed by every hackathon in order to provide fair conditions to decide attendance. It may help to:
- guide potential participants to join (or not) a specific event
- let organizers consider some of the issues at hand
- just amuse or confuse (some) people
# Next steps
- [Check out the flowchart](https://hacknight.dinacon.ch/project/23)
- [Learn about the platform](https://github.com/datalets/dribdat/)
- [Contribute to the standard](https://github.com/datalets/dribdat/issues/112)
- [Join the conversation](https://forum.schoolofdata.ch/c/events/hackathons)