We know that we are intervening in complex organizations, and we need to find ways to also anticipate unintended consequences. The intent is to ease our life, and scientific careers, and make great science!
## Delineation
### Goal
Our goal is to adapt **FAIR** principles for organizations and collaborations.
**F**: We want to be able to search and find people, labs, instruments, responsibilities, expertise, and interests when working at the GFZ. This is especially important for the onboarding phase of new members, but also to situate oneself in the changing setting at the GFZ/POF/science.
**A**: We want to be able to access information and networks right away and shouldn't rely on facilitators or be hindered by gatekeepers. We want to create, enhance, adapt, participate, and better the scientific workplace environment.
**I**: We want to have the option to collaborate, explore and use all available labs, tools, techniques, expertise, data, etc. to make optimized use of time, resources, and existing science. We want to learn fast, fail fast, identify gaps, and improve quickly.
**R**: We want to know where, when, and what data, laboratories, studies, and people exist or existed, and what enables, or inhibits scientific merits.
We can achieve accelerated improvements towards this goal through networked communities. Beyond community building, we can accomplish more together, than even the best of us can accomplish alone. These communities are based on expectations, for example, CLEAR (communicative, learning, engaging, adaptive, relational), or agile systems; restrictions (legal, technical, resources, personal), and participation (decentralized, participatory, ...).
### Strategy
_The critical issue with the status quo is not what works, but rather what works for whom and under what set of conditions._
- We need a solution that provides **scalability**. Scalable and adaptable to our needs, but also in terms of searchability and potential extensions.
- We need to engage with (key) participants early and often. Providing **transparency** enables us to find bugs, biases, and needs but also to fix them, as well as those you can find and fix them.
- We need to think and act in **collaboration**. Being part of and working on something for us can melt down disciplinary borders, and strengthen the community, as sharing is caring.
Possible implementation:
**TRAC**ebilit**Y** is based on a graph database system.
### Way
Decide which data bank management system is suitable for us. Which structure do we want? Which data exists in which form, and what do we need from whom? Which boundaries and restrictions do we need? (user management, legal aspects, content, ...) How to implement import/export/update/visualization? Define GUI, API, and backups, ... Compile controlled vocabulary, how?
How to start? -Small preliminary start e.g. data from "my profile", define in workshops, add by sprint meetings... How to engage others to participate? -agile development, low barrier to contribute, learning and developing concrete features e.g. visualization of field sites, study areas, collaborations, ...
