Personas
To not think about our community as an abstract monolith, but of a heterogeneous group of people with different skill sets and requirements, we developed personas - fictional individuals - with their distinct wants and needs.
In total we determined six personas for our core stakeholder groups. We align these personas with our services to ensure that we can offer added value to these fictional people and also for our services to keep in mind. For these fictional people we develop pathways of how they can navigate our website and services. We keep these people’s needs in mind when designing and optimizing services. Moreover, these personas are not only used for development. We also create marketing material such as videos tailored to their use cases.
We have a set of secondary stakeholders as well, including e.g. journalists or users who use our services as a back-end to their own product. Though we still provide events and services for them, they do not get as much of a developed pathway through the website as the others.
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- Find and create datasets
- Clean data
- Process data
- Create visuals
- Unstructured and noisy data
- Too much time spent with data cleaning
- Lacks overview of relevant publications and datasets
- Data clean-up service that takes up ~60% of work
- Search engines supporting different content types
- Quick search to not loose too much time
- Service that presents earliers solutions to same task
- Search for papers/methods for his tasks
- Gets lost reviewing & researching
- Not enough time to read all interesting papers
- Incomplete descriptions of methods, data, etc
- Better documentation of current state of task
- Learning new skills
- Review literature
- Keep up with community news
- Steep learning curve
- At the same time too much and not enough training material and info
- Training resources tailored to her needs
- Description of typical workflows and processes
- Exchange platform to get in touch with experts
- Compare own data with experimental data
- Explore meaning of results
- Methods research
- Number of meetings
- Data analysis produces strange results without a clue where the problems are
- Not enough computational power available
- Getting in touch with the right experimentalists
- Standards for sharing data with experimentalists
- More data, more power
- Literature search
- Keeping up with latest methods, datasets, etc.
- Another group researches same topic & publishes results first
- Overview over new hot topics
- Also keep up with community news
- Data management of his group
- Ensure data protection
- Write proposals
- Fulfill proposal expectations
- Combining data protection & open science, sometimes the two seem mutually exclusive
- Secure & legal place to store sensitive data that can still be connected to executable code
- Clearer guidelines for proposals
- Reading papers, taking notes, summarizing
- Getting statements from important people in the field
- Writing articles
- Tracking knowledge provenance
- Too many papers, not sure where to start
- An overview over relevant information for a specific topic, including the article, where the info is coming from
- A starting point for finding relevant scientific literature
- (Research) software development
- Using services that already exist in the backend
- No/bad API
- A good API
- Support
- API description and documentation
- Tutorial