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# Roadmap | ||
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The ODM Steering Group or Working Groups have identified the following features and tools for development. | ||
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See the [Roadmap](https://github.com/Big-Life-Lab/covid-19-wastewater/projects/3?add_cards_query=is%3Aopen) project for progress on the roadmap. Add new items or discuss on the discussion [thread](https://github.com/Big-Life-Lab/covid-19-wastewater/discussions/108). Issues with "future" tag are discussed for addition to the roadmap. | ||
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## Requirements | ||
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Requirements for future tools and features: | ||
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- **Support for English and French** - initially for the data model and then other documentation. | ||
- **Open and cross platform** - Tools to support the data model will be generated using or support open software. The objective is to create pseudo-code that can form the basis to program code in R or Python. Rules as pseudo-code allow development teams to generate consistent data applications in other program platforms (i.e. MS 365 or ArcGIS). | ||
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## Tools | ||
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1. **Automatic updating tools** - scripts that can be used to automatically push the most recent updates of the data model to the necessary depending files (template, ERD, ...) | ||
1. **Data mapping methods** - a collection of methods to: | ||
Read in data from templates into a database (SQLite supported). | ||
Conversion from "long" format to "wide" format needed for data analysis/ML. | ||
1. **Data validation tool** - can validate a datafile in terms of formatting and context, and provides feedback of needed changes | ||
1. **Data linking tools** - tools that will help ensure consistan summarization of public health data into summary results relevent for the WWTP catchment area. | ||
1. **Data cleaning methods** - rules for cleaning raw ODM data. | ||
1. **Visualization tools** - basic plots to visualize relevant signals. Simple visualization tools can be part of vignettes to show how to analyze wastewater data. | ||
1. **Transformation functions** - functions to create derived variables and aggreagations. i.e. moving averages, normalisation,... | ||
1. **Open, public data examples within the repository** - Example data to build | ||
and test common tools and demonstrate ODM compliant data format. | ||
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## Documentation | ||
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Documentation that including tutorials, how-to guides, technical references and explanations. See [Divio documentation approach](https://documentation.divio.com). | ||
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1. Tutorials - learning-oriented. | ||
1. How-to guides - problem-oriented. | ||
1. Explanation - understanding-oriented. | ||
1. Reference - information-oriented. | ||
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- Several presentations have introduced the ODM. Let's make the recordings available as a first step. Next, create additional visual documentation for specific functionalities. | ||
- Peer-review description with a permalink/DOI reference which would facilitate sharing and referencing within the scientific community. | ||
- Consider a website that organizes documentation for a wider audience of users that not necessarily know how to work with GitHub. | ||
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## Process | ||
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- Ensure Steering Committee and Working Groups have representation from a range discplines and regions. | ||
- Add a code of conduct. |