Merge pull request #23 from biomarkersParkinson/validator

Add validator script

README.md

@@ -30,6 +30,16 @@ poetry install
 poetry run pytest
 ```
 
+### Building the documentation
+
+We use [mkdocs](https://www.mkdocs.org/) to build the documentation. If you want to build the documentation locally, the following commands will prove useful:
+
+```bash
+mkdocs build       # build the documentation
+mkdocs serve       # serve the documentation on a local server
+mkdocs gh-deploy   # deploy the documentation to GitHub pages
+```
+
 ## Contributing
 
 Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

docs/contact.md

@@ -1,5 +1,7 @@
 # Contact
 
+More information about the TSDF format can be found in the [TSDF preprint](https://arxiv.org/abs/2211.11294).
+
 This package has been written by engineers from the [Netherlands eScience Center](https://esciencecenter.nl).
 It is maintained by:
 

docs/index.md

@@ -1,18 +1,18 @@
-# Welcome to tsdf
+# Welcome to the TSDF (Time Series Data Format) Python package
 
-A package to load [TSDF data](https://arxiv.org/abs/2211.11294) into Python.
+A package to work with TSDF data in Python. This implementation is based on the the TSDF format specification, which can be found in this [preprint](https://arxiv.org/abs/2211.11294).
 
-## What is `TSDF data`?
+## What is TSDF data?
 
 `tsdf` stands for _`time series data format`_.
 It is a unified, standardized format for storing all types of physiological sensor data. It was originally introduced in this [preprint](https://arxiv.org/abs/2211.11294).
 
 TSDF provides a unified, user-friendly format for both numerical sensor data and metadata, utilizing raw binary data and JSON-format text files for measurements/timestamps and metadata, respectively. It defines essential metadata fields to enhance data interpretability and exchangeability, aiming to bolster scientific reproducibility in studies reliant on digital biosensor data as a critical evidence base across various disease domains.
 
 
-## Example: TSDF Metadata JSON
+## Example: TSDF Metadata
 
-This example demonstrates a TSDF metadata file, showcasing the structured format used to easily interpret and read the corresponding binary data. For more intricate examples and detailed specifications, the paper serves as a comprehensive reference.
+This example demonstrates a TSDF metadata JSON file, showcasing the structured format used to easily interpret and read the corresponding binary data. For more intricate examples and detailed specifications, the paper serves as a comprehensive reference.
 
 ```json
 {

docs/installation.md

@@ -1,30 +1,16 @@
 # Installation
 
-## Requirements
-
-`tsdf` requires a recent version of [Python](https://www.python.org/) and a Python package manager (such as `pip`).
-Chances are that you have them already installed.
-You can check if that's the case from the command line:
-
-```bash
-python --version
-```
-
-```bash
-pip --version
-```
-
 ## Installing tsdf
 
 The package is available in [PyPI](https://pypi.org/project/tsdf/). The latest stable release can be installed using:
 
 ```bash
-$ pip install tsdf
+pip install tsdf
 ```
 
-### Installing the develop version
+## Installing the development version
 
-The source code is stored and maintained on [GitHub](https://github.com/biomarkersParkinson/tsdf).
+The source code is available on [GitHub](https://github.com/biomarkersParkinson/tsdf).
 
 If you have `git` installed, the latest version of tsdf can be installed by typing:
 
@@ -41,4 +27,4 @@ Otherwise you can install it manually by following these steps:
 ## What now?
 
 Now you can import functions from the `tsdf` Python package.
-See some examples in the next section.
+See some examples in the next section.