Added more examples

.docs/examples/air.md

+---
+author: Martin Weise
+---
+
+## tl;dr
+
+[:fontawesome-solid-database:  Dataset](https://handle.stage.datacite.org/10.82556/gd17-aq82){ .md-button .md-button--primary target="_blank" }
+[:material-file-document:  Archive](https://doi.org/10.48436/mtha8-w2406){ .md-button .md-button--secondary target="_blank" }
+
+## Description
+
+This digital record contains historical air pollution and air quality data from approximately 20 air monitoring stations
+in Vienna, spanning the years from 1980 to 2021. The data was provided by the Umweltbundesamt and is stored in its
+original form in this record. This record forms the basis of an analysis carried out in a bachelor's thesis at the TU 
+Wien.
+
+## Solution
+
+
+<figure markdown>
+![Jupyter Notebook](../../images/screenshots/air-notebook.png){ .img-border }
+<figcaption>Figure 1: Jupyter Notebook accessing data on DBRepo using the Python Library.</figcaption>
+</figure>
+
+## DBRepo Features
+
+- [x] Import complex dataset
+- [x] System versioning
+- [x] Subset exploration
+- [x] Aggregated views
+- [x] Precise & PID of queries tables
+- [x] External data access for analysis
+
+## Acknowledgement
+
+This work was part of a cooperation with the [Umweltbundesamt](https://www.umweltbundesamt.at/).
+
+<img src="../../images/logos/umweltbundesamt.png" width=100 />
\ No newline at end of file

.docs/examples/covid-19.md

+---
+author: Martin Weise
+---
+
+## tl;dr
+
+[:fontawesome-solid-database:  Dataset](https://dbrepo1.ec.tuwien.ac.at/pid/15){ .md-button .md-button--primary target="_blank" }
+[:simple-github:  Archive](https://github.com/CSSEGISandData/COVID-19){ .md-button .md-button--secondary target="_blank" }
+
+## Description
+
+This dataset contains the daily COVID-19 data provided publicly 
+by [Johns Hopkins University](https://coronavirus.jhu.edu/about/how-to-use-our-data). 
+
+## Solution
+
+We imported their daily snapshots provided as 1145 versioned .csv files from their Git repository archive and imported
+them daily into DBRepo as system-versioned data that can be queried. During the time of this project the COVID-19 
+pandemic was still ongoing and therefore daily snapshots demanded a correct import script to be maintained.
+
+## DBRepo Features
+
+- [x] Data pipeline from Git repository
+- [x] System versioning
+- [x] Subset exploration

.docs/examples/influenza.md

----
-author: Martin Weise
----
-
-## tl;dr
-
-tbd
-
-## Description
-
-TBD
-
-## Solution
-
-TBD
-
-## DBRepo Features
-
-- [x] Import through CSV-dataset upload
-- [x] Data views implementing embargo period (24 hours)
-- [x] External access from Grafana Dashboard

.docs/examples/music.md

+---
+author: Martin Weise
+---
+
+## tl;dr
+
+[:fontawesome-solid-database:  Dataset](https://dbrepo1.ec.tuwien.ac.at/pid/34){ .md-button .md-button--primary target="_blank" }
+[:material-file-document:  Archive](https://gitlab.tuwien.ac.at/martin.weise/fairnb){ .md-button .md-button--secondary target="_blank" }
+
+## Description
+
+We use a dataset collected by [Aljanaki et al.](https://www2.projects.science.uu.nl/memotion/emotifydata/), consisting 
+of 400 MP3 music files, each having a playtime of one minute and labeled with one of four genres: rock, pop, classical 
+and electronic, each genre contains 100 files, the genre will be used as label for the ML model. Then by generating MFCC
+vectors and training a SVM, the ML-model can classify emotions of the provided .mp3 files with and accuracy of 76.25%.
+
+<figure markdown>
+![](../../images/screenshots/mfcc-jupyter.png){ .img-border }
+<figcaption>Figure 1: Accuracy of predictions matrix in Jupyter Notebook.</figcaption>
+</figure>
+
+## Solution
+
+DBRepo is used as relational data storage of the raw- and aggregated features, prediction results and the splits of the
+training- and test data. For each of the 400 .mp3 files, 40 MFCC feature vectors are generated. This data is stored
+in aggregated form in the [`aggregated_features`](https://dbrepo1.ec.tuwien.ac.at/pid/47) table.
+
+## DBRepo Features
+
+- [x] Database as storage for machine learning data
+- [x] System versioning
+- [x] Subset exploration
+- [x] Precise & PID of database tables
+- [x] External data access for analysis

.docs/examples/power.md

@@ -15,7 +15,7 @@ maintenance, quality of products and ultimately process efficiency and -producti
 
 <figure markdown>
 ![](../../images/screenshots/power.png)
-<figcaption>Figure 1: aaaa from <a href="https://publik.tuwien.ac.at/files/PubDat_252294.pdf">Hacksteiner (2016)</a>.</figcaption>
+<figcaption>Figure 1: Total power usage of machine floor TU Pilotfabrik, image from <a href="https://publik.tuwien.ac.at/files/PubDat_252294.pdf">Hacksteiner (2016)</a>.</figcaption>
 </figure>
 
 ## Solution

.docs/examples/survey.md

+---
+author: Martin Weise
+---
+
+## tl;dr
+
+[:fontawesome-solid-database:  Dataset](https://handle.stage.datacite.org/10.82556/g2ac-vh88){ .md-button .md-button--primary target="_blank" }
+[:simple-jupyter:  Notebook](https://binder.science.datalab.tuwien.ac.at/v2/git/https%3A%2F%2Fgitlab.tuwien.ac.at%2Fmartin.weise%2Ftres/HEAD){ .md-button .md-button--secondary target="_blank" }
+
+## Description
+
+This digital record contains historical air pollution and air quality data from approximately 20 air monitoring stations
+in Vienna, spanning the years from 1980 to 2021. The data was provided by the Umweltbundesamt and is stored in its
+original form in this record. This record forms the basis of an analysis carried out in a bachelor's thesis at the TU 
+Wien.
+
+## Solution
+
+
+<figure markdown>
+![Jupyter Notebook](../../images/screenshots/air-notebook.png){ .img-border }
+<figcaption>Figure 1: Jupyter Notebook accessing data on DBRepo using the Python Library.</figcaption>
+</figure>
+
+## DBRepo Features
+
+- [x] Import complex dataset
+- [x] System versioning
+- [x] Subset exploration
+- [x] Aggregated views
+- [x] Precise & PID of queries tables
+- [x] External data access for analysis
+
+## Acknowledgement
+
+This work was part of a cooperation with the [Umweltbundesamt](https://www.umweltbundesamt.at/).
+
+<img src="../../images/logos/umweltbundesamt.png" width=100 />
\ No newline at end of file

mkdocs.yml

@@ -45,9 +45,13 @@ nav:
     - UI:
       - Customization: api/ui.md
   - Examples:
-    - Hazardous Materials: examples/hazard.md
-    - Power in Industry 4.0: examples/power.md
-    - Transportation Monitoring: examples/transportation.md
+    - Air Quality Data: examples/air.md
+    - COVID-19 Data: examples/covid-19.md
+    - Hazard Data: examples/hazard.md
+    - Industry 4.0 Power Data: examples/power.md
+    - Survey Data: examples/survey.md
+    - Music-ML Data: examples/music.md
+    - Transportation Data: examples/transportation.md
     - XPS Data: examples/xps-data.md
   - publications.md
   - contact.md