Added SotA folder. (#6)

* Added ontology sota resources.
* Modified bibtex reference.

---------

Signed-off-by: Lionel TAILHARDAT <lionel.tailhardat@orange.com>

docs/README.md

@@ -6,7 +6,8 @@ See sub-folders for specific content:
 noria-ontology/docs/
 ├───diagrams <shared diagrams and figures>
 ├───NORIA-O <Widoco generated documentation for NORIA-O>
-└───NORIA-O-KOS <sparna-git/skos-play generated documentation for NORIA-O KOS>
+├───NORIA-O-KOS <sparna-git/skos-play generated documentation for NORIA-O KOS>
+└───sota <State of the Art of ontologies related to the NORIA-O field prior to the design of NORIA-O>
 ```
 
 Useful references:

docs/sota/.gitignore

@@ -0,0 +1,2 @@
+# Temporary files
+.ipynb_checkpoints

docs/sota/README.md

@@ -0,0 +1,165 @@
+# noria-ontology / docs / sota files repository
+
+This folder contains the **NORIA-O SotA resources**: a state of the art (SotA) of ontologies related to the NORIA-O field prior to the design of NORIA-O, and means to analyze them.
+
+This work has been published in:
+
+```bibtex
+@phdthesis{LTailhardat-noria-thesis-2024,
+  author  = "Lionel Tailhardat",
+  title   = "Anomaly Detection using Knowledge Graphs and Synergistic Reasoning: Application to Network Management and Cyber Security",
+  school  = "EURECOM, Sorbonne University",
+  address = "France",
+  year    = 2024
+}
+```
+
+## Usage
+
+The main components of this repository are the following ones:
+
+* List of data models: the [noria-sota-ontology.xlsx](noria-sota-ontology.xlsx) file
+* Dataset of data models: sub-folders in [./dm-rdf](./dm-rdf)
+
+### Browse and/or edit the list of data models
+
+* Open the [noria-sota-ontology.xlsx](noria-sota-ontology.xlsx) file
+* Edit the file:
+  * Add references and details to ontologies.
+  * Download an ontology implementation to the [./dm-rdf](./dm-rdf) folder and reflect the folder name into the *downloaded* column.
+  * Use Protege 5.1.0 or the ontology authors' claims to fill the following columns: *classCount*, *objectPropertyCount*, *dataPropertyCount*, *individualCount*, *vocabularyExpressivity*, *vocabularyStatsAndExpressivityOrigin*.
+
+### Run the OOPS! analysis for ontologies with an implementation
+
+The [./dm-rdf](./dm-rdf) folder is for archiving referenced RDF ontologies and studying their characteristics.
+The analysis is carried-out using [OOPS!](https://oops.linkeddata.es/) via its WebService https://oops.linkeddata.es/webservice.html.
+
+#### Per model analysis
+
+* Navigate to `dm-rdf/`
+
+    ```shell
+    cd dm-rdf
+    ```
+
+* Copy the ontology to [dm-rdf/to-oops.xml](dm-rdf/to-oops.xml)
+* Make the call to OOPS:
+
+    ```shell
+    make oops
+    ```
+* Analyze the results from [dm-rdf/from-oops.xml](dm-rdf/from-oops.xml)
+
+Calling the OOPS WebService may require commenting out certain lines in the XML file, especially some *import* clauses.
+The following comment can be helpful in identifying the lines to comment out:
+```
+        <!-- HACK: comment the following line to avoid OOPS WebService unexpected_issue -->
+```
+
+#### Recursive Analysis
+
+* Execute OOPS queries for each directory:
+
+  ```shell
+  sh ./oops-recursive.sh
+  ```
+
+  The execution log is available in [oops-recursive.log](dm-rdf%2Foops-recursive.log) and [oops-recursive-error-sorted.log](dm-rdf%2Foops-recursive-error-sorted.log)
+
+* Extract OOPS statistics for each directory using a SPARQL query:
+
+  ```shell
+  sh ./oops-stats.sh
+  ```
+
+  The execution log is available in [oops-stats.log](dm-rdf%2Foops-stats.log)
+
+* Aggregate the statistics into a single file:
+
+  ```shell
+  csvstack -g $(find . -type f -name oops-stats.csv | paste -s -d ',' -) $(find . -type f -name oops-stats.csv) > oops-stats-one-file.csv
+  ```
+
+  The results are in [oops-stats-one-file.csv](dm-rdf%2Foops-stats-one-file.csv); the `group` column indicates the source of the indicators.
+
+* Analyze the statistics on [oops-stats-one-file.csv](dm-rdf%2Foops-stats-one-file.csv)
+  * Summary view:
+
+    ```shell
+    csvstat oops-stats-one-file.csv > oops-stats-one-file-csvstat.csv
+    ```
+
+    See the output in [oops-stats-one-file-csvstat.csv](dm-rdf%2Foops-stats-one-file-csvstat.csv):
+
+    Example:
+
+    ```
+      1. "group"
+        Most common values:    ./ICAS/oops-stats.csv (15x)
+                               ./ForensicOntology/oops-stats.csv (11x)
+                               ./UCO/oops-stats.csv (11x)
+                               ./OM/oops-stats.csv (10x)
+                               ./DogOnt/oops-stats.csv (10x)
+      3. "pit_code"
+        Most common values:    P13 (43x)
+                               P11 (42x)
+                               P08 (41x)
+                               P04 (29x)
+                               P10 (20x)
+      5. "pit_importance"
+        Most common values:    Minor (156x)
+                               Important (135x)
+                               Critical (17x)
+    ```
+
+
+### Browse the list of data models as a Turtle file
+
+Steps for converting the list of data models into a [Turtle](https://www.w3.org/TR/turtle/) file, and thereby enabling further processing:
+
+* Browse the Web to the [SKOS Play ! Convert](https://skos-play.sparna.fr/play/convert) service
+* Convert the [noria-sota-ontology.xlsx](noria-sota-ontology.xlsx)
+  * Output format = Turtle
+  * Ignore SKOS post-processing = Checked
+* Save the resulting file as [noria-sota-ontology.ttl](noria-sota-ontology.ttl)
+
+### Generating the ontology diagram
+
+Steps for generating an ontology diagram rely on the [WebVOWL](https://github.com/VisualDataWeb/WebVOWL) tool:
+
+* Ontology > Select ontology file > Upload : select the `to-oops.xml` file
+* Let WebVOWL apply the recommended layout parameters
+* Center graph
+* Export > Export as SVG : fetch and store the resulting `to-oops.xml.svg` file
+
+### Get insights using a Jupyter notebook
+
+Install requirements:
+
+* Python 3.11
+* Python packages:
+
+  ```shell
+  pip install -r ./scripts/requirements.txt
+  ```
+
+* Jupyter notebook framework:
+
+  ```shell
+  sudo apt install jupyter-core jupyter-notebook
+  ```
+
+Run the notebook service:
+
+* (optional) If using a virtual env
+
+  ```shell
+  python -m ipykernel install --user --name=<VirtualEnvName>
+  ```
+* Start the Jupyter notebook service
+
+  ```shell
+  jupyter notebook
+  ```
+
+* Load and run the [./scripts/noria-sota-stats.ipynb](./scripts/noria-sota-stats.ipynb) notebook.

docs/sota/dm-rdf/.gitignore

@@ -0,0 +1,3 @@
+# Temporary files
+*.log
+catalog-v001.xml