Commit 42a6b11f authored by Susanne Arndt's avatar Susanne Arndt
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Merge branch '3-customize-widoco_sections' into 'main'

Resolve "Customize widoco_sections"

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This is a place holder text for the introduction. The introduction should briefly describe the ontology, its motivation, state of the art and goals.
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This is an ontology draft for the description of metadata of traffic observations, in particular video recordings of road traffic.
The draft resulted from an exchange of the Chair of Automobile Engineering at TU Dresden with representatives of NFDI4Ing (Community Cluster 4.4, Archetype Golo, Base Services S3) and FID move in NFDI4Ing's Special Interest Group "Metadata and Ontologies". An essential part of that meeting was the presentation of the reseaerch data management approach at the Chair of Automobile Engineering, in particular its tooling, its metadata approach and its workflow.
Traffic observations are managed with ListDB, a solution combined of a SharePoint instance and a virtual machine for data servicing . An accompanying Codebook defines relevant metadata that should be provided for each road traffic observation.
The ontology draft is, in fact, based on the Codebook (v. 1.0.0.) and an attempt to make a machine-readable document out of it, applying standards from the Semantic Web Stack (RDF(S) and OWL).
Research data management with ListDB and the ontology draft has been the topic of a Workshop at NFDI4Ing 2021 Conference (see [References](https://gitlab.hrz.tu-chemnitz.de/s4308286--tu-dresden.de/listdb#References)).
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This is a placeholder text for the description of your ontology. The description should include an explanation and a diagram explaining how the classes are related, examples of usage, etc.
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The ListDB Ontology draft is referring back to the [Data Catalogue Vocabulary (DCAT, Version 2)](https://www.w3.org/TR/vocab-dcat-2/). DCAT is "an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web" (Albertoni et al. 2020). It "enables a publisher to describe datasets and data services in a catalog using a standard model" (Albertoni et al. 2020).
"A dataset in DCAT is defined as a 'collection of data, published or curated by a single agent, and available for access or download in one or more serializations or formats'. A dataset is a conceptual entity, and can be represented by one or more distributions that serialize the dataset for transfer. Distributions of a dataset can be provided via data services." (Albertoni et al. 2020)
ListDB basically is a data catalog where information about data sets is stored and which points to the distributions and files belonging to a data set. Each data set in ListDB is centered around a single traffic observation. The basic model of ListDB Ontology is therefore depicted as follows:
![Visualization of Traffic Observation Data Sets and Relation of ListDB Ontology to DCAT 2](/visualizations/traffic_observation_dataset.png)
Each data set has exactly one metadata file in which information about the traffic observation is given. This can be
- information about the location of the recording,
- temporal infomation,
- information about the environment,
- organizational information, or
- information about measurements.
![Visualization of Class 'metadata file' and metadata properties for metadata file instances](/visualizations/metadata_file.png)
The metadata file description refers to classes that define subclasses relevant for the description of traffic observations. The next visualization gives some examples of subclasses of the class 'Location':
![Visualization for class 'Location' and some examples for subclasses](/visualizations/Location_class.png)
The description of an instance of class 'metadata file' uses specific subproperties and a range of defined values:
![Visualization of an instance of class 'metadata file' with some example relations and values](/visualizations/instance_metadata_file.png)
A JSON-LD representation of a metadata file example refers to the terms defined in ListDB Ontology (and other semantic resources) via its identifiers. The example also contains the element for the data set the metadata file belongs to:
```JSON-LD
{
"@context": {
"owl": "http://www.w3.org/2002/07/owl#",
"dcterms": "http://purl.org/dc/terms/",
"geo": "http://www.w3.org/2003/01/geo/wgs84_pos#",
"example": "http://www.semanticweb.org/new/ontologies/2022/3/5/",
"skos": "http://www.w3.org/2004/02/skos/core#",
"listdb": "https://www.listdb.de/ontology#",
"wikidata": "http://www.wikidata.org/entity/",
"dcat": "http://www.w3.org/ns/dcat#"
},
"@graph": [
{
"@id": "listdb:E0000000251",
"@type": [
"dcat:Dataset",
"listdb:C0000000061"
]
},
{
"@id": "listdb:I0000000016",
"@type": [
"owl:NamedIndividual",
"listdb:C0000000062"
],
"dcterms:spatial": {
"@id": "_:b1"
},
"geo:location": {
"@id": "listdb:E0000000226"
},
"skos:prefLabel": {
"@language": "en",
"@value": "20210512_1452_Fic_Hec_4W_d_1.txt"
},
"wikidata:P281": "01097",
"wikidata:P669": [
{
"@id": "listdb:I0000000046"
},
{
"@language": "de",
"@value": "Fichtenstrasse"
},
{
"@language": "de",
"@value": "Hechstrasse"
}
],
"listdb:AP0000000064": {
"@language": "en",
"@value": "GoPro mounted on drone. Videos were processed afterwards before saving."
},
"listdb:AP0000000075": "Dresden",
"listdb:AP0000000151": {
"@id": "listdb:I0000000046"
},
"listdb:AP0000000161": 1,
"listdb:AP0000000162": "GoPro Hero Session4",
"listdb:DP0000000027": {
"@language": "de",
"@value": "LKT"
},
"listdb:DP0000000028": "Test",
"listdb:DP0000000029": 2,
"listdb:DP0000000187": "20210512_1452",
"listdb:E0000000213": {
"@id": "listdb:I0000000206"
},
"listdb:E0000000216": {
"@id": "listdb:E0000000217"
},
"listdb:E0000000223": {
"@id": "listdb:E0000000224"
},
"listdb:E0000000230": {
"@id": "listdb:E0000000231"
},
"listdb:E0000000232": {
"@id": "listdb:E0000000235"
},
"listdb:E0000000236": {
"@id": "listdb:E0000000237"
},
"listdb:OP0000000018": {
"@id": "listdb:I0000000024"
},
"listdb:OP0000000038": {
"@id": "listdb:I0000000034"
},
"listdb:OP0000000042": {
"@id": "listdb:I0000000044"
},
"listdb:OP0000000049": {
"@id": "listdb:I0000000048"
},
"listdb:OP0000000056": {
"@id": "listdb:I0000000054"
},
"listdb:OP0000000060": {
"@id": "listdb:I0000000058"
},
"listdb:OP0000000073": {
"@id": "listdb:I0000000067"
},
"listdb:OP0000000085": {
"@id": "listdb:I0000000081"
},
"listdb:OP0000000118": {
"@id": "listdb:I0000000088"
},
"listdb:OP0000000119": {
"@id": "listdb:I0000000111"
},
"listdb:OP0000000125": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000127": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000129": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000165": {
"@id": "listdb:I0000000155"
},
"listdb:OP0000000166": {
"@id": "listdb:I0000000160"
},
"listdb:OP0000000168": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000169": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000170": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000171": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000172": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000173": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000174": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000175": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000176": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000177": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000178": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000179": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000180": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000181": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000182": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000183": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000184": {
"@id": "listdb:I0000000122"
},
"listdb:OP0000000185": {
"@id": "listdb:I0000000149"
},
"listdb:OP0000000190": {
"@id": "listdb:I0000000191"
},
"listdb:OP0000000194": {
"@id": "listdb:I0000000195"
},
"listdb:OP0000000196": {
"@id": "listdb:I0000000036"
},
"listdb:OP0000000197": {
"@id": "listdb:I0000000036"
},
"listdb:OP0000000199": [
{
"@id": "listdb:I0000000200"
},
{
"@id": "_:b0"
}
],
"listdb:OP0000000201": {
"@id": "listdb:I0000000202"
}
}
]
}
```
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Add your references here. It is recommended to have them as a list.
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Albertoni, Ricardo et al. (2020): Data Catalog Vocabulary (DCAT) - Version 2. W3C Recommendation. URL: https://www.w3.org/TR/vocab-dcat-2/
Arndt, Susanne; Bäumler, Maximilian; Roski, Stefanie; Fuchs, Matthias (2021): Strukturierte Metadaten in den Verkehrswissenschaften. In: Marco Berger, Jan Linxweiler & Stefanie Roski (eds): NFDI4Ing Conference 2021 - Collection of Abstracts. Zenodo. https://doi.org/10.5281/zenodo.5702697.
- Slide Set 1: https://cloudstore.zih.tu-dresden.de/index.php/s/FdsMH5JfxpGxCfo
- Slide Set 2: https://cloudstore.zih.tu-dresden.de/index.php/s/fajs8GPBoXQ5c23
Brickley, Dan (2009): WGS84 Geo Positioning: an RDF vocabulary. URI: (http://www.w3.org/2003/01/geo/wgs84_pos#).
DCMI Usage Board (2020): DCMI Metadata Terms. URI: (http://purl.org/dc/elements/1.1/), (http://purl.org/dc/terms/).
Miles, Alistair; Bechhofer, Sean (2004): SKOS Vocabulary. URI: (http://www.w3.org/2004/02/skos/core#).
Open Geospatial Consortium (2012): OGC GeoSPARQL – A Geographic Query Language for RDF Data. URI: (http://www.opengis.net/ont/geosparql#).
QUDT.org (2022): Quantities, Units, Dimensions and Types. URI: (http://qudt.org/schema/qudt/). DOI: (https://doi.org/10.25504/FAIRsharing.d3pqw7).
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This is a place holder text for the abstract. The abstract should contain a couple of sentences summarizing the ontology and its purpose.
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This is an ontology draft for the description of metadata of traffic observations, in particular video recordings of road traffic. It defines properties to describe conditions and provenance of the recordings and some of the landmarks and environmental conditions at the scene of the recording.
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