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03-discovery-specification.bs
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<pre class='metadata'>
Title: TREE Discovery and Context Information
Shortname: TREEDiscovery
Level: 1
Status: w3c/CG-DRAFT
Markup Shorthands: markdown yes
URL: https://w3id.org/tree/specification/discovery
Repository: https://github.com/treecg/specification
Mailing List: [email protected]
Mailing List Archives: https://lists.w3.org/Archives/Public/public-treecg/
Editor: Pieter Colpaert, https://pietercolpaert.be
Abstract:
This specification defines how a client selects a specific dataset and search tree, as well as extracts relevant context information.
</pre>
# Definitions # {#overview}
A `tree:Collection` is a subclass of `dcat:Dataset` ([[!vocab-dcat-3]]).
The specialization being that this particular dataset is a collection of _members_.
A `tree:SearchTree` is a subClassOf `dcat:Distribution`.
The specialization being that it uses the main TREE specification to publish a search tree.
A node from which all other nodes can be found is a `tree:RootNode`.
Note: The `tree:SearchTree` and the `tree:RootNode` MAY be identified by the same IRI when no disambiguation is needed.
A TREE client MUST be provided with a URL to start from, which we call the _entrypoint_.
# Initializing a client with a url # {#starting-from}
The goal of the client is to understand what `tree:Collection` it is using, and to find a `tree:RootNode` to start the traversal phase from.
This discovery specification extends the initialization step in the TREE specification, for the cases in which multiple options are possible.
The client MUST dereference the URL, which will result in a set of quads. The client now MUST first perform the init step from the main specification.
If that did not return any result, then the client MUST check whether the URL before redirects (`E`) has been used in one of the following discovery patterns described in the subsections:
1. `E` is a `tree:Collection`: then the client needs to [select the right search tree](#tree-search-trees)
2. `E` is a `dcat:Dataset`: then the client needs to [select the right distribution or dataservice from a catalog](#dcat-dataset)
3. `E` is a `ldes:EventStream`: then the client MAY take into account [LDES specific properties](#ldes)
4. `E` is a `dcat:Distribution`: then the client needs to [process it accordingly](#dcat-distribution)
5. `E` is a `dcat:DataService`: then the client needs to [process it accordingly](#dcat-dataservice)
6. `E` is a catalog or is not explicitly mentioned: then it needs to select a dataset based on [shape information](#tree-collection-shapes) and [DCAT Catalog information](#dcat-catalog)
## Selecting a collection via shapes ## {#tree-collection-shapes}
When multiple collections are found by a client, it can choose to prune the collections based on the `tree:shape` property.
The `tree:shape` property will refer to a first `sh:NodeShape`.
The collection MAY be pruned in case there is no overlap with the properties the client needs.
Issue: Will we document the precise algorithm to use? Should we extend shapes with cardinality approximations as well?
## Selecting a collection via a catalog ## {#dcat-catalog}
A DCAT Catalog is an overview of datasets, data services and distributions.
As TREE clients first need to select a dataset, and then a search tree to use, it aligns with how DCAT-AP works.
DCAT discovery extends upon the previous section in which a collection or dataset can be selected based on the `tree:shape` property.
For now, we will assume the DCAT information is available in subject pages.
Issue: Do we need more text on how to handle different types of DCAT interfaces?
The dataset descriptions can be used for filtering the datasets available in a catalog to a list of datasets that can be useful for the client.
Such properties may include the spatial extent, the time extent, or how it is possibly a part of another `dcat:Dataset`.
Issue: How precise do we need to be in this specification?
When the `dcat:Dataset` is a `tree:Collection`, the DCAT catalog is going to contain a `dct:type` property with `https://w3id.org/tree#Collection` or `https://w3id.org/ldes#EventStream` as the object.
## Choosing from multiple SearchTrees with TREE ## {#tree-search-trees}
Issue: This is yet to be done
## Selecting a search tree via a DCAT dataset ## {#dcat-dataset}
The are two ways in which you can find a search tree from a dataset: via the distributions and via the data services. Both need to be tested.
Selecting a distribution or data service when multiple are available needs to be done based on [the search tree description](tree-search-trees).
If nothing is available, all need to be tested by processing them as exemplifie din the next subsections.
### Selecting a search tree via DCAT Distribution ### {#dcat-distribution}
`E dcat:distribution ?D . ?D dcat:downloadURL ?N .` then ?N is a rootnode of E.
Issue: This is yet to be done
### Selecting a search tree from a DCAT data service ### {#dcat-dataservice}
* `?DS dcat:servesDataset E ; dcat:endpointURL ?U` or `E dcat:endpointURL ?U`, then the algorithm MUST repeat the algorithm with `?U` as the entrypoint.
Issue: This is yet to be done
## Linked Data Event Streams ## {#ldes}
In case the client is not made for query answering, but only for setting up a replication and synchronization system, then there is a special type that can be used to indicate the search tree is made for this purpose: the `ldes:EventSource`.
Clients that want to prioritize taking a _full_ copy MAY give full priority to this server hint.
<div class="example">
```turtle
E a ldes:EventSource ;
tree:rootNode|dcat:downloadURL </node1> .
```
</div>
# Extracting content information # {#context}
Issue: This is yet to be done
Context information enables a client to understand who the creator of a certain dataset is, when it was last changed, what other datasets it was derived from, etc.
## DCAT and dcterms ## {#context-dcat}
Issue: This is yet to be done
## Provenance ## {#context-prov}
Issue: This is yet to be done
## Linked Data Event Streams ## {#context-ldes}
Issue: This is yet to be done
LDES (https://w3id.org/ldes/specification) is a way to evolve search trees in a consistent way. It defines every member as immutable, and a collection as append-only.
Therefore, one can make sure to only process each member once.
Extra terms are added, such as the concept of an EventStream, retention policies and a timestampPath.