1. Definitions
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_.
2. Initializing a client with a url
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:
-
E
is atree:Collection
: then the client needs to select the right search tree -
E
is adcat:Dataset
: then the client needs to select the right distribution or dataservice from a catalog -
E
is aldes:EventStream
: then the client MAY take into account LDES specific properties -
E
is adcat:Distribution
: then the client needs to process it accordingly -
E
is adcat:DataService
: then the client needs to process it accordingly -
E
is a catalog or is not explicitly mentioned: then it needs to select a dataset based on shape information and DCAT Catalog information
2.1. Selecting a collection via 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.
Will we document the precise algorithm to use? Should we extend shapes with cardinality approximations as well?
2.2. Selecting a collection via a 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.
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
.
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.
2.3. Choosing from multiple SearchTrees with TREE
2.4. Selecting a search tree via a 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. If nothing is available, all need to be tested by processing them as exemplifie din the next subsections.
2.4.1. Selecting a search tree via DCAT Distribution
E dcat:distribution ?D . ?D dcat:downloadURL ?N .
then ?N is a rootnode of E.
2.4.2. Selecting a search tree from a DCAT data service
-
?DS dcat:servesDataset E ; dcat:endpointURL ?U
orE dcat:endpointURL ?U
, then the algorithm MUST repeat the algorithm with?U
as the entrypoint.
2.5. Linked Data Event Streams
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.
3. Extracting content information
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.
3.1. DCAT and dcterms
3.2. Provenance
3.3. Linked Data Event Streams
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.