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We’ve previously seen what needs to be added to a manifest to enable search inside. On this page we’ll cover how the client forms a query using the information from the manifest.
http://iiif.io/api/search/1.0/#query-parameters
| Parameter | Definition |
|---|---|
q |
A space separated list of search terms. |
motivation |
A space separated list of motivation terms. |
date |
A space separated list of date ranges. |
user |
A space separated list of URIs that are the identities of users. |
qThe q parameter allows for searching within the next of an annotation.
motiviationIt is possible to narrow results by the motivation of the annotation.
| Motivation | Definition |
|---|---|
painting |
Only annotations with the sc:painting motivation |
non-painting |
Annotations with any motivation other than sc:painting |
commenting |
Annotations with the oa:commenting motivation |
describing |
Annotations with the oa:describing motivation |
tagging |
Annotations with the oa:tagging motivation |
linking |
Annotations with the oa:linking motivation |
So an example of a search query would be like the following. It is as simple as adding a q parameter to the URI for the search service.
https://ocr.lib.ncsu.edu/search/segPap_003?q=amazon
Note that this particular implementation ignores all parameters other than q.
To understand a search query response, you need to look at the relationship between resources and hits.
The hits are the search results. There are a number of features that are possible with hits but the main property to focus on are the annotations. The list of annotations are identifiers that refer to the @id of one of the listed resources.
A resource is an embedded annotation. (This is a performance optimization instead of having to make additional requests for many annotations.) The value of the on property for the annotation is a canvas. This can either be the full canvas or a region of the canvas using a spatial media fragment (xywh). The use of the xywh fragment then allows for a client to highlight just the text that matches the query.
To allow for painting an annotation onto a particular region of the canvas to highlight the search match, a search server would need to know the bounding box for the match. In some cases this might be the individual word or the line or paragraph the word is in.
http://iiif.io/api/search/1.0/#autocomplete
The autocomplete service works similarly. Here’s an example URI for autocomplete:
https://ocr.lib.ncsu.edu/search/segPap_003?q=ama
The terms list returns the matches that can be provided as search suggestions.