FAIR reviews ontology
This vocabulary represents scientific reviews. This model is used to annotate http://fairreviews.linkeddata.es/ data.
The relation between a review and a given rating assigned by a reviewer.
has rating
Relation between a scientific contribution and the reviews issued for it.
has review
Relation between a review the confidence set by the author about the review topic. As the review can be written only by one author the confidence is assumed to be for such author about the given paper without need of creating a new class involving the three actors in a n-ary alike solution.
has reviewer confidence
The relation between a review and agents that have contributed to the overall review as sub-reviwers.
has sub-reviewer
The relation between a given endeavour and the endeavour that it is replying to. For example, the relation between a reply and a given review.
is reply to
The relation between a review and the scientific contribution that is subject of the review.
is review of
The relation between a review and the tracking or scholarly venue management system where the reviewing process took place.
issued at
The realation between a review and the entity (e.g. conference, journal) that it was issued for (usually the one that requested the review).
issued for
The relation between the review and the agent publishing it. It might be the the author of the review or conference or journal to which the scientific resource was submitted to.
released by
Confidence value of expertise in the review topic given by the reviwer
confidence value
Content of the review.
content
Numerical value of the rating given to a review.
rating value
Language of the scientific contribution (paper, review, etc.).
Language
Un identificador que identifica de forma única a una entidad - tal como una agencia de financiación, una persona y un recurso - que pertenece a un esquema particular, como los especificados por individuos de la clase datacite:IdentifierScheme.
identificador
A non-empty group of Permissions and/or Prohibitions.
Policy
The set of values of a given confidence scale.
Confidence concept
A scale defining the confidence of a reviewer for a given topic.
Confidence concept scheme
A venue (e.g. conference, workshop), a expression collection (e.g. journal, special issue), or an individual agent (e.g. organization, researcher) collecting scientific contributions.
Convening organization
A discrete scale defining the confidence of a reviewer for a given topic.
Discrete confidence concept scheme
A discrete scale defining the rating given by a reviewer for a specific scientific contribution.
Discrete rating concept scheme
The set of values of a given rating scale.
Rating concept
A scale defining the rating given by a reviewer for a specific scientific contribution.
Rating concept scheme
A reply to a review or another endeavour.
Reply
A review of a scientific contribution.
Review
The platform where the review process takes place.
Tracking system
Discrete scale from Approved to Not Approved, including Aprproved With Reservations,
Approved to Not Approved
Approved
Approved with reservations
Not approved
Discrete scale from Accept to Reject, including pre-screening and two strikes rule
Accept to Reject, Two Strikes
Accept
Major revision
Minor revision
Reject
Reject (Pre-Screening)
Reject (Two Strikes)
Discrete scale from 1 to 5, used by Association for Computational Linguistics annual meetings
Discrete 1 to 5
Not reviewer's area of expertise, or paper is very hard to understand. The evaluation is just an educated guess.
Reviewers is willing to defend my evaluation, but it is fairly likely that he/she missed some details, didn't understand some central points, or can't be sure about the novelty of the work.
Reviewer is pretty sure, but there's a chance he/she missed something. Although she/he has a good feel for this area in general, she/he did not carefully check the paper's details, e.g., the math, experimental design, or novelty.
Reviewer is quite sure, tried to check the important points carefully. It's unlikely, though conceivable, that he/she missed something that should affect his/her ratings.
Reviewer is positive that the evaluation is correct, has read the paper very carefully and is familiar with related work.
Discrete scale from 0 to 10
Discrete 0 to 10
0 out of 10
1 out of 10
10 out of 10
2 out of 10
3 out of 10
4 out of 10
5 out of 10
6 out of 10
7 out of 10
8 out of 10
9 out of 10
Discrete scale from 0 to 5
Discrete 0 to 5
0 out of 5
1 out of 5
2 out of 5
3 out of 5
4 out of 5
5 out of 5
Discrete scale from -2 to 2, including 0
Discrete -2 to 2
0 on a [-2,2] scale
-1 on a [-2,2] scale
-2 on a [-2,2] scale
1 on a [-2,2] scale
2 on a [-2,2] scale
Discrete scale from Expert to Null, also representend in an scale from 4 to 0
Expert to Null
Expert
High
Low
Medium
Null
Discrete scale from Strong Reject to Strong Accept, including Bordeline
St. Reject to St. Accept
Borderline
Strong Accept
Strong Reject
Weak Accept
Weak Reject
Discrete scale from Strong Reject to Strong Accept, excluding Bordeline
St. Reject to St. Accept, without Borderline
0 to 10 continuos
0 to 15 continuos
0 to 5 continuos