Strong Reject (Strong Reject to Strong Accept, without Borderline review rating scale)

1.2.2

The Bibliometric Data Ontology (BiDO)

The **_Bibliometric Data Ontology (BiDO)_** is a modular OWL 2 ontology that allows the description of bibliometric data in RDF.  The [**_core_**](http://purl.org/spar/bido-core) module of the ontology allows us to describe any entity and the related bibliometric data (through the property `bido:holdsBibliometricDataInTime`) at a certain time (i.e., `tvc:atTime`, a property defined by the imported [TVC ontology design pattern](http://purl.org/spar/tvc) for specifying temporal instants or intervals) and according to a certain agent (through the property `bido:accordingTo`, which is a sub-property of `prov:wasAttributedTo` and allows us to indicate the agent responsible for such bibliometric data). In addition, BiDO imports PROV-O for adding provenance data about the activities related to the creation of such bibliometric data. Two alternative kinds of bibliometric data are specifiable (through the property `bido:withBibliometricData`) in BiDO: numeric and categorial bibliometric data. Numeric bibliometric data are those characterised by a certain integer or float value related to a particular bibliometric measure, while categorial data are those characterised by the assignment of certain categories to a particular bibliographic resource.  Currently, BiDO is composed by three different modules, each extending the core one. [**_Standard bibliometric measures._**](http://purl.org/spar/bido-standard-bibliometric-measures) This module defines a list of possible bibliometric measures that can be used to define bibliometric data of publication-related entities, e.g.: h-index, e-index, journal impact factor, author citation count.  [**_Research career chategories._**](http://purl.org/spar/bido-research-career-category) This module extends the class `bido:CategorialBibliometricData` of the core module with specific categories describing the research career of people described in terms of the specific facets: * the research period considered, i.e., the interval of research years that the algorithm is taking into consideration (e.g., the first 5/10 years); * the kind of curve of the citations received by an author according to the aforementioned period, which is characterised by a trend (flat/increasing/decreasing) and, in the latter two cases, by an acceleration or deceleration point (none or premature, median, overdue acceleration/deceleration); * the slope of such curve, in terms of strength (low/moderate/high) and kind of growth (linear/polynomial/exponential/logarithmic); * the order of magnitude, which categorises the number of citations received in the considered period according to a uniform model of common-sense estimation, which describes intervals of half-order of magnitude – i.e., “[0,1)”, “[1,3)”, “[3,9)”, “[9,27)”, “[27,81)”, “[81,243)”, “[243,729)”, etc.  [**_Review measures._**](http://purl.org/spar/bido-review-measures) The need of describing aspects related to the review process is an important aspect to address by publishers (e.g., Springer) for keeping track of crucial information about conferences and journals. In addition, these data can be crucial for assessing the quality of the venues where researchers publish papers. This module of BiDO describes a list of possible reviews measures that can be used to define bibliometric data of scholarly venues such as conferences, workshops, and journals.  ## Examples of use In the following subsections, we introduce some examples to showcase how to use BiDO. The prefixes that are used in all the examples provided below are defined as follows: @prefix : <http://www.sparontologies.net/example/> . @prefix bido: <http://purl.org/spar/bido/> . @prefix cito: <http://purl.org/spar/cito/> . @prefix conf: <http://lod.springer.com/data_v2/conference/> . @prefix fabio: <http://purl.org/spar/fabio/> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix frbr: <http://purl.org/vocab/frbr/core#> . @prefix journal: <http://www.journals.elsevier.com/> . @prefix onto: <http://lod.springer.com/data_v2/ontology/class/> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix time: <http://www.w3.org/2006/time#> . @prefix tvc: <http://www.essepuntato.it/2012/04/tvc/> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . ### Specifying the impact factor of a journal Numeric bibliometric data are those characterised by a certain integer or float value related to a particular bibliometric measure. BiDO allows one to specify these measures – e.g., h-index, author citation count, e-index, and journal impact factor – to bibliographic resources. For instance, in the following example we assign the 2014 Impact Factor to the Journal of Web Semantics. journal:journal-of-web-semantics a fabio:Journal ; bido:holdsBibliometricDataInTime :web-semantics-if-2014 . :web-semantics-if-2014 a bido:BibliometricDataInTime ; tvc:atTime :2015-validity-period ; bido:accordingTo :thomson-reuters ; bido:withBibliometricData :web-semantics-if-2014-value . :2015-validity-period a time:Interval ; time:hasBeginning :2015-01-01 ; time:hasEnd :2015-12-31 . :web-semantics-if-2014-value a bido:NumericBibliometricData ; bido:hasMeasure bido:journal-impact-factor ; bido:hasNumericValue "2.464"^^xsd:float . :thomson-reuters a foaf:Organization ; foaf:homepace <http://thomsonreuters.com> . ### Assigning a research career category to a person The module of BiDO for describing research career chategories allows one to assign specific categories describing kinds of research careers to people, as described in the following paper: Osborne, F., Peroni, S., Motta, E. (2014). Clustering Citation Distributions for Semantic Categorization and Citation Prediction. In Zhao, J., van Erp, M., Keßler, C., Kauppinen, T., van Ossenbruggen, J., van Hage, W. R. (Eds.), Proceedings of the 4th Workshop on Linked Science (LISC 2014), CEUR Workshop Proceedings 1282: 24–35. Aachen, Germany: CEUR-WS.org. http://ceur-ws.org/Vol-1282/lisc2014_submission_9.pdf For instance, in the example we assign a particular research category (defined mainly by mathematical and geometrical features) to John Doe. :john-doe a foaf:Person ; bido:holdsBibliometricDataInTime :5-years-research-career . :5-years-research-career a bido:BibliometricDataInTime ; tvc:atTime :since-july-2014 ; bido:accordingTo :research-career-algorithm ; bido:withBibliometricData :increasing-with-prem-dec-and-low-log-slope-in-243-729-5-y-beg . :since-july-2014 a time:Interval ; time:hasBeginning :2014-07-11 . :research-career-algorithm a fabio:Algorithm ; cito:isDescribedBy <http://ceur-ws.org/Vol-1282/lisc2014_submission_9> ; frbr:realization :algorithm-implementation . :algorithm-implementation a fabio:ComputerProgram . :increasing-with-prem-dec-and-low-log-slope-in-243-729-5-y-beg a bido:ResearchCareerCategory ; bido:hasCurve :increasing-curve-with-premature-deceleration ; bido:hasSlope :low-logarithmic-slope ; bido:hasOrderOfMagnitude bido:243-729 ; bido:concernsResearchPeriod bido:5-years-beginning . :increasing-curve-with-premature-deceleration a bido:Curve ; bido:hasTrend bido:increasing ; bido:hasAccelerationPoint :premature-deceleration . :low-logarithmic-slope a bido:Slope ; bido:hasStrength bido:low ; bido:hasGrowth bido:logarithmic . ### Conference rank and average of reviews per paper This example shows how to use BiDO for describing numeric and categorial bibliometric data related to a conference, i.e., the '5th International Conference on Automated Deduction'. In particular, we specify average number of reviews per paper and the conference ranking that the conference has. The particular module used for specifying such data is the Review Measures module. conf:cade1980 a onto:Conference ; rdfs:label "5th International Conference on Automated Deduction" ; bido:holdsBibliometricDataInTime conf:cade1980-avg-num-reviews-per-paper , conf:cade1980-cff-rank . conf:cade1980-avg-num-reviews-per-paper a bido:BibliometricDataInTime ; rdfs:label "3 reviews per paper on average (according to Springer)" ; bido:withBibliometricData conf:cade1980-numeric-data-avg-num-reviews-per-paper ; bido:accordingTo :springer . :springer a foaf:Organization ; rdfs:label "Springer" ; foaf:homepage <http://www.springer.com> . conf:cade1980-numeric-data-avg-num-reviews-per-paper a bido:NumericBibliometricData ; rdfs:label "3 reviews per paper on average" ; bido:hasNumericValue "3"^^xsd:integer ; bido:hasMeasure bido:average-of-reviews-per-paper . conf:cade1980-cff-rank a bido:BibliometricDataInTime ; rdfs:label "B (according to CORE)" ; tvc:atTime :2015-validity-period ; bido:withBibliometricData bido:core-b ; bido:accordingTo :core . :2015-validity-period a time:Interval ; time:hasBeginning :2015-01-01 ; time:hasEnd :2015-12-31 . :core a foaf:Organization ; rdfs:label "Computing Research and Education Association of Australasia" ; foaf:homepage <http://www.core.edu.au> . ## Competency Questions BiDO can be used for answering several questions related to bibliometric data. In the following subsections, some of them are introduced together with their respective SPARQL queries. The prefixes that are used in all the SPARQL queries provided below are defined as follows: PREFIX bido: <http://purl.org/spar/bido/> PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX tvc: <http://www.essepuntato.it/2012/04/tvc/> PREFIX time: <http://www.w3.org/2006/time#> ### CQ1 What numeric bibliometric data are held by an entity, and according to which source? SELECT ?entity ?dataSituation ?source ?measure ?numericValue WHERE { ?entity bido:holdsBibliometricDataInTime ?dataSituation . ?dataSituation a bido:BibliometricDataInTime ; bido:withBibliometricData ?bibliometricData . ?bibliometricData a bido:NumericBibliometricData ; bido:hasMeasure ?measure ; bido:hasNumericValue ?numericValue . OPTIONAL { ?dataSituation bido:accordingTo ?source . } } ### CQ2 What is the validity time interval for bibliometric data held in time? SELECT ?entity ?dataSituation ?startDate ?endDate WHERE { ?entity bido:holdsBibliometricDataInTime ?dataSituation . ?dataSituation a bido:BibliometricDataInTime ; tvc:atTime ?timeInterval . OPTIONAL { ?timeInterval time:hasBeginning ?startDate . } OPTIONAL { ?timeInterval time:hasEnd ?endDate . } } ### CQ3 Which research career category and detailed trajectory features are assigned to a person? SELECT ?person ?category ?trend ?slopeStrength ?slopeGrowth ?orderOfMagnitude ?period WHERE { ?person a foaf:Person ; bido:holdsBibliometricDataInTime ?dataSituation . ?dataSituation bido:withBibliometricData ?category . ?category a bido:ResearchCareerCategory . OPTIONAL { ?category bido:hasCurve ?curve . ?curve bido:hasTrend ?trend . } OPTIONAL { ?category bido:hasSlope ?slope . ?slope bido:hasStrength ?slopeStrength ; bido:hasGrowth ?slopeGrowth . } OPTIONAL { ?category bido:hasOrderOfMagnitude ?orderOfMagnitude . } OPTIONAL { ?category bido:concernsResearchPeriod ?period . } } ### CQ4 Which algorithms or organizations produce or evaluate bibliometric data held by an entity? SELECT ?entity ?dataSituation ?source ?sourceType WHERE { ?entity bido:holdsBibliometricDataInTime ?dataSituation . ?dataSituation a bido:BibliometricDataInTime ; bido:accordingTo ?source . OPTIONAL { ?source a ?sourceType . } } ### CQ5 What categorical bibliometric rankings or measures (such as conference ranks or categorical reviews) are assigned to an entity? SELECT ?entity ?dataSituation ?bibliometricData ?source WHERE { ?entity bido:holdsBibliometricDataInTime ?dataSituation . ?dataSituation a bido:BibliometricDataInTime ; bido:withBibliometricData ?bibliometricData . OPTIONAL { ?dataSituation bido:accordingTo ?source . } FILTER NOT EXISTS { ?bibliometricData a bido:NumericBibliometricData . } }

bibliometric data

bibliometrics

scholarly publishing

scientometrics

semantic publishing

Semantic Publishing and Referencing Ontologies

SPAR Ontologies

Enrico Motta (https://orcid.org/0000-0003-0015-1952)

Francesco Osborne (https://orcid.org/0000-0001-6557-3131)

Silvio Peroni (http://orcid.org/0000-0003-0530-4305)

Sebastian Barzaghi (https://orcid.org/0000-0002-0799-1527)

2014-08-11

2015-07-13

2026-10-05

2026-10-05

Osborne, F., Peroni, S., Motta, E. (2014). Clustering Citation Distributions for Semantic Categorization and Citation Prediction. In Proceedings of the 4th Workshop on Linked Science (LISC 2014): 24–35. http://ceur-ws.org/Vol-1282/lisc2014_submission_9.pdf

https://doi.org/10.25504/FAIRsharing.d7f0a9

bido

http://purl.org/spar/bido