Scholia is a tool to handle scienti c bibliographic information through Wikidata. The Scholia Web service creates on-the- y scholarly pro les for researchers, organizations, journals, publishers, individual scholarly works, and for research topics. To collect the data, it queries the SPARQL-based Wikidata Query Service. Among several display formats available in Scholia are lists of publications for individual researchers and organizations, publications per year, employment timelines, as well as coauthor and topic networks and citation graphs. The Python package implementing the Web service is also able to format Wikidata bibliographic entries for use in LaTeX/BIBTeX.
7 http://wikipapers.referata.com/, https://acawiki.org/, http://wikilit.
referata.com/ and http://neuro.compute.dtu.dk/wiki/ 8 https://www.mediawiki.org/wiki/Help:Templates 9 https://www.wikidata.org 10 https://query.wikidata.org 11 The API is at https://www.wikidata.org/w/api.php, and the dump les are available at https://www.wikidata.org/w/api.php. 12 https://github.com/larsgw/citation.js Domain Broad coverage Size > 600; 000 scienti c articles Style of Metadata Export via, e.g., Lars Willighagen's citation.js12 Persistent Inbound Links? Yes, with the Q identi ers Persistent Outbound Links Yes, with identi ers like DOI, PMID, PMCID, arXiv Full Text? Via identi ers like DOI or PMCID; dedicated property for `full text URL' Access Free access added to Wikidata, and we have so far experienced very few deletions of such data in reference to a notability criterion. The current interest in expanding bibliographic information on Wikidata has been boosted by the WikiCite project, which aims at collecting bibliographic information in Wikidata and held its rst workshop in 2016 [23].
The bibliographic information collected on Wikidata is about books, articles (including preprints), authors, organizations, journals, and publishers. These items (corresponding to subject in Semantic Web parlance) can be interlinked through Wikidata properties (corresponding to the predicate), such as author (P50),13 published in (P1433), publisher (P123), series (P179), main theme (P921), educated at (P69), employer (P108), part of (P361), sponsor (P859, can be used for funding), cites (P2860) and several other properties.14
Numerous properties exist on Wikidata for deep linking to external resources, e.g., for DOI, PMID, PMCID, arXiv, ORCID, Google Scholar, VIAF, Crossref funder ID, ZooBank and Twitter. With these many identi ers, Wikidata can act as a hub for scientometrics studies between resources. If no dedicated Wikidata property exists for a resource, one of the URL properties can work as a substitute for creating a deep link to a resource. For instance, P1325 (external data available at ) can point to raw or supplementary data associated with a paper. We have used this scheme for scienti c articles associated with datasets stored in OpenfMRI [20], an online database with raw brain measurements, mostly from functional magnetic resonance imaging studies. Using WDQS, we query the set of OpenfMRI-linked items using the following query: ? item wdt : P1325 ? resource . filter s tr st ar ts ( str (? resource ) ,
" https :// openfmri . org / dataset / " )
13 The URI for Wikidata property P50 is http://www.wikidata.org/prop/direct/P50
or with the conventional pre x wdt:P50. Similarly for any other Wikidata property.
14 A Wikidata table lists properties that are commonly used in bibliographic contexts:
https://www.wikidata.org/wiki/Template:Bibliographical_properties .
A similar scheme is used for a few of the scienti c articles associated with data
in the neuroinformatics databases Neurosynth [26] and NeuroVault [
When bibliographic items exist in Wikidata, they can be used as references to support claims (corresponding to triplets with extra quali ers) in other items of Wikidata, e.g., a biological claim can be linked to the Wikidata item for a scienti c journal.
By using these properties systematically according to an emerging data model,15 editors have extended the bibliographic information in Wikidata. Particularly instrumental in this process was a set of tools built by Magnus Manske, QuickStatements16 and Source MetaData,17 including the latter's associated Resolve authors tool.18 Information can be extracted from, e.g., PubMed, PubMed Central and arXiv and added to Wikidata.
How complete is Wikidata in relation to scienti c bibliographic information? Journals and universities are well represented. For instance, 31,895 Wikidata items are linked with the identi er for the Collections of the National Library of Medicine (P1055). Far less covered are individual articles, individual researchers, university departments and citations between scienti c articles. Most of the scienti c articles in Wikidata are claimed to be an instance of (P31) the Wikidata item scienti c article (Q13442814). With a WDQS query, we can count the number of Wikidata items linked to scienti c article: select ( count (? work ) as ? count ) where {
? work wdt : P31 wd : Q13442814 . } As of 12 March 2017, the query returned the result 615,182, see also Table 1. In comparison, arXiv states having 1,240,585 e-prints and ACM Digital Library states to have 24,110 proceedings.19 There were 8,617 authors associated with Wikidata items linked through the author property (P50) to items that are instance of scienti c article, and the number of citations as counted by triples using the P2860 (cites) property stood at 2,729,164: select ( count (? citedwork ) as ? count ) where {
? work wdt : P2860 ? citedwork . }
The completeness can be fairly uneven. Articles from PLOS journals are much better represented than articles from the journals of IEEE.
The sponsor property has been used extensively for National Institute for Occupational Safety and Health (NIOSH) with 52,852 works linking to the organization, 18,135 of which are instance of scienti c articles, but apart from NIOSH, the use of the property has been very limited for scienti c articles.20 15 https://www.wikidata.org/wiki/Wikidata:WikiProject_Source_MetaData/
Bibliographic_metadata_for_scholarly_articles_in_Wikidata 16 https://tools.wmflabs.org/wikidata-todo/quick_statements.php 17 hhttps://tools.wmflabs.org/sourcemd/ 18 https://tools.wmflabs.org/sourcemd/new_resolve_authors.php 19 As of 9 March 2017 according to https://arxiv.org/ and https://dl.acm.org/ contents_guide.cfm 20 National Institute for Occupational Safety and Health has a Wikimedian-in
Residence program, through which James Hare has added many of the NIOSH works.
of the person, e.g., articles about Mardia. Likewise, universities can be viewed, for instance, as organizations or as sponsors. Indeed, any Wikidata item can be viewed in any Scholia aspect, but Scholia can show no data if the user selects a \wrong" aspect, i.e. one for which no relevant data is available in Wikidata.
For each aspect, we make multiple WDQS queries based on the Wikidata item for which the results in the panels are displayed, | technically in embedded iframes. For the author aspect, Scholia queries WDQS for the list of publications, showing the result in a table, displaying a bar chart of the number of publications per year, number of pages per year, venue statistics, co-author graph, topics of the published works (based on the \main theme" property), associated images, education and employment history as timelines, academic tree, map with locations associated with the author, and citation statistics { see Fig. 1 for an example of part of an author aspect page. The citation statistics displays the most cited work, citations by year and citing authors. For the academic tree and the citation graph, we make use of Blazegraph's graph analytics RDF GAS API21 that is available in WDQS. The embedded WDQS results link back to WDQS where a user can modify the query. The interactive editor of WDQS allows users not familiar with SPARQL to make simple modi cations without directly editing the SPARQL code.
Related to their work on quantifying conceptual novelty in the biomedical literature [14], Shubhanshu Mishra and Vetle Torvik have set up a website proling authors in PubMed datasets: LEGOLAS.22 Among other information, the website shows the number of articles per year, the number of citations per year, the number of self-citations per year, unique collaborations per year and NIH grants per year as bar charts that are color-coded according to, e.g., author role ( rst, solo, middle or last author). Scholia uses WDQS for LEGOLAS-like plots. Figure 2 displays one such example for the number of published items as a function of year of publication on an author aspect page, where the components of the bars are color-coded according to author role.
For the organization aspect, Scholia uses the employer and a liated Wikidata properties to identify associated authors, and combines this with the author query for works. Scholia formulates SPARQL queries with property paths to identify suborganizations of the queried organization, such that authors a liated with a suborganization are associated with the queried organization. Figure 3 shows a corresponding bar chart, again inspired by the LEGOLAS style. Here, the Cognitive Systems section at the Technical University of Denmark is displayed with the organization aspect. It combines work and author data. The 21 https://wiki.blazegraph.com/wiki/index.php/RDF_GAS_API 22 http://abel.lis.illinois.edu/legolas/ bar chart uses the P1104 (number of pages) Wikidata property together with a normalization based on the number of authors on each of the work items. The bars are color-coded according to individual authors associated with the organization. In this case, the plot is heavily biased, as only a very limited subset of publications from the organization is currently present in Wikidata, and even the available publications may not have the P1104 property set. Other panels shown in the organization aspect are a co-author graph, a list of recent publications formatted in a table, a bubble chart with most cited papers with a liated rst author and a bar chart with co-author-normalized citations per year. This last panel counts the number of citations to each work and divides it by the number of authors on the cited work, then groups the publications according to year and color-codes the bars according to author.
For the publisher aspect, Scholia queries all items where the P123 property (publisher) has been set. With these items at hand, Scholia can create lists of venues (journals or proceedings) ordered according to the number of works (papers) published in each of them, as well as lists of works ordered according to citations. Fig. 4 shows an example of a panel on the publisher aspect page with a scatter plot detailing journals from BioMed Central. The position of each journal in the plot reveals impact factor-like information.
For the work aspect, Scholia lists citations and produces a partial citation
graph. Fig. 5 shows a screenshot of the citation graph panel from the work
Fig. 4. Screenshot from Scholia's publisher aspect with number of publications versus
number of citations for works published by BioMed Central. The upper right point
with many citations and many published works is the journal Genome Biology. From
https://tools.wmflabs.org/scholia/publisher/Q463494.
aspect for a speci c article [
A few redirects for external identi ers are also implemented. For instance,
with Uta Frith's Twitter name `utafrith', /scholia/twitter/utafrith will redirect
Listing 1. SPARQL query on the work aspect page for claims supported by a work,
| in this case Q22253877 [
SELECT distinct ? item ? itemLabel ? property ? propertyLabel ? value ? valueLabel WHERE { ? item ?p ? statement . ? property wikibase : claim ?p . ? statement ?a ? value . ? item ?b ? value . ? statement prov : wasDerivedFrom / <http :// www . wikidata . org / prop / reference /P248 > wd: Q22253877 .
SERVICE wikibase : label {
bd: serviceParam wikibase : language "en" } } ORDER BY ? itemLabel to /scholia/Q8219, which in turn will redirect to /scholia/author/Q8219. Scholia implements similar functionality for DOI, ORCID and GitHub user identi er.
As a command-line tool, Scholia provides a prototype tool that uses Wikidata and its bibliographic data in a LATEX and BibTEX environment. The current implementation looks up citations in the latex-generated .aux le and queries Wikidata's MediaWiki API to get cited Wikidata items. The retrieved items are formatted and written to a .bib that bibtex can use to format the bibliographic items for inclusion in the LATEX document. The work ow for a LATEX document with the lename example.tex is latex example python -m scholia . tex write -bib -from - aux example . aux bibtex example latex example latex example Here, the example document could read \ documentclass { article } \ usepackage [ utf8 ]{ inputenc } \ begin { document } \ cite { Q18507561 } \ bibliographystyle { plain } \ bibliography { example } \ end { document }
In this case, the \cite command cites Q18507561 (Wikidata: a free collaborative knowledgebase [25]). A DOI can also be used in the \cite command: instead of writing \cite{Q18507561}, one may write \cite{10.1145/2629489} to get the same citation. Scholia matches on the \10." DOI pre x and makes a SPARQL query to get the relevant Wikidata item.
The scheme presented above can take advantage of the many available style les of BibTEX to format the bibliographic items in the various ways requested by publishers. We have used Scholia for reference management in this paper. 5
WDQS and Scholia can provide many di erent scientometrics views of the data available in Wikidata. The bibliographic data in Wikidata are still quite limited, but the number of scientometrically relevant items will likely continue to grow considerably in the coming months and years.
The continued growth of science data on Wikidata can have negative impact on Scholia, making the on-the- y queries too resource demanding. In the current version, there are already a few queries that run into WDQS's time out, e.g., it happens for the view of co-author-normalized citations per year for Harvard University. If this becomes a general problem, we will need to rede ne the queries. Indeed, the WDQS time out will be a general problem if we want to perform large-scale scientometrics studies. An alternative to using live queries would be using dumps, which are available in several formats on a weekly basis, with daily increments in between.23 The problem is not a limitation of SPARQL, but a limitation set by the server resources. Some queries may be optimized, especially around the item labeling.
Working with Scholia has made us aware of several issues. Some of these are minor limitations in the Wikidata and WDQS systems. The Wikidata label length is limited to 250 characters, whereas the `monolingual text' datatype used for the `title' property (P1476) is limited to 400 characters. There are scholarly articles with titles longer than those limits.
Wikidata elds cannot directly handle subscripts and superscripts, which commonly appear in titles of articles about chemical compounds, elementary particles or mathematical formulas. Other formatting in titles cannot directly be handled in Wikidata's title property,24 and recording a date such as \Summer 2011" is di cult.
Title and names of items can change. Authors can change names, e.g. due to marriage, and journals can change titles, e.g. due to a change of scope or transfer of ownership. For instance, the Journal of the Association for Information Science and Technology has changed names several times over the years.25 Wikidata can handle multiple titles in a single Wikidata item and with quali ers describe the dates of changes in title. For scientometrics, this ability is an advantage in principle, but multiple titles can make it cumbersome to handle when Wikidata is used as a bibliographic resource in document preparation, particularly for articles published near the time when the journal changed its name. One way to alleviate this problem would be to split the journal's Wikidata item into several, but this is not current practice.
In Wikidata, papers are usually not described to be a liated with organizations. Scholia's ability to make statistics on scienti c articles published by organization is facilitated by the fact that items about scienti c articles can link to items about authors, which can link to items about organizations. It is possible to link scienti c articles to organization by using Wikidata quali ers in connection with the author property. However, this scheme is currently in limited use.
This scarcity of direct a liation annotation on Wikidata items about articles means that scientometrics on the organizational level are unlikely to be precise at present. In the current version, Scholia even ignores any temporal quali er for 23 https://www.wikidata.org/wiki/Wikidata:Database_download 24 By way of an example, consider the article \A library of 7TM receptor C-terminal tails. Interactions with the proposed post-endocytic sorting proteins ERM-binding phosphoprotein 50 (EBP50), N-ethylmaleimide-sensitive factor (NSF), sorting nexin 1 (SNX1), and G protein-coupled receptor-associated sorting protein (GASP)", an article with the title \Cerebral 5-HT2A receptor binding is increased in patients with Tourette's syndrome", where \2A" is subscripted and \User's Guide to the amsrefs Package", where the \amsrefs" is set in monospaced font. 25 http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2330-1643/issues records these former titles: Journal of the American Society for Information Science and Technology, Journal of the American Society for Information Science, and American Documentation. the a liation and employer property, meaning that a researcher moving between several organization gets his/her articles counted under multiple organizations.
Data modeling on Wikidata gives rise to re ections on what precisely a \publisher" and a \work" is. A user can set the publisher Wikidata property of a work to a corporate group, a subsidiary or possibly an imprint. For instance, how should we handle Springer Nature, BioMed Central and Humana Press ?
Functional Requirements for Bibliographic Records (FRBR) [11] suggests a scheme for works, expressions, manifestations and \items". In Wikipedia, most items are described on the work level as opposed to the manifestation level (e.g., book edition), while citations should usually go to the manifestation level. How should one deal with scienti c articles that have slightly di erent \manifestations", such as preprint, electronic journal edition, paper edition and postprint, or editorials that were co-published in multiple journals with identical texts? An electronic and a paper edition may di er in their dates of publication, but otherwise have the same bibliographic data, while a preprint and its journal edition usually have di erent identi ers and may also di er in content. From a scientometrics point of view, these di erence in manifestation may not matter in some cases, but could be the focus of others. Splitting a scienti c article as a work (in the FRBR sense) over multiple Wikidata items seems only to complicate matters.
The initial idea for Scholia was to create a researcher pro le based on Wikidata data with list of publications, picture and CV-like information. The inspiration came from a blog post by Lambert Heller: What will the scholarly pro le page of the future look like? Provision of metadata is enabling experimentation.26 In this blog post, he discussed the di erent features of several scholarly Web services: ORCID, ResearchGate, Mendeley, Pure, VIVO, Google Scholar and ImpactStory. In Table 3, we have set up a table listing Heller's features for the Wikidata{Scholia combination. Wikidata{Scholia performs well in most aspects, but in the current version, Scholia has no backend for storing user data, and user features such as forum, Q&A and followers are not available.
Beyond the features listed by Heller, which features set Wikidata{Scholia apart from other scholarly Web services? The collaborative nature of Wikidata means that Wikidata users can create items for authors that do not have an account on Wikidata. In most other systems, the researcher as a user of the system has control over his/her scholarly pro le and other researchers/users cannot make amendment or corrections. Likewise, when one user changes an existing item, this change will be re ected in subsequent live queries of that item, and it may still be in future dumps if not reverted or otherwise modi ed before the dump creation.
With WDQS queries, Scholia can combine data from di erent types of items in Wikidata in a way that is not usually possible with other scholarly pro le Web services. For instance, Scholia generates lists of publications for an organization by combining items for works and authors and can show co-author graphs re26 http://blogs.lse.ac.uk/impactofsocialsciences/2015/07/16/ scholarly-profile-of-the-future/ Business model Y Community donations and funding from foundations to Wikimedia Foundation and a liated chapters Portrait picture Y The P18 property can record Wikimedia Commons images related to a researcher Alternative names Y Aliases for all items, not just researchers IDs / pro les in other sys- Y Numerous links to external identi ers: ORCID, Scotems pus, Google Scholar, etc.
Papers and similar Y Papers and books are individual Wikidata items Uncommon research prod- Y For instance, software can be associated with a deucts veloper Grants, third party funding (N) Currently no property for grant holders and probably no individual grants in Wikidata. The sponsor property can be used to indicate the funding of a paper Current institution Y A liation and employer can be recorded in Wikidata Former employers, educa- Y Education, academic degree can be speci ed, and fortion mer employers can be set by way of quali ers Self-assigned keywords (Y) The main theme of a work can be speci ed, interests or eld of work can be set for a person. The values must be items in Wikidata. Users can create items.
Concepts from controlled Y See above vocabulary Social graph of follower- N There are no user accounts on the current version of s/friends Scholia.
Social graph of coauthors Y Citation/attention meta- Y Citations between scienti c articles are recorded with data from platform itself a property that can be used to count citations. Citation/reference between Wikidata items.
Citation/attention meta- (N) Deep links to other citation resources like Google data from other source Scholar and Scopus.
Comprehensive search to (N) Several tools liks Magnus Manske's Source MetaData match/include papers that look up bibliographic metadata based on DOI,
PMID or PMCID Forums, Q&A etc.
Deposit own papers
N (Y) Appropriately licensed papers can be uploaded to
Wikimedia Commons or Wikisource Research administration N tools Reuse of data from outside Y API, WDQS, XML dump, third-party services of the service stricted by a liation. Similarly, the co-author graph can be restricted to authors publishing works annotated with a speci c main theme. Authors are typically annotated with gender in Wikidata, so Scholia can show gender color-coding of co-author graphs. On the topic aspect page, the Scholia panel that shows the most cited works that are cited from works around the topic can point to an important paper for a topic { even if the paper has not been annotated with the topic { by combining the citations data and topic annotation. References for claims are an important part of Wikidata and also singles Wikidata out among other scholarly pro le Web service, and it acts as an extra scientometrics dimension. The current version of Scholia has only a single panel where the query uses references: the \Supports the following statement(s)" on the work aspect page, but it is possible to extend the use of this scientometrics dimension. 6
This work was supported by Innovationsfonden through the DABAI project. The work on Scholia was spawned by the WikiCite project [23]. We would like to thank the organizers of the workshop, particular Dario Taraborelli. Finn Arup Nielsen's participation in the workshop was sponsored by an award from the Reinholdt W. Jorck og Hustrus Fund. We would also like to thank Magnus Manske and James Hare for considerable work with Wikidata tools and data in the context of WikiCite.