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Around 2.7 million Wikidata items have an illustrative image. These files, you might say, are Wikimedia's stock images, and if the number is large, it is still only 5% or so of items that have one. All such images are taken from Wikimedia Commons, which has 50 million media files. One key issue is how to expand the stock.
Indeed, there is a tool. WD-FIST exploits the fact that each Wikipedia is differently illustrated, mostly with images from Commons but also with fair use images. An item that has sitelinks but no illustrative image can be tested to see if the linked wikis have a suitable one. This works well for a volunteer who wants to add images at a reasonable scale, and a small amount of SPARQL knowledge goes a long way in producing checklists.
Gran Teatro, Cáceres, Spain, at night
It should be noted, though, that there are currently 53 Wikidata properties that link to Commons, of which P18 for the basic image is just one. WD-FIST prompts the user to add signatures, plaques, pictures of graves and so on. There are a couple of hundred monograms, mostly of historical figures, and this query allows you to view all of them. commons:Category:Monograms and its subcategories provide rich scope for adding more.
And so it is generally. The list of properties linking to Commons does contain a few that concern video and audio files, and rather more for maps. But it contains gems such as P3451 for "nighttime view". Over 1000 of those on Wikidata, but as for so much else, there could be yet more.
Go on. Today is Wikidata's birthday. An illustrative image is always an acceptable gift, so why not add one? You can follow these easy steps: (i) log in at https://tools.wmflabs.org/widar/, (ii) paste the Petscan ID 6263583 into https://tools.wmflabs.org/fist/wdfist/ and click run, and (iii) just add cake.
GLAM ♥ data — what is a gallery, library, archive or museum without a catalogue? It follows that Wikidata must love librarians. Bibliography supports students and researchers in any topic, but open and machine-readable bibliographic data even more so, outside the silo. Cue the WikiCite initiative, which was meeting in conference this week, in the Bay Area of California.
Wikidata training for librarians at WikiCite 2018
In fact there is a broad scope: "Open Knowledge Maps via SPARQL" and the "Sum of All Welsh Literature", identification of research outputs, Library.Link Network and Bibframe 2.0, OSCAR and LUCINDA (who they?), OCLC and Scholia, all these co-exist on the agenda. Certainly more library science is coming Wikidata's way. That poses the question about the other direction: is more Wikimedia technology advancing on libraries? Good point.
Wikimedians generally are not aware of the tech background that can be assumed, unless they are close to current training for librarians. A baseline definition is useful here: "bash, git and OpenRefine". Compare and contrast with pywikibot, GitHub and mix'n'match. Translation: scripting for automation, version control, data set matching and wrangling in the large, are on the agenda also for contemporary library work. Certainly there is some possible common ground here. Time to understand rather more about the motivations that operate in the library sector.
Links
Wikidata and Libraries: Facilitating Open Knowledge, book chapter by Mairelys Lemus-Rojas, metadata librarian and Lydia Pintscher, Wikidata Product Manager, from Leveraging Wikipedia: Connecting Communities of Knowledge (2018)
LD4P and WikiCite: Opportunities for collaboration, WikiCite 2018 program abstract, Christine Fernsebner Eslao of Harvard Library Information and Technical Services and Michelle Futornick, Linked Data for Production Program Manager at Stanford University
Besides the handiness of Zotero's warehousing of personal citation collections, the Zotero translator underlies the citoid service, at work behind the VisualEditor. Metadata from Wikidata can be imported into Zotero; and in the other direction the zotkat tool from the University of Mannheim allows Zotero bibliographies to be exported to Wikidata, by item creation. With an extra feature to add statements, that route could lead to much development of the focus list (P5008) tagging on Wikidata, by WikiProjects.
Zotero demo video
There is also a large-scale encyclopedic dimension here. The construction of Zotero translators is one facet of Web scraping that has a strong community and open source basis. In that it resembles the less formal mix'n'match import community, and growing networks around other approaches that can integrate datasets into Wikidata, such as the use of OpenRefine.
Looking ahead, the thirtieth birthday of the World Wide Web falls in 2019, and yet the ambition to make webpages routinely readable by machines can still seem an ever-retreating mirage. Wikidata should not only be helping Wikimedia integrate its projects, an ongoing process represented by Structured Data on Commons and lexemes. It should also be acting as a catalyst to bring scraping in from the cold, with institutional strengths as well as resourceful code.
T115158Write a Zotero translator and document process for creating new Zotero translator and getting it live in production, long Phabricator thread 2015–17.
Recently Jimmy Wales has made the point that computer home assistants take much of their data from Wikipedia, one way or another. So as well as getting Spotify to play Frosty the Snowman for you, they may be able to answer the question "is the Pope Catholic?" Possibly by asking for disambiguation (Coptic?).
Headlines about data breaches are now familiar, but the unannounced circulation of information raises other issues. One of those is Gresham's law stated as "bad data drives out good". Wikipedia and now Wikidata have been criticised on related grounds: what if their content, unattributed, is taken to have a higher standing than Wikimedians themselves would grant it? See Wikiquote on a misattribution to Bismarck for the usual quip about "law and sausages", and why one shouldn't watch them in the making.
Wikipedia has now turned 18, so should act like as adult, as well as being treated like one. The Web itself turns 30 some time between March and November this year, per Tim Berners-Lee. If the Knowledge Graph by Google exemplifies Heraclitean Web technology gaining authority, contra GIGO, Wikimedians still have a role in its critique. But not just with the teenage skill of detecting phoniness.
There is more to beating Gresham than exposing the factoid and urban myth, where WP:V does do a great job. Placeholders must be detected, and working with Wikidata is a good way to understand how having one statement as data can blind us to replacing it by a more accurate one. An example that is important to open access is that, firstly, the term itself needs considerable unpacking, because just being able to read material online is a poor relation of "open"; and secondly, trying to get Creative Commons license information into Wikidata shows up issues with classes of license (such as CC-BY) standing for the actual license in major repositories. Detailed investigation shows that "everything flows" exacerbates the issue. But Wikidata can solve it.
Systematic reviews are basic building blocks of evidence-based medicine, surveys of existing literature devoted typically to a definite question that aim to bring out scientific conclusions. They are principled in a way Wikipedians can appreciate, taking a critical view of their sources.
PRISMA flow diagram for a systematic review
Ben Goldacre in 2014 wrote (link below) "[...] : the "information architecture" of evidence based medicine (if you can tolerate such a phrase) is a chaotic, ad hoc, poorly connected ecosystem of legacy projects. In some respects the whole show is still run on paper, like it's the 19th century." Is there a Wikidatan in the house? Wouldn't some machine-readable content that is structured data help?
Most likely it would, but the arcana of systematic reviews and how they add value would still need formal handling. The PRISMA standard dates from 2009, with an update started in 2018. The concerns there include the corpus of papers used: how selected and filtered? Now that Wikidata has a 20.9 million item bibliography, one can at least pose questions. Each systematic review is a tagging opportunity for a bibliography. Could that tagging be reproduced by a query, in principle? Can it even be second-guessed by a query (i.e. simulated by a protocol which translates into SPARQL)? Homing in on the arcana, do the inclusion and filtering criteria translate into metadata? At some level they must, but are these metadata explicitly expressed in the articles themselves? The answer to that is surely "no" at this point, but can TDM find them? Again "no", right now. Automatic identification doesn't just happen.
Actually these questions lack originality. It should be noted though that WP:MEDRS, the reliable sources guideline used here for health information, hinges on the assumption that the usefully systematic reviews of biomedical literature can be recognised. Its nutshell summary, normally the part of a guideline with the highest density of common sense, allows literature reviews in general validity, but WP:MEDASSESS qualifies that indication heavily. Process wonkery about systematic reviews definitely has merit.
The term Applications Programming Interface or API is 50 years old, and refers to a type of software library as well as the interface to its use. While a compiler is what you need to get high-level code executed by a mainframe, an API out in the cloud somewhere offers a chance to perform operations on a remote server. For example, the multifarious bots active on Wikipedia have owners who exploit the MediaWiki API.
APIs (called RESTful) that allow for the GET HTTP request are fundamental for what could colloquially be called "moving data around the Web"; from which Wikidata benefits 24/7. So the fact that the Wikidata SPARQL endpoint at query.wikidata.org has a RESTful API means that, in lay terms, Wikidata content can be GOT from it. The programming involved, besides the SPARQL language, could be in Python, younger by a few months than the Web.
Magic words, such as occur in fantasy stories, are wishful (rather than RESTful) solutions to gaining access. You may need to be a linguist to enter Ali Baba's cave or the western door of Moria (French in the case of "Open Sesame", in fact, and Sindarin being the respective languages). Talking to an API requires a bigger toolkit, which first means you have to recognise the tools in terms of what they can do. On the way to the wikt:impactful or polymathic modern handling of facts, one must perhaps take only tactful notice of tech's endemic problem with documentation, and absorb the insightful point that the code in APIs does articulate the customary procedures now in place on the cloud for getting information. As Owl explained to Winnie-the-Pooh, it tells you The Thing to Do.
Working With Wikibase From Go, Digital Flapjack blogpost 26 November 2018, Michael Dales, developer for ScienceSource using golang, with a software engineer's view on Wikibase and the MediaWiki API
Talk of cloud computing draws a veil over hardware, but also, less obviously but more importantly, obscures such intellectual distinction as matters most in its use. Wikidata begins to allow tasks to be undertaken that were out of easy reach. The facility should not be taken as the real point.
Coming in from another angle, the "executive decision" is more glamorous; but the "administrative decision" should be admired for its command of facts. Think of the attitudes ad fontes, so prevalent here on Wikipedia as "can you give me a source for that?", and being prepared to deal with complicated analyses into specified subcases. Impatience expressed as a disdain for such pedantry is quite understandable, but neither dirty data nor false dichotomies are at all good to have around.
Issue 13 and Issue 21, respectively on WP:MEDRS and systematic reviews, talk about biomedical literature and computing tasks that would be of higher quality if they could be made more "administrative". For example, it is desirable that the decisions involved be consistent, explicable, and reproducible by non-experts from specified inputs.
What gets clouded out is not impossibly hard to understand. You do need to put together the insights of functional programming, which is a doctrinaire and purist but clearcut approach, with the practicality of office software. Loopless computation can be conceived of as a seamless forward march of spreadsheet columns, each determined by the content of previous ones. Very well: to do a backward audit, when now we are talking about Wikidata, we rely on integrity of data and its scrupulous sourcing: and clearcut case analyses. The MEDRS example forces attention on purge attempts such as Beall's list.
Two dozen issues, and this may be the last, a valediction at least for a while.
It's time for a two-year summation of ContentMine projects involving TDM (text and data mining).
Wikidata and now Structured Data on Commons represent the overlap of Wikimedia with the Semantic Web. This common ground is helping to convert an engineering concept into a movement. TDM generally has little enough connection with the Semantic Web, being instead in the orbit of machine learning which is no respecter of the semantic. Don't break a taboo by asking bots "and what do you mean by that?"
The ScienceSource project innovates in TDM, by storing its text mining results in a Wikibase site. It strives for compliance of its fact mining, on drug treatments of diseases, with an automated form of the relevant Wikipedia referencing guideline MEDRS. Where WikiFactMine set up an API for reuse of its results, ScienceSource has a SPARQL query service, with look-and-feel exactly that of Wikidata's at query.wikidata.org. It also now has a custom front end, and its content can be federated, in other words used in data mashups: it is one of over 50 sites that can federate with Wikidata.
The human factor comes to bear through the front end, which combines a link to the HTML version of a paper, text mining results organised in drug and disease columns, and a SPARQL display of nearby drug and disease terms. Much software to develop and explain, so little time! Rather than telling the tale, Facto Post brings you ScienceSource links, starting from the how-to video, lower right.
Please be aware that this is a research project in development, and may have outages for planned maintenance. That will apply for the next few days, at least. The ScienceSource wiki main page carries information on practical matters. Email is not enabled on the wiki: use site mail here to Charles Matthews in case of difficulty, or if you need support. Further explanatory videos will be put into commons:Category:ContentMine videos.
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