Wikipedia + open access = not quite a revolution (not yet at least)

The title of the arxiv blog post sounded so catchy and wishful thinking into a high truthlikeness: “Why Wikipedia + open access = revolution”, summarizing and expanding on arxiv.org/abs/1506.07608 with the title “Amplifying the Impact of Open Access: Wikipedia and the Diffusion of Science.” [1], with some quotes:

“The odds that an open access journal is referenced on the English Wikipedia are 47% higher compared to closed access journals,” say Teplitskiy and co.

Open access publishing has changed the way scientists communicate with each other but Teplitskiy and buddies have now shown that its influence is much more significant. “Our research suggests that open access policies have a tremendous impact on the diffusion of science to the broader general public through an intermediary like Wikipedia,” says Teplitskiy and co.

It means that open access publications are dramatically amplifying the way science diffuses through the world and ultimately changing the way we understand the universe around us.

I sooo want to believe. And, honestly, when I search for something and Wikipedia is the first hit and I do click, it does seem to give a decent introductory overview of something I know little about so that I can make a better start for searching the real sources. I never bothered to look up my own areas of specialisation, other than when a co-author mentioned there was (she put?—I can’t recall) a reference to her tool in Wikipedia some time ago. But there’s that nagging comment to the technologyreview blog post saying the same thing, and adding that when s/he looked up his/her own field, s/he

“then realized that in my own field, my main reaction was to want to scream at the cherry picking of sources to promote some minor researcher.”

So, I looked up “ontology engineering” and “Ontologies” that redirected to “Ontology (information science)” (‘information science’, tsk!)… and I kinda screamed. The next sections are, first, about the merits of the arxiv paper (outcome: their conclusions are certainly rather quite exaggerated) and, second, I’ll use that ‘ontology (information science)’ entry to dig a bit deeper as use case, using both the English entry and in several other languages as that’s what the arxiv paper covers as well. I’ll close with some thoughts on what to do about it.

 

On the arxiv paper’s data and results

There are several limitations to the paper; some of them discussed by its authors, some are not. The arxiv paper does not distinguish between online freely available scientific literature where only the final typesetted version is behind a paywall and official ‘open access’. This is problematic for processing the computer science entries in Wikipedia for trying to validate their hypothesis. In addition, they considered only journals with their open access policy, and journal-level analysis (cf article-level analysis), idem for the problematic ISI impact factor, and only those 21000 listed in Scopus, amounting eventually to the (ISI index-)top 4721 journals of which 335 open access to test Wikipedia content against. The open access list was taken from being listed in the directory of OA journals, ignoring the difference between ‘green’ and ‘gold’ and paywall-access from, say Elsevier. Overall, this already does not bode well for extending the obtained conclusion to computer science entries and, hence, the diffusion of knowledge claim.

The authors admit they may undercount references for the non-English entries, but they have few references anyway (Fig 1 in the arxiv paper), so it’s basically largely an English-Wikipedia analysis after all, i.e., so the conclusion is not really straightforwardly extending to ‘diffusion of knowledge’ for the non-English speaking world.

The statistical model is described on p19 of the pdf, and I don’t quite follow the rationale, with an elusive set of ‘journal characteristics’ and some estimated variables without detail. Maybe some stats person can shed a light on it.

Then the bubble-figure in the technologyreview, which is Fig 8 in the arxiv paper and it is reproduced in the screenshot below, which “shows that across 50 [non-English] Wikipedias, there is an inverse relationship between the effects of accessibility and status on referencing”. Come again? It’s not like the regression line fits well. And why are the language entries—presumably independent of one another—in a relation after all? Notwithstanding, the odds for a Serbian entry to have a reference to an open access journal is some 275% higher than to a paywalled one, vs entries in Turkish that cite higher impact factor journals some 200% more often, according to the arxiv paper. I haven’t found details of that data, though, other than a back-of-the-envelope calculation when glancing over the figure: Serbian has a 1.5 for impact and a 3.75 or so for open access, Turkish 3 and 1.3-ish. Of how many entries and how many citations for those languages? They state that “While the English Wikipedia references ~32,000 articles from top journals, the Slovak Wikipedia references only 108 and Volapuk references 0.”. But Volapuk still ends up with an open access odd ratio of 0.588 and an ln(impact factor) of 2.330 (Appendix A3), which is counted only with the set of top-rated journals only; how is that possible when there are no references to those top journals? The number of counted journal citations is not given for each language, so a ‘statistically significant’ may well actually be over a number that’s too low to do your statistics with. Waray-Waray is a very small dot, and reading from Fig 1, it’s probably not more than those 108 references in the Slovak entries.

All in all, there is some room for improvement on this paper, and, in any case, some toning down of the conclusions, let alone technologyreview’s sensationalist blog title.

fig8of1506.07608

Fig 8 from Teplitskiy et al (2015)

Ontology (information science) Wikipedia entry, some issues

Let me not be petty whining that none of my papers are in the references, but take a small example of the myriad of issues.

Take the statement “There are studies on generalized techniques for merging ontologies,[12] but this area of research is still largely theoretical.” Uh? The reference is to an obscure ‘dynamic ontology repair’ project pdf from the University of Edinburgh, retrieved in 2012. We merged DMOP’s domain content with DOLCE in 2011, with tool support (Protégé, to be precise). owl:import was around and working at that time as well. Not to mention the very large body of papers on ontology alignment, reference book by Shvaiko & Euzenat, and the Ontology Alignment Evaluation Initiative.

The list of ontology languages even includes SBVR and IDEF5 (not ontology languages), and, for good measure of scruffiness, a project (TOVE).

The obscure “Gellish” appears literally everywhere: it is an ontology, it is a language, it is an English dictionary (yes, the latter apparently also falls under ‘examples’ of ontologies. not), and it is even the one and only instantiation of a “hybrid ontology” combining a domain and an upper ontology. Yeah, right. Looking it up, Gellish is van Rensen’s PhD thesis of 2005 that has an underwhelming 2 citations according to Google Scholar (10 for the related journal paper), and there’s a follow-up 2nd edition of 2014 by the same author, published with lulu, no citations. That does not belong to an introductory overview of ontologies in computing. Dublin core as an example of an ontology? No (but it is a useful artefact for metadata annotations).

Under “criticisms”: aside from a Werner Ceusters statement from a commentary on someone from his website—since when deserves that to be upgraded to Wikipedia content?!?—there’s also “It’s also not clear how ontology fits with Schema on Read (NoSQL) databases.”. Ontologies with NoSQL? sigh.

“Further readings” would, I expect, have a fine set of core readings to get a more comprehensive overview of the field. While some relevant ones are there (e.g., the “what is an ontology?” paper by Oberle, Guarino, and Staab; “Ontology (Science)” by Smith, Gruber’s paper despite the flawed definition), numerous ones are the result of some authors’ self-promotion, like the one on bootstrapping biomedical ontologies, an ontology for user profiles, IE for disease intelligence—they’re not even close to ‘staple food’ for ontologies—and the 2001 OIL paper and Ontology Development 101 technical report are woefully out-dated. The “References” section is a mishmash of webpages, slides, and a few scientific papers most of which are not from mainstream ontology research venues.

And that’s just a sampling of the issues with the “Ontology (information science)” Wikipedia entry; the ontology engineering entry is worse. No wonder my students—having grown up with treating Wikipedia as gospel—get confused.

 

Ontologies entries in other languages

That much about the English language version of ‘ontology (information science)’. I happen to speak a few other languages as well, so I also checked most of those for their ‘ontology (information science)’ entry. For future reference as a stock-taking of today’s contents, I’ve pdf-printed them all (zipped). For starters, they all had ontologies at least categorised properly into ‘informatica’. +1.

The entry in Dutch is very short; one can quibble and nit-pick about term usage, and it is disappointing that there’s only one reference (in Dutch, so wouldn’t count in the arxiv analysis), but at least it’s not riddled with mistakes and inappropriate content.

The German one is quite elaborate, and starts off reasonably well, but has some mistakes. Among others, the typical novice pitfall of confusing classes for instances [“Stadt als Instanz des Begriffs topologisches Element der Klasse Punkte”] and the sample ontology—which of itself is a good idea to add to an overview page—has lots of modelling issues, such as datatypes and mixing subclasses with properties (the Maler [painter] with region of origin Flämish [Flemish]). Interestingly, ontology types for the English reader are foundational, domain, and hybrid, whereas the German reader has only lightweight and heavyweight ones. As for the references, there are some oddball ones, but the fair/good ones are in the majority, if incomplete, and perhaps a bit lopsided to Barry Smith material.

The Italian entry is of similar length as the German entry, but, unfortunately, has some copy-and-paste from the English one when it comes to the list of languages and examples, so, a propagation of issues; the ‘example of applications’ does list another project, and there is no ‘criticisms’ section. The text has been written separately instead of being a translation-of-English (idem ditto for the other entries, btw), and thus also consists of some other information. For starters, removing most of the ‘Premesse’ would be helpful (or elaborating on it in a criticism section; starting the topic with information warfare and terrorism? nah). The section after that (‘uso come glossario di base’) is chaotic, reading like a competitor-author per paragraph, and riddled with problematic statements like that all computer programs are based on foundational ontologies (“Tutti i programmi per computer si basano su ontologie fondazionali,”), and that the scope of an ontology is to develop a database (“Lo scopo di un’ontologia computazionale […] [è] di creare una base di dati”). It does mention OntoClean. Italian readers will also be treated on a brief discussion of the debate on one or multiple ontologies (absent from the other entries). It has a quite different set of ‘external links’ compared to the other entries, and there are hardly any references. Al in all, one leaves with a quite distinct impression of ontologies after reading the Italian one cf the Dutch, German, and English ones.

Last, the Spanish entry is about as short as the Dutch one. There’s overlap in content with the Italian entry in the sense of near-literal translation (on the foundational ontology and that Murray-Rust guy on the ‘semantic and ontological war’ due to ‘competition between standards’), and it has a plug for MathWorld (?!).

So, if the entries on topics I’m an expert in are such of such dubious quality (the German entry is, relatively, the best), then what does that imply for the other entries that superficially may seem potentially useful introductory overviews? By the same token, they probably are not. And the ontology topics are not even in an area with as much contention as topics in political sciences, history, etc. Go figure.

 

Now what?

Is this a bad thing? I already can see a response in the making along the line of “well, it’s crowdsourced and everyone can contribute, we invite you to not just complain, but instead improve the entry; really, you’re welcome to do so”. Maybe I will. But first, two other questions have to be answered. The arxiv paper that got my rant started claimed that open source papers are good, and that they’re reworked in interested-layperson digestible bites in Wikipedia to spread and diffuse knowledge in the world. The idea is nice, but the reality is different. Pretty much all the main papers on ontologies are freely available online even if not published ‘open access’ (computer science praxis, thank you), yet, they are not the ones that appear in Wikipedia. Question 1: Why are those—freely available—main references of ontologies not referenced there already?

A concern of a different type is that several schools in South Africa have petitioned to get free Internet access to search Wikipedia as a source of information for their studies. Their main argument was that books don’t arrive, or arrive late, and there is no library in many schools, which is a common problem. They got the zero-rate Wikipedia from MTN; more info here. (I’ll let you mull over its effects on the quality of education they get from that.) Question 2: Can Wikipedia be made a really authoritative resource with the current set-up so as to live up to what the learners [and interested laypersons] need? If I were to rewrite an update to the Wikipedia pages today, a pesky editor or someone else simply can click to roll it back to the previous version, or slowly but steadily have funny references seeping back in and sentences cut and rephrased. Writing free textbooks, or at least extensive lecture notes, seems a better option, or a ‘synthesis lectures’ booklet endorsed by lots of people researching and using ontologies. What about a ‘this version is endorsed by …’ button for Wikipedia entries?

Any better ideas, or answers to those questions, perhaps? Free diffusion of digested high quality scientific knowledge really does sound very appealing…

References

[1] Teplitskiy, M., Lu, G., Duede, E. Amplifying the Impact of Open Access: Wikipedia and the Diffusion of Science. arxiv.org/abs/1506.07608

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