A Red&Blue approach to Wikipedia references.

Elisabeth Bik is according to her Wikipedia article a "scientific integrity consultant". Her work is often to the detriment of the reputation of scientists and the work they do. Many of the scientists have a Wikipedia article and retracted publications serve as references in Wikipedia articles.

Many more publications are retracted, most if not all are registered at Retraction Watch. It is reasonable to expect that many publications serving as references in a Wikipedia are retracted. Arguments used to achieve a Neutral Point of View based on a retracted publications, are wrong by definition. 

When all references of a Wikipedia are registered in a Red&Blue Wikibase and, when all books with an ISBN and scientific publications with a DOI are ALSO known at Wikidata, it becomes possible to offer a new service. A service providing information about retractions and citations to the publications used as a reference.

Such a service is to be interactive as well.. Just consider: a Wikipedian wants to check the quality of a Wikipedia article. An update button, first checks for retractions and for all citing publications. It then checks for missing data like citations and authors. At the same time new references are added; they are  all processed in the same way.

In the background, all publications will be checked by a batch functionality for updates at Wikidata. Particularly for new retractions, authors who claim a publication.. In this way the information on any topic will be as good as we can make it.

• scientific publications are retracted and these retractions impact our NPOV
• publications may be used as a reference in multiple Wikipedias
• keeping information on sources up to date protects our NPOV
• making the latest references available to all our Wikipedians ensures an optimal result

So what is not to like? 

Thanks, 

        GerardM

Another Red&Blue application; the epidemiologist who wrote the book on "Smoking Kills"

Professor Richard Doll of Oxford is considered one of the best epidemiologists of the 20th century. There are 20 Wikipedias who consider him notable enough for an article yet Wikidata had until now no scientific paper associated with him. That was easily solved by disambiguating "author strings" for Mr Doll. 

With currently 54 publications to his name, none of his books are included. At the Open Library, Mr Doll is known five times and several books were known by these different Mr Dolls. All books have now been attributed to the Mr Doll with id OL1150080A. This identifier is now linked on Wikidata and reading the available books can be read by an international public.

All publications known at Wikidata for Mr Doll are represented in his Scholia. Given that there is much more to explore, this representation will evolve over time. People may add books or publications and additional co-authors may be disambiguated (currently a potential of 159 authors). 

The English Wikipedia has a Scholia template and it is implemented on the Richard Doll article. Functionality like this makes all the effort worth it bringing information to a next level of exposure. It works both ways. Suppose that all references of all Wikipedia articles in any Wikipedia are to be found in Wikidata. All of these references will be known in the Red&Blue Wikibase. All references with an identifier like a DOI or an ISBN can easily be integrated in Wikidata for re-use in other Wiki projects. 

With some additional work, it is even possible to associate references to individual statements and have them known in Wikidata as well. Again this promotes exposure of all the work we do and it promotes re-use in other Wiki projects.

• Scholia is/could be available as a template on any and all Wikipedias
• You can read books when available at OpenLibrary
• Anyone can contribute to the tapestry of information for any scholar
• References can easily be added in Red&Blue Wikibase
• These references can be linked to Wikidata making for one stop shopping for updates

So what is not to like? 

Thanks, 

       GerardM

A Red&Blue Wikibase disambiguation on the English Wikipedia

Mark Edward Hay is an American marine ecologist. There is a Wikipedia article about him in two languages and there is an article in Wikispecies. Consequently there is an item in Wikidata.

In a template it says: "[[Lowell Thomas Award]] (2015)". The link it a redirect to [[Lowell Thomas]] the man the award is named after. This is accepted practice in Wikipedia and it is not a problem. The redirect page has 23 links to articles mostly of people who received the same award.

With a Red&Blue Wikibase for the English Wikipedia, it will be possible to associate a relation with the award. This could fit in a template and additional red links can be added based on the source. 

When a Wikipedia adds new links, it is done by typing in the name of an potential article. Given that people who received an award are notable, consequently new blue links are highly likely to occur. New red links are entered in a template so there is this implied relation. 

At Wikidata an item for the Lowell Thomas award was recently added because of Mr Hay. It currently only refers to one recipient; Mr Hay. The 23 relations known at the en:red&blue are more than welcome to be added to Wikidata. Red links are more tricky as Wikidata is a superset of data of all the Wikipedias  articles of all Wikipedia and then some. 

So when Wikidata already knows about a recipient, it can make a red Wikibase link blue. When any Wikipedia adds the Lowell Thomas Award as a link, all the information can be populated from Wikidata making it much easier to have sanity checks indicating where data may be right or wrong..

• Hidden data in redirection articles are given an additional use
• Data available in multiple Wikipedias is actually shared making knowledge more complete
• Data only available in one Wikipedia becomes more generally available

So what is not to like?

Thanks,

      GerardM

A Red&Blue Wikibase for the red, blue and black wikilinks of each @Wikipedia

Wikipedia uses blue links to maneuver between its articles. When there is no article it is called a "red link". This text based functionality works reasonably well but it has important limitations.

• article names are constructs that makes them unique
• disambiguation pages need to be maintained
• there are false positives linking to the wrong articles

When you know your Wikipedia history well, one of the most effective innovations was to remove the interwiki links from the Wikipedias and replace them with links to Wikidata. Wikidata makes use of identifiers and as a consequence the change of an article name has no effect, this ensures that articles on the same subject remain properly linked.

The Wikidata project uses the Wikibase software and this enables the "federation" of multiple databases. This means that data may exist in multiple databases but it all work together. 

Suppose that you replace both the blue links and the red links in a Wikipedia with identifiers of a separate Wikibase. Almost all blue links will implicitly be linked to a Wikidata item and Wikidata already knows about the relations between blue links it has items for. Consequently a Wikipedia Red&Blue Wikibase will be richly populated from the start.

Every Wikipedia remains autonomous and we keep it that way. But we DO know more at Wikidata because it is a superset of all Wikipedias. So when a Wikipedia knows about an award, so does Wikidata. When Wikidata knows about more recipients, it is suggested to include them as red links. It must be a suggestion because a Wikipedia may have another script, another naming convention for names and this has to be correct before it becomes available as text in the Wikipedia proper. 

When a label is correct for a Wikipedia, it is obvious that there is to be a link to the item AND that the label can be used for that language as well. With 200+ Wikipedias enriching Wikidata in this way, both the multilingual and the multicultural quality & quantity of Wikidata will sky rocket.

• Wikipedias remain autonomous in their content
• Wikidata will progress from a technically multi lingual project to a functional multi lingual project
• Disambiguation will be technically available for all accepted Red&Blue labels
• Known relations with a reference will be available with a reference to every Wikipedia.

So what is not to like?

Thanks,  GerardM

Be both Anthony G. and Αντώνης Γ. Καφάτος as a scientist and have an ORCiD identifier

Anthony G. Kafatos is a co-author on many papers that are part of the "Seven Countries Study". When you want to know about the many papers he was involved in, it helps when they are all linked. The papers known at Wikidata are linked to his item. When papers are still known as a string, an "author name string", they are hard to spot AND they may be spelled differently AND even be in a different script.

Anthony was also spelled as Antony.. Both work in the same department at the same University making it safe to consider them the same. Someone has to decide, this time it was me. That is not great because what do I know. One alternative is that nothing gets decided but it is much better when scientists themselves are involved.

Data is an ecosystem. Best is when any and all scientists have one ORCiD identifier and authorise the institutions they trust to update their profile with their latest and greatest work. This has profound implications. This data will now be available for many applications including Wikidata. It will become easier to understand what the neutral point of view on a subject is.

This is the Scholia for Mr Kafatos. At this time there are 18 links to papers on the "Seven Nations Study", four more than for Mr Ancel Keys the architect of the study. 

Thanks, GerardM

Food for thought; statistics and Wikidata - DONT BE A KARELIAN

The lumberjacks in Karelia Finland got all the physical activity you can expect for lumberjacks, they looked the part and they died in droves before their fifties. This was as well known in the world of health scientists as well as the fact that in Japan people had the least problems with heart failure. Epidemiologists started one of the most famous studies, the "Seven Countries Study" to learn about these phenomenon. The Karelians ate a lot of meat and butter, this caused arthrosclerosis and it was identified as the cause of all these early demises. 

The Finish government wanted this to change, the lumberjacks loved their meat but their wives loved their hubbies more and they started them on a different diet. The government did a double blind research project and the fine Karelian gentlemen started to outperform their fellow Fins... As a consequence the Finnish government promoted healthy food to all Fins.

In Wikidata we have MANY scientific publications with "Seven Countries Study" in the name of the publications. With more than 100 such publications tagged, many authors, publications and subjects have become apparent. This can be seen in the Scholia for the Seven Countries Study. Statistically it is likely that when another 100 publications are added, the patterns found may slightly differ. Additional authors may be represented but the relative weight of existing authors is likely to remain the same. 

Ancel Keys is the architect of the Seven Countries Study, he authored both papers and books with many publications and publishers and he collaborated with many of the most prominent scientists in his time. The results of all these published studies are profound and not only for the Karelian lumberjacks. Not everybody is happy with the results. Influencers have us believe that Mr Keys misrepresented the facts of the study. However, when you look at the co-author graph, Mr Keys is not really central to all the collaborations. It is also obvious that there were many different publishers involved. 

The meat of the matter is obvious. Don't be a Karelian of centuries past, be smart, be there for your nearest and dearest and understand that a traditional Japanese diet or the Mediterranean diet gives you more mileage. The Seven Countries Study had a run for over fifty years, it knows about what people ate and the mortality that is the consequence of their diet. You can ignore this at your own peril :)

Thanks, GerardM

A #Netflix documentary, #Youtube reviews and a more #NPOV @Wikidata reaction

I really enjoyed watching "You are what you eat", a Netflix four part documentary based on research of the differences found between a vegan and an omnivorous diet in identical twins. The results of this research can be found in a paper called "Cardiometabolic Effects of Omnivorous vs Vegan Diets in Identical Twins". 

The documentary has several story lines, one is about the research itself, another informs about participants in the study and finally we are informed about the industry that produces our food. The chosen participants are a vehicle for the story, there were chefs, athletes cheese aficionados and people from other cultures (seen from an US-American perspective). What people eat is produced so we are informed about the food industry. The picture painted is not pretty but based in facts.

On YouTube there are several "reviews" and now some reviews as well. All of the "reviews" are really disappointing because they express expectations that are not realistic. The program is NOT about only the science and it is NOT giving equal weight to the production of fish or meat. The results of the research are favorable to a vegan diet and the documentary provides information on what is available when less or no meat is eaten. It is why we learn about the quality of vegan cheese and meat products. Great cheeses and a biltong that is not meat based are explored by participants of the study. 

I found the YouTube "reviews" disappointing because they came across as hatchet jobs. When they consider the documentary biased, it finds its basis in the bias of the reviewer and not necessarily on the results of the research. When it is said that these reviews were requested by "so many people", it feels like that people in the agro business exposed their hand. 

Wikipedia has the article on the documentary and it has an article on the principal author of the paper. They have an appropriate neutral point of view.

My Wikidata reaction is that I added the paper to Wikidata, I added many of its authors and many of the papers cited as references and to be brutally honest, seen from within Wikidata it looks awful, it is one dimensional, it is unusable. However thanks to tools the full impact of available information becomes available. Scholia is my preferred tools for science. This is the Scholia for the paper.

Thanks,

      GerardM