The fallibility of notability

When Wikidata will be split up in a "science" part and "all the rest", scientists who have a Wikipedia article will need to be part of the "rest" as well. This is necessary as all Wikipedia articles have a link to Wikidata because of the "interwiki" mechanism.

It follows that there will be an over abundance of USA scientists and there will  hardly be any scientists of Africa or South America. 

Some data about scientists is likely to be considered to be part of "all the rest" awards for instance. Are these scientists who received an award to be known in two data sets? Some scientists had a career as an athlete.. an other reason for duplication. It is hard enough to maintain the interwiki links and existing duplication within Wikidata, it will become exponentially more difficult when another data set is added.

When the creation of Wikimedia Commons was considered, similar good reasons led to hesitation and prevented us to bite the bullet for quite some time. Commons started with the creation of a Wiki, a MediaWiki patch that showed a picture in a Wikipedia and it then took a long time for most of the duplicate pictures to be only in Commons. It was not technically perfect but it was done perfect in the wiki way.

I hope that we will bite the bullet this time as well. With a new unrestricted wikibase, the old batch jobs can be dusted off and make good for the years of academic data we missed. I pray that Scholia will become functional soon after. 

I will still be able to do my Wikidata thing.. projects like African politicians, Muslim countries and their rulers (past and present).. Awards that can do with an update obviously including science awards.. I will not be bored but maybe I will be working .. maybe not.

Thanks,

       GerardM

Old soldiers never die, they march in the remembrance parades

As our movement matures, people who were there at the beginning, age. They get other priorities, they get sick, operated upon and as a consequence have a windfall of time to do more work at Wikidata. 

I did a similar job for a dear fellow Wikimedian.. It is now my turn, my chirurg is in this picture and as I add missing co-authors this picture becomes more complex. It will also become more complex when existing co-authors are enriched with new and linked papers.

With Wikipedia there is the promise that even though the information will evolve, all the work people have put in will be there in future and enable people to read/study the subjects each editor cared for.

The data of Wikidata as it is will be split in parts. For the best of reasons but once its structure is broken, the tools that bring structure to the data will be broken as well. The same tools that enable the enrichment of the data will be broken. Much of my Wikimedia legacy will be lost because there will no longer be a public enabled to learn about scholarly works in a Wiki way.

For a few years now this sword of Damocles has hung over Wikidata. As a consequence the potential of Wikidata is not being realised. The data could be so much richer when automated processes bring free knowledge together. References in Wikipedia  indicating later papers and improve its quality. 

As long as I can I will do my Wikidata thing; hope is eternal.

Thanks,

       GerardM

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

A Scholia for "water fluoridation"

Some topics are poisonous. People have a set point of view; hell or high water they will budge from their position. Even Wikipedia with its "neutral point of view" makes no dent in their preoccupation. So why argue?

Wikipedia is known for its references to sources and Wikidata is great at connecting these sources together. Particularly scholarly papers with a "DOI" may link to authors, cites works and works citing a paper. When a paper is of particular interest, you can expand the information in all these ways.

So I did not get into an argument about "water fluoridation", I included papers mentioned to Wikidata. I linked some papers with "water fluoridation" in its title to the subject. I attributed papers to authors including one by the Surgeon General of the United States..

Everything that was done on the subject is reflected in the Scholia for the subject. It suffices for me as my participation in an endless argument.

Thanks, GerardM 

Covid enquette in the Netherlands ..

 

Dutch politicians will have their day in an "enquette commissie" coming up with their version of what there is to learn from the COVID-19 pandemic. The result will probably mirror the composition of the mainly right wing commission. It is not as if we do not know what there was to learn; a recent research paper commissioned and paid for by the Dutch government lays out the effects of vaccination on mortality in the Netherlands. It does even refer to a study on religion and vaccination coverage in the Netherlands.

Given the composition of the committee, they will have a hard time convincing people of their outcome. Nobody is really interested in my opinion, but I do believe in proper science. Given the qualification of the people writing the commissioned paper, I added the paper to Wikidata, author strings were replaced by author identifiers, known publications were linked to the authors, I linked the cited papers and ensured that the primary author is known to Wikidata as well. The result is that anyone can find this enriched information in its Scholia.

Given that some Dutch politicians express that they not understand the scholarly process, the best I can do is open up information that has a scholarly foundation, particularly in a field where I do trust politicians to come up with a report that reflects their political bias.

Thanks,

      GerardM

For Dr @ashadevos there are 14 @Wikipedia articles

 

Hardly a "woman in red", Dr De Vos has many accomplishments chronicled in these Wikipedia articles. She presents herself with her colleagues on Facebook and, the graph of her co-authors should paint a similar picture, initially it did not. At first there were only a few publications to her name, they have been expanded to 26 at present. It introduced many co-authors and there are now some 112 co-authors missing.

Obviously, there is much more that could be done. Adding more papers and co-authors adds complexity to the Scholia of Dr de Vos. More distinctions could be added, talks at conferences and papers that were cited. I typically restrict myself to papers with a DOI and authors with an ORCiD identifier as they have the biggest network effect. 

I was reminded by Greenpeace that some people give themselves nothing for their birthday. So I updated this Wikidata item. Who will notice or care.. Like Greenpeace, Dr De Vos cares about whales; it is her specialty.

Thanks,

     GerardM

Gender balance at @Wikipedia, deletion; a rear guard action.

 A recent Wikipedia Research article aims to prove that the English Wikipedia deletion process is not biased. For some that is a loaded question because it  centers on the question if Wikipedia is equitable.

As so often the article is all about English Wikipedia and it has its own bias. English Wikipedia does not serve half the public of the Wikimedia Foundation and much of the other half does not read English. The gender balance in English Wikipedia is however improving; the percentage of articles about women is slowly but surely increasing.

At issue in the article is whether the English Wikipedia deletion policies effectively harm gender and race biases. Obviously there are more biases; you may be male and white but when you are not from an Anglo-american background chances for Wikipedia recognition are slim. When you care to research this, check out Wikidata, it includes a super set of what Wikipedia includes and it is biased in this way as well.

When a Wikipedia article about a scientist is deleted, it does not follow that its Wikidata item is deleted and given enough identifiers, it is likely that its related subset increases over time tilting the "notability" balance. Even so, many important scientists are "scientists in red", an example is Prof Emily Fairfax her prominence is for instance in her explaining and demonstrating that beavers feature prominently in the fight against forest fires. 

When English Wikipedia defends its own policies, it follows that they rely on the base assumptions in those policies. When those assumption are questioned, their arguments are lost. Given that English Wikipedia represents a subset of "the sum of all knowledge" that is included in Wikidata, it follows that much of Wikipedia can be understood from such a perspective. 

Wikidata has no "red links"; when a relation exists for an recipient of an award, there must be an item for both the award and the recipient. Wikipedia has one link in black to the "SIRS Lifetime Achievement Award". while Wikidata has a link to all recipients. They are linked to identified publications and other awards and consequently the Scholia for the award is really informative. 

Based on information like this improved information is available that must wait for a Wikipedia volunteer. English Wikipedia is a victim of its success, it cannot fully maintain its information. The same can be said for Wikidata. It is however a superset and it does not necessarily require a mastery of English.

With new technologies becoming more relevant, there is an avenue to improve the quality of any Wikipedia, inform people based on the data in Wikidata and improve on the quality of the information that we provide. 

Thanks,

     GerardM

Analysis of a Wikipedia article

For professor Gerhard Gries there is a Wikipedia article and as a consequence there was a Wikidata item. Actually there were two; they have been merged. Many articles have been attributed to professor Gries and a Scholia template was added to the article.

Professor Gries has his own lab: the "Gerhard and Regine Gries Lab". There is no article for his wife and, there was no red link. There was no Wikidata item for his wife but there were 59 links indicating her as a missing co-author. She has now 68 articles linked to her as an author or co-author. Regine Gries is now a "woman in red".

The article states in two places that he is a "Fellow of the Entomological Society of America" (2019). It is in the text and it is in a Wikipedia category. Relevant are two additional lists; the website of the Entomological Society of America and the result of a query at Wikidata (shown in a Scholia). All these lists are incomplete, the fellows of 2022 are not yet included on the SoA website; they can be found in a different place. The Scholia has been added to the category article on the English Wikipedia; in effect you will find several "fellows in red". 

Three additional awards are listed, awards that have no category on the article. One is for the "Fellow of the Entomological Society of Canada", its reference may be found here. Another one is for the Nan-Yao Su Award and finally the Gold Medal of the Entomological Society of Canada had to be added to Wikidata. There are always more "award winners in red" to be found or to be added.

Every list, every category in Wikipedia is likely to be incomplete. What we do not know may be relevant. With data on missing articles available in Wikidata, there are more more options to make Wikipedia more inclusive.

Thanks,

       GerardM

he, she, they/them

One ambition at Wikipedia is to have more articles about women.  The Women in Red project does really well, slowly but surely the balance between articles about males and females is improving. How do we know this: in Wikidata we have a database we can query and it shows over time.

Obviously, both many deserving men and women could get an article in future and particularly many scientists are already known in Wikidata through their publications. So how do we know the gender of these scientists? Because of a name like Emma or Janice it is likely a woman.. Not a precise method particularly for those people who identify themselves in a different way. Google scholar or Twitter often shows a picture and that is not fool proof either. 

The dilemma is in two ways: manual entries are open to errors in the first place. A six percent error rate is to be expected in any edit and anyone is kindly requested to fix what should be improved; Wikidata is rich in alternatives for male/female identifiers. The alternative is that we do not add a likely gender. This results in no awareness of the composition of the co-authors of an author. No awareness of the volume and balance of people who do not have an article yet.

I think that a male author with only male co-authors is problematic in and of itself. Quite often it is just that no attention was given to female co-authors so I often remedy this by giving attention to them. I add them to Wikidata, look for an ORCiD identifier, a Twitter handle a Google scholar profile. The effect is not only apparent for the male author, but it has an effect on all the co-authors for the newly registered author.

The issue I have is, I see no solution for the dilemma of a gender balance in Wikidata. What I do know is that Wikidata is a collaborative project and anyone is kindly requested to make it as good as it can be.

Thanks, GerardM

@WDScholia, proficiat Prof @DrSarahNull

 On Twitter it was announced that Sarah E. Null will be a professor at USU Watershed Sciences. Hydrology will prove to be a subject of even more importance. This subject has my interest so I checked out her entry in Wikidata.

Identifiers are really important, so I added her Twitter handle and her Google Scholar ID. Her Scholia showed what papers were known and I clicked "improve data" to disambiguate additional publications and link them to her Wikidata entry.

Google Scholar provides information of her publications and I added one paper to Wikidata; "Prolonged and Severe Drought in the Most Dammed Tributaries of the Lower Mekong Basin". It has 8 authors and only four have an ORCiD identifier, three did not have a Wikidata entry. Now they do and their ORCiD identifier makes them unique.

Typically I add several publications when I concentrate on a person. When I stop, I often revisit the "improve data" part of a Scholia to add missing co-authors. Of particular interest are the ones who are missing the most. They have the biggest impact on the "Co-author graph", making it more complex. Jay R. Lund is missing as a co-author ans so is J. R. Lund. Wikidata knew a "Jay Lund" and a "Jay R. Lund", they have been merged and I was then possible to attribute the missing publications for Jay R. Lund. After all this, Prof Null is no longer the only known author on seven papers. :) A bit diapointing so I added one other co-author for now; Marcelo A. Olivares. Others will creep in as more work is done in the future. 

Thanks,

       GerardM

An hydrology professor was killed in a shooting

I learned of Prof Meixner because of an outpouring of grief on Twitter by many people I knew of because of my hobby. I include papers and authors related to hydrology and related topics to Wikidata. As they expressed their loss, I started adding papers for Prof Meixner. The result is an evolving Scholia for him and his co-authors.

I have also done some work on some of the people I noticed on Twitter. Their Scholia has been expanded as a result. When they collaborated on research with Prof Meixner, they may pop up in his co-author graph.

Recently I had a tshirt printed with a design from a paper. When people suggest a picture that goes with a DOI and explain why it illustrated one of his papers, I will include the text on my blog. When there are more than one, the one Twitter likes best will get a tshirt.

It is horrible only to learn about someone when he dies like this. Apparantly this is how I deal with it.

Thanks,

       GerardM

Diversity for WMF is in its fundraising and in its results

Diversity is a stated objective and the Wikimedia Foundation does a comparatively good job.. except that it could be so much better.

It is known that (read Gapminder) genuinely rich people live in every country. The Wikimedia Foundation as a rule does not target the truly rich and consequently the average donation is low. It makes us independent of the vagaries of the opinions of the really rich. As Wikimedia becomes a truly global organisation, it should raise funds everywhere and report what WMF does locally. 

As we report on what we do locally, it follows that we have an interest for any locality. As local children do use Commons we ask people to upload pictures of a local policeman, firefighter, nurse, police car ambulance etc for them to use. As students read in their own language we easily offer e-books using the hub best suited for the purpose. When as a response we are asked to provide services, we prioritise the local service and we will internationalise and localise to get the most out of our investments.

As we become more global and diverse, the percentage of what the provision of our services will represent more and more the global distribution of people. It will grow our community, it will grow our audience and we will evolve away from an organisation managed from "the center of the world".

Plenty of challenges ahead but not so much the amount of money the highest earners in the WMF get paid. At that I do not give a fuck as long as the job gets done and, so should you.

Thanks,

        GerardM

Hierarchies of scientists from a personal @Wikidata/@Wikipedia point of view

 

As a hobby I add publications and scholars to Wikidata. I am particularly interested in hydrology, biodiversity and climate change. When I come across scientists, I look them up on Wikidata, I care most about scientists with an ORCiD identifier, I often add Google scholar and Twitter identifiers as well. ]

As there have been many, many papers and scholars for a long time, the impact I have is particularly in scientists new to Wikidata and attributing papers to them. This results in an improved representation that can be seen in their Scholia. When there is a Wikipedia article for a scientist, a template for the Scholia can be added; it will always show the most up to date information.

The way it works out is that I am a "browser", I read Twitter feeds by a scholar, find a publication they enthuse about and I may already be on a tangent adding the papers and scholars. In my job I do not have time to read and comprehend but I have time to mechanically add more papers. I read in the morning, make a pick for the day and I "search" using the Scholia search function with a DOI as the argument. When a paper does not exist I am presented with the option to add it to Wikidata. When its authors can be found because of their ORCiD identifier, they are linked from the start to their Wikidata item.

My personal hierarchy

• I find a paper, a scholar on Twitter
• They publish on a subject I am interested in
• When they are already known to Wikidata, they are linked to the publication I search for
• When search indicates that an ORCiD identifier exists, I search Wikidata and add a scholar or add an identifier.
• When Twitter indicates Twitter handles, I add them
• When I cannot guess the gender, I look at Google scholar for a picture, I add the identifier as well.
• When a scholar is picked for the day, I add the latest pictures first because they include more ORCiD identifiers for co-authors.

A Wikidata/Wikipedia hierarchy

• Most valuable are scholars with a Wikipedia article that includes a Scolia template
• Scholars with a Wikipedia article
• Scholars with a Wikidata item with many identifiers including an ORCiD identifier.
• Scholars with only an ORCiD identifier
• Scholars with no identifiers
• Scholars only known because of an "Author string"

When I come across an Australian scientists who was rewarded with an award, who has a Twitter account, an ORCiD and a Google Scholar identifier but no Wikidata item, it is someone I will add. So a warm welcome to Heather Neilly. She is of interest to me because of her work as an ecological consultant and in natural resource management for local government. Her latest work is on vegetation change in sheep-grazed chenopod shrublands in South Australia.

Thanks,

       GerardM

Sabina Nowak a Polish scientist, an expert on European wolves

Dr Nowak has a Wikipedia article in several languages. Her notability is obvious because wolves is a very hot topic in many European countries. When people have opinions about wolves, it is obvious that in a European context you cannot dismiss the research of Dr Nowak over the years. 

When the notability and the quality of a Wikipedia article is assessed, it is obvious that an encyclopedic article is not best served with a list of papers Dr Nowak contributed to; the Scholia template provides more in depth information. However, Scholia only functions when the papers are known and attributed.

In Wikidata, there were two items that needed to be merged. Three papers were linked, an additional nine could be attributed. Additional identifiers were added, of particular significance is Google Scholar as it knows many if not most of the papers of a scientist. 

Adding missing papers is easy; you search with a DOI for the paper and when Wikidata does not know it, it is suggested to add it using the quickstatements tool. The best bit is that when CrosRef knows the ORCiD identifier for an author, it will either identify the author or will add the ORCiD identifier as a qualifier. 

Adding the Scholia template to any Wikipedia article about published scholars makes sense; the data is a "work in progress". It changes as more papers and co-authors become known. It is also an invitation to our communities and scientists to improve both the Wikipedia article and the data represented in the Scholias for any scientist.

Thanks, GerardM