@Wikipedia: #notability versus #relevance

I had a good discussion with imho a deletionist Wikipedia admin. For me the biggest take away was how notability is in the way of relevance.

With statements made like: "There are only two options, one is that the same standards apply, and the other is the perpetuation of prejudice" and "I view our decisions of notability as primarily subjective--decisions based on individual values and understandings of what WP should be like" no/little room is given for contrary points of view.

Notability has as its problem that it enables such a personal POV while relevance is about what others want to read. For a professor Bart O. Roep there is no article. Given two relevant diabetes related awards he should be notable and as he started a human study for a vaccine for diabetes type 1, he should be extremely relevant.

A personal POV ignoring the science that is in the news has its dangers. It is easy enough for Wikimedians to learn about scientific credentials, the papers are there to read but what we write is not for us but for our public. Withholding articles opens our public up to fake facts and fake science. An article about Mr Roep is therefore relevant and timely particularly because people die as they cannot afford their insulin. Articles about the best of what science has to bring about diabetes now is of extreme relevance.

At Wikidata, there is no notability issue. Given the relevance of diabetes all that is needed is to concentrate effort for a few days on a subject. New authors and papers are connected to what we already have, genders are added to authors (to document the gender ratio) and as a result more objective facts available for the subjective Wikipedia admins to consider, particularly when they accept tooling like Scholia to open up the available data.
Thanks,
      GerardM

#Wikidata - Exposing #Diabetes #Research

People die of diabetes when they cannot afford their insulin. There is not much that I can do about it but I can work in Wikidata on the scholars, the awards, the papers that are published that have to do with diabetes. The Wikidata tools that are important in this are: Reasonator, Scholia and SourceMD and the ORCiD, Google Scholar and VIAF websites prove themselves to be essential as well.

One way to stay focused is by concentrating on awards and, at this time it is the Minkowski Prize, it is conferred by the European Association for the Study of Diabetes. The list of award winners was already complete so I concentrated on their papers and co-authors. The first thing to do is to check if there is an ORCiD identifier and if that ORCiD identifier is already known in Wikidata, I found that it often is and merges of Wikidata items may follow. I then submit a SourceMD job to update that author and its co-authors.

The next (manual) step is about gender ratios. Scholia includes a graphic representation of co-authors and for all the "white" ones no gender has been entered. The process is as follows: when the gender is "obvious", it is just added. For an "Andrea" you look them up in Google and add what you think you see. When a name is given as "A. Winkowsky", you check ORCiD for a full name and iterate the process.

Once the SourceMD job is done, chances are that you have to start the gender process again because of new co-authors. Thomas Yates is a good example of a new co-author, already with a sizable amount of papers (95) to his name but not complete (417). Thomas is a "male".

What I achieve is an increasingly rich coverage of everything related to diabetes. The checks and balances ensure a high quality. And as more data is included in Wikidata, people who query will gain a better result.

What I personally do NOT do is add authors without an ORCiD identifier. It takes much more effort and chances of getting it wrong make it unattractive as well. In addition, I care for science but when people are not "Open" about their work I am quite happy for their colleagues to get the recognition they deserve.
Thanks,
      GerardM

Perspectives on #references, #citations

Wikipedia articles, scientific papers and some books have them: citations. Depending on your outlook, citations serve a different purpose. They exist to prove a point or to enable further reading. These differing purposes are not without friction.

In science, it makes sense to cite the original research establishing a fact. Important because when such a fact is retracted, the whole chain of citing papers may need to be reconsidered. In a Wikipedia article it is imho a bit different. For many people references are next level reading material and therefore a well written text expanding on the article is to be preferred, it helps bring things together.

When you consider the points made in a book to be important, like the (many) points made in Superior, the book by Angela Saini, you can expand the Wikidata item for the book by including its citations. It is one way to underline a point because those who seek such information will find a lot of additional reading and confirmation for the points made.

Adding citations in Wikidata often means that the sources and its authors are to be introduced. It takes some doing and by adding DOI, ORCiD, VIAF, and or Google Scholar data it is easy to make future connections. When you care to add citations to this book with me, this is my project page.
Thanks,
     GerardM

Be #Excellent - science in Europe / Holland - #wetenschapper2030

At the "Wetenschap 2030 / Evolutie of revolutie" conference in The Hague it was all about excellence. Confusion set in when the question was raised: what is excellence.

Two big Dutch science funding organisations invited young scientist to consider scientific practice in 2030. It was a great gathering, more than half of the public were women, one prominent speaker told them she had two children and we were reminded that a more diverse team is a more successful team as shown in a recent paper.

One of the introductions set the tone. In science itself there is no room for all of us. It would take exponential funding, funding that is not available. In a few panels the subject of the daily practice was discussed and indeed, it is cut throat. Many people do not share expertise, results; there is no common good, everything to win in a rat race to move up the ladder towards tenure. Some say these practices are on the way out, others indicate that it depends on the field you research.

And then there is this guy from Europe who says, only excellence will get you funding from the EU..

What helps; scientists that may indicate what their primary concern is to be, what they want to be evaluated on; education, research.. Counter intuitively, such focused reviews have the effect that results outside the track benefit as well. In this way it is the university itself who finds excellence and improves its processes.

Another perspective on excellence; what value does research offer. Not to the scholars, nor the universities but to the ones bearing the burden of the costs and expect results. Are these results truly the best that can be achieved, does it reflect cooperation, are the numbers reproducible and the papers readable. For Europe to fund; the proposal must have merit.

My take away message; all those scientists that do not collaborate, back stab and think it acceptable because that is the way it is done, they do not deserve my taxeuro going forward towards 2030. The good news; thanks to Open Science and everything related change is underway but we are not there yet. Important: it does not follow that getting funding is a sign of quality, there is too little money to go around for all proposals with merit.
Thanks,
       GerardM

#Scholia: on the "requirement" of completeness

Scholia, the presentation of scholarly information on authors, papers, universities, awards et al is at this time not included in the "Authority control" part of a Wikipedia article. The reason I understand is because Wikipedians "that matter" insist that its information is to be complete.

That is imho utter balderdash.

The first argument is the Wiki principle itself. Things do not need to be complete, in the Wiki world it is all about the work that is underway. The second is in the information that it provides: its information is arguably superior to what a Wikipedia article provides on the corpus of papers written by an author. The third is that with the prospect of all references of all Wikipedias ending up in Wikidata, value is added when a paper can be seen in relation to its authors and citations. It matters when it is known what citations a paper is said to support. It matters that we know the papers that are retracted. The fourth argument is in the  maths of it all; typically scientific papers have multiple authors. It takes only one author with an ORCiD identifier to get its papers included. The other authors have not been open about their work, it is their own doing why they are not known in the most read corpus on the planet. They still exist but as "author strings". When a kind soul wants to remove them from obscurity they can.

As to the "Katie Bouman"s among them? There are many fine people that are equally deserving, that have not been recognised yet for their relevance. Fine people that have a public ORCiD record. For them it is feasible to have their Scholia ready when they are recognised. For the others, well it is not a Pokemon game, it is a Wiki.
Thanks,
      GerardM

@Wikidata Women in science - Lesley Wyborn

For Lesley Wyborn a Wikipedia article exists. She "built an international reputation for innovative leadership in geoinformatics and global e-research, particularly in the geoscience area" according to the motivation for the "Outstanding Contributions in Geoinformatics" award. Notability, no issue.

When the article was written in 2016, no attention was given to the "authority control" and consequently in 2018 an additional item was created with an ORCID identifier. In 2019 additional work was done and the two items were merged. A Google Scholar identifier and the award was added potentially addressing the issues raised on the Wikipedia article.

Arguably both the Wikidata and the Wikipedia information could be more informative. However, given that both are Wikis that is quite acceptable. It is quite likely that many more papers are already on Wikidata and just need attribution. That is something for others to do.. we are a community remember.
Thanks,
     GerardM

How and when I trust science, when would you trust science?

When something drops on my head, it is gravity that brings it down. When I travel to the USA, the shortest route is over Iceland, the world is round. I did not get polio, measles or whooping cough, my parents had me vaccinated. I worked in computing, most of the women were better then the men, my observation, I am happy working for women.

When I read articles in Wikipedia, I know that I can trust it up to a certain level because there are citations indicating that something is true or that a given opinion is held. Its neutral point of view means that equal weight is to be given to opinions but not when it flies in the face of proven facts, the science about a subject. The best news; when scientific papers are retracted, we start to know about this and act upon it in Wikipedia. The nonsense, the preconceptions, the paid for science is to be removed once it is retracted.

In the Netherlands a prominent scientist has been tasked to root out those medical practices that are proven not to work. His work will be hard he will have to deal with vested interests, ingrained practices and a public that wants everything to be as expected. People will still be vaccinated, some medications will no longer be available, some treatments will not be there, they do not work even when you are desperate for them to work..

That is me, now you, when can you trust.. Well it is good to be wary, just consider the numbers. When a politician says he was effective because many drug dealers went to jail, ask yourself why should they be in jail, did your community end up safer? If not, not much was achieved. When scientific papers show the numbers of junks go down when substance dependence is treated as a medical and not as a criminal issue. Wonder what this meant for the communities these people come from. Seek out the numbers and you are no longer talking politics but considering the science of it.

A lot of so called science defends points of view that do not fit facts on the ground. This can be tricky/tough to understand because the difference may be local versus global. World wide, temperatures go up. Our climate is no longer stable and yes, in the USA it has been cold lately.. not so in Europe, Africa, Asia. One thing to consider, is it truly science, peer reviewed and everything or is it to shore up a point of view.. A tell tale is when it is from a "research institute" / "policy institute" paid for by an interested party.
Thanks,
      GerardM

Scopus is "off side"

At Wikidata we have all kinds of identifiers for all kinds of subjects. All of them aim to provide unique identifiers and the value of Wikidata is that it brings them together; allowing to combine the information of multiple sources about the same subject.

Scientists may have a Scopus identifier. In Wikidata Scopus is very much a second rate system because to learn what identifiers goes with what people requires jumping through proprietary hoops. Scopus is the pay wall, it has its own advertising budget and consequently it does not need the effort of me and volunteers like me to put the spotlight on the science it holds for ransom. When we come across Scopus identifiers we  include them but Scopus identifiers are second class citizens.

At Wikipedia we have been blind sighted by scientists who gained awards, became instant sensations because of their accomplishments. For me this is largely the effect of us not knowing who they are, their work. Thanks to ORCiD, we increasingly know about more and more scientists and their work. When we don't know of them, when their work is hidden from the real world, I don't mind. When we know about them and their work in Wikidata it is different. It is when we could/should know their notability.
Thanks,
      GerardM

The Bandwidth of Katie Bouman

First things first, yes, many people were involved in everything it took to make the picture of a black hole. However, the reason why it is justified that Katie Bouman is the face of this scientific novelty is because she developed the algorithms needed to distill the image from the data. To give you a clue about the magnitude of the problem she solved; the data was physically shipped on hard drives from multiple observatories. For big science, the Internet often cannot cope.

There are eternal arguments why people are notable in Wikipedia. For a lot of that knowledge a static environment like Wikipedia is not appropriate and this environment is causing a lot of those arguments. To come back to Katie, eh every scientist, their work is collaborative and much of it is condensed into "scientific papers". One of the black hole papers is "First M87 Event Horizon Telescope Results. I. The Shadow of the Supermassive Black Hole". There are many authors to this paper not only "Katherine L. Bouman". When a major event like a first picture of a black hole is added, it is understandable that a paper like this is at first attributed to a single author..

Wikimedia projects have to deal with the ramifications of science for many reasons. The most obvious one is that papers are used for citations. To do this properly, it is science who defines what is written and not selected papers to support an opinion. The public is invited to read these papers and the current Wikipedia narrative is in the single papers, single points of view. This makes some sense because the presentation is static. In Wikidata the papers on any given topic are continuously expanded, the same needs to be true for papers by any given author. Technically a Wikipedia could use Wikidata as the source for publications on a subject or by an author. The author could be Katie Bouman and proper presentations make it obvious that the pictures of a black hole were a group effort with Katie responsible for the algorithms.
Thanks,
       GerardM

@Wikidata is no relational #database

When you consider the functionality of Wikidata, it is important to appreciate it is not a relational database. As a consequence there is no implicit way to enforce restrictions. Emulating relational restrictions fail because it is not possible to check in real time what it is that is to be restricted.

An example: in a process new items are created when there is no item available with an external identifier. Query indicates that there is no item in existence and a new item is created. A few moments later the existence of an item with the same external identifier is checked using query. Because of the time lag that exists, what is known to be in the database and what actually is in the database differs and query indicates there is no item and a new but duplicate item is created.

Implications are important.

Wikidata is a wiki. The implications are quite different. In a wiki things need not be perfect, and the restrictions of a relational model are in essence recommendations only. In such a model duplicate items as described above are not a real problem, batch jobs may merge these items when they occur often enough. Processes may use arrays knowing the items it created earlier and thereby minimising the issue.

Important is that we do not blame people for what Wikidata is not and accept its limitations. Functionality like SourceMD enable what Wikidata may become; a link to all knowledge. Never mind if it is knowledge in Wikipedia articles, scholarly articles or in sources used to prove whatever point.
Thanks,
      GerardM

#Sharing in the Sum of all #Knowledge from a @Wikimedia perspective II

When we are to share in the "sum of all knowledge" we share what we know about subjects; articles, pictures, data. We may share what knowledge we have, what others have and that is what it takes  for us to share in the sum of all knowledge. The question is why should we share all this, how to go about it and finally how will it benefit our public and how will it help us share the sum of all knowledge.

At the moment we do not really know what people are looking for. One reason is that search engines like the ones by Google, Microsoft and DuckDuckGo recommend Wikipedia articles and as a consequence the search process is hidden from us. We do not know what people really are looking for. However, some people prefer the "Wikipedia search engine" in their browser. We can do better and present more interesting search results. From a statistical point of view, we do not need big numbers to gain significant results.

When we check what the "competition" does we find their results in many tabs; "the web" and "images" are the first two. The first is text based and offers whatever there is on the web. What we will bring is whatever we and organisations we partner with, have to offer. It will be centered on subjects and its associated factoids presented in any language.

One template to consider is how Scholia presents. It differs. It depends on whether it is a publication, a university, a scholar, a paper. Large numbers make specific presentations feasible and thanks to Wikidata we know what kind of presentation fits a particular subject. A similar approach is possible for sports, politics. It takes experimentation and that is what makes it a Wiki approach.

Thanks to this subject based approach, language plays a different role. Vital is that for finding the subjects potentially differing labels are available or become available. One important difference with the Google, Microsoft or DuckDuckGo approach is that as a Wiki, we can ask people to add labels and missing statements. This will make our subject based data better understood in the languages people support. Yes, we can ask people to have a Wikimedia profile and yes, we may ask people to support us where we think people looking for information have to overcome hurdles.
Thanks,
       GerardM

#Sharing in the Sum of all #Knowledge from a @Wikimedia perspective I

Sharing the sum of all knowledge is what we have always aimed for in our movement. In Commons we have realised a project that illustrates all Wikimedia projects and in Wikidata we have realised a project that links all Wikimedia projects and more.

When we tell the world about the most popular articles in Wikipedia, it is important to realise that we do not inform what the most popular subjects are. We could, but so far we don't. The most popular subjects is the sum of all traffic of all Wikipedia articles on the same subject. Providing this data is feasible; it is a "big data" question.

We do have accumulated data for the traffic of articles on all Wikipedias, we can link the articles to the Wikidata items. What follows is simple arithmetic. Powerful because it will show that English Wikipedia is less than fifty percent of all traffic. That will help make the existing bias for English Wikipedia and its subjects visible particularly because it will be possible to answer a question like: "What are the most popular subjects that do not have an article in English?" and compare those to popular diversity articles.

In Wikidata we know about the subjects of all Wikipedias but it too is very much a project based on English. That is a pity when Wikidata is to be the tool that helps us find what subjects people are looking for that are missing in a Wikipedia. For some there is an extension to the search functionality that helps finding information. It uses Wikidata and it supports automated descriptions.

Now consider that this tool is available on every Wikipedia. We would share more information.With some tinkering, we would know what is missing where. There are other opportunities; we could ask logged in users to help by adding labels for their language to improve Wikidata. When Wikidata does not include the missing information, we could ask them to add a Wikidata item and additional statements, a description to improve our search results.

This data approach is based on the result of a process; the negative results of our own Search and it is based on active cooperation of our users. At the same time, we accumulate negative results of search where there has been no interaction, link it to Wikidata labels and gain an understanding of the relevance of these missing articles. This fits in nicely with the marketing approach to "what it is that people want to read in a Wikipedia".
Thanks,
      GerardM

A #marketing approach to "what it is that people want to read in a @Wikipedia"

All the time people want to read articles in a Wikipedia, articles that are not there. For some Wikipedias that is obvious because there is so little and, based on what people read in other Wikipedias, recommendations have been made suggesting what would generate new readers.This has been the approach so far; a quite reasonable approach.

This approach does not consider cultural differences, it does not consider what is topical in a given "market". To find an answer to the question: what do people want to read, there are several strategies. One is what researchers do: they ask panels, write papers and once it is done there is a position to act upon. There are drawbacks; 

• you can only research so many Wikipedias
• for all the other Wikipedias there is no attention
• the composition of the panels is problematic particularly when they are self selecting
• there are no results while the research is being done

The objective of a marketing approach is centered around two questions: 

• what is it that people are looking for now (and cannot find) 
• what can be done to fulfill that demand now

The data needed for this approach; negative search results. People search for subjects all the time and there are all kinds of reasons why they do not find what they are looking for.. Spelling, disambiguation and nothing to find are all perfectly fine reasons for a no show. 

The "nothing to find" scenario is obvious; when it is sought often, we want an article. Exposing a list of missing articles is one motivator for people to write. Once they have written, we do have the data of how often an article was read. When the most popular new articles of the last month are shown, it is vindication for authors to have written popular articles. It is easy, obvious and it should be part of the data Wikimedia Foundation already collects.. In this way the data is put to use. It is also quite FAIR to make this data available. 

For the "disambiguation" issue, Wikidata may come to the rescue. It knows what is there and, it is easy enough to add items with the same name for disambiguation purposes. Combine this with automated descriptions and all that is requires is a user interface to guide people to what they are looking for. When there is "only" a Wikidata item, it follows that its results feature in the "no article" category.

The "spelling" issue is just a variation on a theme. Wikidata does allow for multiple labels. The search results may use of them as well. Common spelling errors are also a big part of the problem. With a bit of ingenuity it is not much of a problem either.

Marketing this marketing approach should not be hard. It just requires people to accept what is staring them in the face. It is easy to implement, it works for all the 280+ language and it is likely to give a boost to all the other Wikipedias but also to Wikidata.

Thanks,

        GerardM

@WikiResearch - Nihil de nobis, sine nobis

There is this wonderful notion how Research is going to tell us what to do in light of the strategic Wikimedia 2030 plans. Wonderful. There is going to be this taxonomy of the information we are missing.

Let me be clear. We do need research and the data it is based on, it is to be available to us. There is no point in a future taxonomy of missing knowledge when we have been asking for decades : "what articles are people looking for that they cannot find". If there is to be a taxonomy what else should it be based on?

When we are to fill in the gaps of what Wikipedia covers, we can stimulate more new articles by indicating what traffic they get in the first month. Stimulate our readers to learn more by showing what Wikidata has to offer and show its links to texts in other languages. It may even result in new stubs even articles in "their" language. This technology has been available for years now.

The WikiResearch is full of arguments on the importance of citations and Wikidata as the platform for all Wikipedia sources, why then are the WikiResearch papers not in Wikidata from the start. What is it, that WikiResearchers consider that Wikidata is not about them? Just as it is about any other subject Wikidata covers? What is it that makes their work less findable (FAIR) than what is known to have been published as open content by the NIH?

The point I want to make is that no matter how well intended it is what the WikiResearch aims to achieve, they lose the interest, involvement and commitment of people like me, the people they need to get the results they aim for.

Yes do research, but we should not wait for its results, we know how to stimulate people to write new articles.
Thanks,
      GerardM

#Wikidata - A quick and dirty "HowTo" to improve exposure of a subject in Wikidata

When you want to expose a particular subject, any subject, in Wikidata. This is the quick and dirty way to expose much of what there is to know. There are a few caveats. The first is that the aim is not to be complete, the second that it is biased towards scientists who are open about their work at ORCiD.

You start with a paper, a scientist. They have an DOI / ORCiD identifier and, they may already be in Wikidata. First there is the discovery process of the available literature and the authors involved. The SourceMD tool is key; with a SPARQL query or with a QID per line, you run a process that will update publications by adding missing authors or it will add missing publications and missing authors to known publications.

When you treat this as an iterative process, more authors and publications become known. When you run the same process for (new) co-authors, more publications and authors become known that are relevant to your subject.

To review your progress, you use Scholia. it has multiple modes that help you gain an understanding of authors, papers, subjects, publications, institutions.. You will see the details evolve. NB mind the lag Wikidata takes to update its database. It is not instant gratification.

A few observations, your aim may be to be "complete" but publications are added all the time and the same is true for scientists. People increasingly turn to ORCiD for a persistent identifier for their work. The real science is in designating a subject to a paper. Arguably the subject may be in the name of the article but as an approach it is a bit coarse. I leave that to you as your involvement makes you a subject "specialist".
Thanks,
       GerardM

#Wikidata - Naomi Ellemers and the relevance of #Awards

In a 2016 blogpost, I mentioned the relevance of awards. At the time Professor Ellemers received an award and it was the vehicle to make that point in the story.

Today in an article in a national newspaper, Mrs Ellemers makes a strong point that the perception of awards is really poblematic. What they do is reinforce a bias that American science is superior. It leads to a perception by European students that it is the USA "where it is all happening". A perception that Mrs Ellemers argues is incorrect.

NB Mrs Ellemers is the recipient of the 2018 Career Contribution Award of the Society for Personality and Social Psychology.

Wikidata re-inforces this bias for American science by including a rating for "science awards". This rating values awards by comparing them. This rating is done by an American organisation and the whole notion behind it is suspect because the assumptions are not necessarily / not at all beneficial for the practice of science.

How to counter such a bias? As far as I am concerned there is no value in making a distinction between awards and "science awards" and biased information like this should be removed. Just consider, when European science is considered less than American science... how would  African science be rated?
Thanks,
     GerardM

Dr Matshidiso Moeti, an exeption to my rules

When I add scientists to Wikidata, I really want something to link to, an external source like ORCID, Google Scholar Viaf.. When I link publications it is the data at ORCID I link to, I don't do manual linking.

From the sources I have read, Dr Moeti is the kind of person who deserves a Wikipedia article. Her work and the people she works with, the cases she works not only deserve recognition it is imho vitally important that they do, that you learn about them. This is why I made exceptions to my rule.

This is her Scholia, this is her Reasonator and please, take an interest.
Thanks,
      GerardM

The case for #Wikimedia Foundation as an #ORCID member organisation

The Wikimedia Foundation is a research organisation. No two ways about it; it has its own researchers that not only perform research on the Wikimedia projects and communities, they coordinate research on Wikimedia projects and communities and it produces its own publications. As such it qualifies to become an ORCID Member organisation.

The benefits are:

• Authenticating ORCID iDs of individuals using the ORCID API to ensure that researchers are correctly identified in your systems
• Displaying iDs to signal to researchers that your systems support the use of ORCID
• Connecting information about affiliations and contributions to ORCID records, creating trusted assertions and enabling researchers to easily provide validated information to systems and profiles they use
• Collecting information from ORCID records to fill in forms, save researchers time, and support research reporting
• Synchronizing between research information systems to improve reporting speed and accuracy and reduce data entry burden for researchers and administrators alike

At this time the quality of information about Wikimedia research is hardly satisfactory. As is the standard; announcements are made about a new paper and as can be expected the paper is not in Wikidata. The three authors are not in ORCID, as is usual for people who work in the field of computing so there is no easy way to learn about their publications.

What will this achieve; it will be the Wikimedia Foundation itself that will push information about its research to ORCID and consequently at Wikidata we can easily update the latest and greatest. It is also an important step for documentation about becoming discoverable. It is one thing to publish Open Content, when it is then hard to find, it is still not FAIR and the research does not have the hoped for impact. It also removes an issue that some researchers say they face; they cannot publish about themselves on Wikimedia projects. 

Another important plus; by indicating the importance of having scholarly papers known in ORCID we help reluctant scientists understand that yes, they have a career in open source, open systems but finding their work is very much needed to be truly open.

Thanks,

       GerardM

@Wikidata #quality - one example: Leonardo Quisumbing

Quality happens on many levels. Judge Leonardo Quisumbing passed away and a lot of well meant effort went into his Wikidata item.  The data is inconsistent with our current practice so in the Wikidata chat people were asked to help fix the data.

Judge Quisumbing held many positions, one of them was "Secretary of Labor and Employment". This is a cabinet position and it follows that Mr Quisumbing was also a "politician". It is one thing to include this position and occupation to a person, from a quality point of view it is best to include a "start date" a "replaces" an "end date" and a "replaced by". The problem: the predecessor and successor do not exist in Wikidata.

Many a secretary of Labor do have a Wikipedia article and they are included in a category. Using the "Petscan" tool it is easy to import all those mentioned. Typically the quality of the info is good however there is always the "six percent" error rate. Indeed one person was erroneously indicated as a "secretary of labor".  The problem is that people who only care about quality on the item level are really hostile to such imported issues. They are best ignored for their ignorance/arrogance.

A next level of quality is to complete the list with all missing secretaries. This can be done warts and all from the Wikipedia article. It results in a Reasonator page that includes all the red and black links of the article. Many new items are created in the process and having automated descriptions are vital in finding as many matches as possible.

Judge Quisumbing became an "Associate Justice of the Supreme Court of the Philippines" and became the senior associate justice in 2007. Adding associate judges from a category was obvious, adding senior associated judges is a task similar to secretaries of labor. However, a senior is the first among the many and consequently it requires a judgment call on how to express this.

Given that Wikidata is a wiki, you do the best you can to the level that has your interest. There is still a need to improve the Wikidata item for judge Quisumbing but that is for someone else.
Thanks,
       GerardM

@Wikidata - #Quality in a #Wiki environment

What quality is, quality in a data environment has been studied often enough. Lots of words are spend about it but one notion is always left out. What is data quality in a Wiki environment. How does that translate to Wikidata.

First of all; Wikidata serves many purposes. The initial purpose of Wikidata was to replace the in-article "interwiki" links. They were notoriously difficult to maintain, often wrong. A single Wikidata item replaced the links for a subject in all Wikipedias and this brought stability and a high level of confidence in the result. Over time the quality of the "interwiki' links went down; there are fewer people involved adding and curating these links and it is seen as a quality issue when new items are generated for new articles; they do not have statements and are often not linked. There have been protests against these new additions.

A second purpose is the use of Wikidata statements in Wikipedia templates. Assessing data quality becomes complicated as there are micro, mesa and macro levels of quality at play. The micro level: is sufficient data available for one template in one Wikipedia article. The mesa level: is sufficient data available for one template in Wikipedia articles on the same topic. The macro level: is the same data available for all interested Wikipedias and do we have the required labels in those languages.

Quality considerations are driven by this approach. On a micro level you want all awards for a scientist to be linked on an item. On the mesa level you want all recipients of an award to be linked to their item. On the macro level you want all awards to have labels in the language of a Wikipedia and have all local considerations been met.

Standard quality considerations in a Wiki environment are not helpful; they are judgemental. People contribute to Wikidata and all have their own purposes. A Wiki is a work in progress and when quality assessments are to be performed, the question should focus on the extend a specific function is supported. What people seek in support also changes; as long as there was no article for professor Angela Byars-Winston it was fine only to know about her for one publication. Now that Jess Wade picked her for an article, it may be relevant that she is the first and so far only person known to Wikidata who was a "champion of change" and that more papers are identified for her.

Wikidata includes many references to scientific papers and authors. However, so far it serves no purpose. Allegedly there is a process underway that imports papers used as citations in the Wikipedias but it is not clear what papers are used in what Wikipedia article. So far it is a big stamp collection, a collection with a rapidly growing quality. A collection that highlights authors who are open about their work and who share the details of their work at ORCID. In effect, this data set indicates that the relevance of a scientist improves by being open.

Wikidata invites people to add/curate the data that is of interest to them. Particularly the esoteric data, data about subjects like African geography, Islamic history need a lot of tender loving care. It is where Wikidata and the large Wikipedias are weak. For as long as Wikidata is largely defined by the large Wikipedias it will reflect the same biases and these biases will be hard to assess and curate.
Thanks,
      GerardM

The #decline of #Wikipedia (as we know it)

Regularly, we are told about misgivings about Wikipedia. It can not stay as it is, it is in decline; it is all doom and gloom.  NB the use of the phrase "doom and gloom" increased in the 1950s.

So Wikipedia will not remain as we know it? GOOD, it forces us to think how we can improve what we have. When things are to change, what will have a healthy impact? How will we get something that serves us better in "sharing the sum of all knowledge". How will we get more people use what we have to offer and how will we entice more people to contribute to the data collection that is included in all the Wikimedia Foundation projects.

First thing; our projects need to be less US-American. For me, a POV situation I was in, was "obviously"decided in favour of only considering the USA point of view; I let it slide but went to pastures green. The money we raise is for: "keeping the servers going". An objective a bit too limited to my taste but it raises the cash. Money is mainly raised in the USA but in order to be truly global, it is better to raise more equally in every country at least for the amount it cost to serve it. Gapminder is where you may be reminded that money is everywhere. As to the servers, why have all crucial eggs in one USA basket? Given its current politics, there is indeed a potential doom and gloom scenario possible. Having them more dispersed will bring our data closer to our audience, our editors as well. Benefiting them with better performance; that is the easy win. A more complicated solution is in the implementation of the Vrije Universiteit research of a peer to peer MediaWiki.

When our projects are to be less US-American, it is important for spending to be more global too.

When today's Wikipedia practices are no longer considered to be set in stone, we can finally implement features that enable, ensure and enhance its future. First, we should be less self centric; after all there is only one sum of all knowledge and we define only a part of it. Magnus showed how to maintain lists in an efficient way and Amir added recently a "task" to Phabricator to implement proper disambiguation of "red links". We are increasingly aware, not only of the references of all Wikipedias but also of publications by scientists that enable their work to be found. Complement this with the scientific papers we publish and we improve the public relevance of scientists by making them findable, by pointing to their science.

With a changed approach at Wikipedia, we may be bold and change the outlook on what Wikipedia is there for as well. Why not make Wikipedia the gateway to information held elsewhere? Why not show a Scholia page for every scientist we know, why not offer the books at OpenLibrary or inform on the availability of books at the local library?  Why not partner with other organisation we have a shared objective in. But most importantly let us be aware that an African professor teaches in Africa and that we allow for and enable the context of our partners and volunteers.

For me there is no reason for doom and gloom as there are so many opportunities to become even more effective. With a whole new year in front of us; let us do well.
Thanks,
        GerardM

Professor @steve_hanke and reading what is #FAIR

Professor Hanke is on Twitter. He has his five Wikipedia articles and his info on Wikidata is well developed. With a scholar of his eminence, you would expect a lot of known publications as well. However, never mind the 153 English Wikipedia references, never mind the links to 13 external authorities, finding his work is not easy nor obvious.

The problem with Wikipedia references, it is a hodgepodge of links about him and links to his works. His VIAF registration may bring you some of his works but it will not tell you where his books are cited. Mr Hanke does not have an ORCID identifier and consequently it is not easy to include his data on Wikidata.

This is not about Mr Hanke; in certain fields of science people do not have an ORCID identifier or are not open about their publications. When you are interested in a specific subject or a specific scientist, it helps when the information is FAIR.

So what is missing; there is this database with all Wikipedia references, it needs to be included in Wikidata as soon as possible. It may require a fair deal of social manoeuvring to include all Wikipedia references to Wikidata. But the benefits; the benefits will be huge. Given that Wikipedia references are backed up by the Internet Archive, this will extend for these links in Wikidata as well. It makes them FINDABLE and ACCESSIBLE. At Wikidata, this data becomes INTEROPERABLE and REUSABLE (FAIR).

So my 2019 wish for the Wikimedia Foundation is to become FAIR in what it says and what it does.
Thanks,
      GerardM

Dear Katherine: Socialization Tactics in Wikipedia and Their Effects

In the contract of Wikimedia employees it says that they are not allowed to blow their own horn in any of the Wikimedia projects. It is according to a very senior Wikimedia official why they cannot add/contribute to information to scientific papers like Socialization Tactics in Wikipedia and Their Effects in Wikidata.

Dear Katherine, you will agree with me that this is a perverse effect of a well intentioned item in personnel contracts. So let me tell you more about the effects and how we can overcome this issue.

As you know, there is a thriving research community and its recorded presentations showcase the  research on Wikimedia projects. These presentations are recorded and may be found on YouTube. Typically these showcases are based on scientific papers. They should be recorded in Wikidata with all the details like it is done for any and all subjects. When a paper is properly covered, we know all its authors, the papers it cites and in time the papers who in turn cite the paper. When an author is well covered, we know every paper published, co-authors, subjects, subjects, citing authors. We know this because of Scholia. Scholia is what prevents Wikidata from being a stamp collection, Scholia is what makes a subject come alive, it is what brings data together, makes it digestible and gives it relevance.

Not so for subjects relating to Wikimedia apparently for contractual reasons. There are several strategies to overcome this. But first let us decide what we are, what we do and why this matters.

Wikimedia is a publisher of scientific papers; currently there are three and in order to raise the impact of the papers it publishes, they have to gain visibility. To do this we can associate with ORCID, and publish and certify all the details of papers to its authors. One of the things we do on a big scale, is re-publish data from ORCID. They have a program whereby they can sync their information with ours.. They collaborate with Crossref and so could we. When we do, we make Open Science much more visible.

Dear Katherine, what we have shown is that we can and do care about publications, about citations. We care about science. The least we want is our own research to be presented the best we can. In order to achieve this we have to consider the unintended impact of a provision in a labour contract and overcome this self inflicted barricade.
Thanks,
       GerardM

#Wikidata and the papers of Professor Wiesje van der Flier

Professor van der Flier has an ORCID identifier. She works at the Neurology/ Alzheimer center of the VU University Medical Center.

Mrs van der Flier has in Iris E. Sommer a co-author. We know that they have at least one co-autor in Edwin van Dellen. There may be more and we will certainly know for those co-authors that are as open about their work. Professor Sommer was the initial interest because she is a member of "de Jonge Akademie".

We will know because they have an ORCID identifier. At Wikidata it serves two vital functions; it helps with disambiguation, a job was ran for all people with the surname "Li"... Given that ORCID allows people to share their information publicly, it allows us to import the publications of authors and identify their equally open co-authors.

The Scholia page for Professor van der Flier knew 31 people who were certainly knew to me. They are being processed and chances are that at the end of it Mrs van der Flier will know more co-authors, more papers and her representation in Wikidata will be more complete.
Thanks,
      GerardM

Yes, it will only know the co-authors that are open about their work but, that is only FAIR.

#Science; I can read

The basis for what Wikipedia articles offers are its sources. Those sources can be anything and when we want to know the veracity of what we read, the sources have to be available. Not only that, we rely on those sources to be consistent and we rely on those sources to be readable.

When sources are on the web, the Internet Archive will have iterations of a source available in its Wayback machine. It ensures that sources remain available and thereby much of the integrity of Wikipedia is maintained.

For scientific sources we are unlucky. Reading a scientific paper can set you back $45,- and it only allows you to read that paper for a day.. In effect all such papers cannot be read; we "have to" trust them and there are plenty of papers that are extremely problematic and also expensive to read.

Many papers are increasingly FAIR. They are Findable, Accessible, Interoperable and Reusable. The best first line partners we have are again the Internet Archive and ORCiD. Organisations like the Biodiversity Heritage Library store scientific papers at the IA thereby making them available for as long as the IA exists. ORCiD is where living scientists identify themselves and if they so choose, the publications they (co-)authored. It makes them and/or their papers findable. The papers typically include a DOI making them accessible. After that it is anyone's guess if you can actually read them.

Scientists that are open about their work may find that they and their work found its way into Wikidata. For Karsten Suhre this was done; his scientific work is represented in his Scholia and many of his co-authors have been automatically added from ORCiD and have been processed as well. His co-authors that are not as open are largely missing but that is only Fair; I do not volunteer to promote them.

What Wikidata has is not representative of all of science but it increasingly represents the science that is open access, the science that I can read, that you can read that is for all of us there to read. The science that deserves to be used as sources in Wikipedia. We can read.
Thanks,
      GerardM

Bringing more #science to @Wikidata

Slowly but surely more scientific papers and their authors find their way into Wikidata. Particularly when scientists have staked their claims in ORCiD, adding is easy and obvious.

It is easy because in ORCiD every author, paper, organisation et al have their own unique identifiers. So when you add a paper, all authors who claimed to be author are already linked.

Earlier today, I added papers and co-authors for Jaume Piera. As a consequence Laura Recasens was added today and as you can see in the illustration of her co-authors, several new authors popped up as a consequence.

To do this I use a combination of tools. Reasonator is my preferred tool to display data; for scientists it tells me if he or she is known to be an author. When there are, Scholia presents the scholarly author information. Of particular relevance to me is the co-author presentation. For co-authors shown in white, no gender is given in Wikidata and when the name is an initial and a surname, I will look up the ORCiD information to find a full name. Typically that is how people are known in ORCiD.

I use the SourceMD tool for two purposes; "creating and amending papers for authors" and to "add metadata from ORCiD authors to Wikidata". It is processed in a batch job, I run one job for up to 15 authors at a time and it takes forever to run.

Other people run other jobs, a particular hat tip to Daniel Mietchen who makes sure that recent publications find their way into Wikidata and finds many other reasons to improve on what we have. All this would not be possible without the many tools by Magnus and for Scholia I do thank Finn Årup Nielsen thanks to this evolving presentation, science as a process comes alive.

There is more to do; the Wikipedia citation are in a separate database and much of its data may be found in Wikidata.. Who will merge them. Publications do cite other publications, it is a field I am not really interested in.. They are added so there must be a tool.

When you are interested in a particular scientist, a particular paper.. Just use the tools and slowly but surely we all make Wikidata a great tool to represent science fact.
Thanks,
      GerardM

More #impact for your #science is in being a #source at @wikipedia

In a study about how students research a new subject it was found that they read the Wikipedia article first. Then they move to its sources and from there it takes off.

In order to have an impact you, as a scientist, wants to be their first getting the attention of your work. There are a few tips.

• Make sure that you and your work are known. First make your work known at ORCiD. From there it gets into Wikidata
• PS check out the Scholia presentation of you and your scientific work.. (example)
• Make sure that your work can be read. Wikipedia actively seeks free reads using the OAbot.
• Do not think that current practices of your field will benefit new scientists in the future. Many fields are not well represented at ORCiD

For your information. There is a database with the sources used in Wikipedia. The only thing lacking is that this database still needs to be integrated in Wikidata for it to gain a real impact.
Thanks,
      GerardM

#Library #Science - Prof Dr Frank Huysmans

Mr Huysman's works at the Universiteit Amsterdam. He teaches "Library sciences" and as is usual for a scientist, he has a fair share of publications to his name.

The problem is that this field of science is not well represented in Wikidata. There were no publications to his name. Importing them from ORCiD proved problematic; only four were added out of the 22 known there. Working from what was known, it was possible to add co-authors and enrich those, seek out their co-authors and enrich them as well. The result is the current 40 publications to Mr Huysman's name.

Mr Huysman has both a Twitter and an ORCiD account. Everybody who does, in Wikidata, will have his or her profile in Wikidata updated thanks to a job that is running by Daniel Mietchen. They are the ones who publicly promote their science and in this way they gain some additional credibility.

NB when you have an ORCiD and twitter, tweet #IcanHazWikidata and you will get your Qid.

When you care about your science, do maintain your ORCiD profile because it will make your papers, your co-authors and the organisation for more visible in Wikidata.. Your #Scholia profile will get better and better and chances of being quoted in Wikipedia improve.
Thanks,
     GerardM

#Science - Ladies you work together

Yesterday I singled out a Paola Giardina because she was a co-author of someone who had SO many co-authors, I could not manage the information that was in there. Yesterday Paola had a large number of co-authors that were white (no gender info). Today there are even more present.

One thing is pretty obvious in what I see: women are more likely to work with women than men. When you want to analyse this, it is important to know the data this is based on. At this time 31% of the people with an ORCiD identifier are female. When you consider probability, it is likely that some 31% of people who have not been associated yet with a gender will be female as well.

In many universities the percentage of women studying is more than 50%. All of them get involved in research. All students are involved in the production of papers and all of them are entitled to their ORCiD and to their Wikidata identifier.

So when we want to express the notability of women in modern science, all we have to do is ask any and all scientists to make their publication details part of the open record. Slowly but surely, it will become obvious who and where the best science is produced and who collaborates with whom.
Thanks,
     GerardM

#Accepting science; the solution is in the reading not the publishing

The most important thing religion has over science? Its papers can be read. Sources like the Bible, he Quran can be read for free. You can get *your* copy from many true believers. A copy is in your library. With science the papers that can prove to you that goldfish should be classified as endangered are behind a paywall. It is only your common sense that might say: "Hey, wait a minute.."

When Wikipedia insists on its sources, they are only functional when these sources can actually be read. This is why the Internet Archive plays such a vital role in maintaining the validity of stated facts.

Some scientists think that "the public" cannot read scientific papers. They forget that even for scientists a paper that cannot be read is a paper that does not exist in their contemplations. The public does read scientific papers. The Cochrane crowd for instance reads papers and checks particular premises for validity.. We know that scientific research of coronary disease was biased for males and as a consequence women still die. A bias like that is what they look for, it is why they reject many papers because they are basically *not* valid.

There is a lot to do about what scientific publishing should be. How it should be funded.. The base line is that when a publication is not available for anyone to read, the facts do not matter. Why believe vaccines are safe when the publications that prove it are behind a paywall?
Thanks,
       GerardM

#Wikidata - the missing #Elsevier papers

It started with a Twitter tweet.. "There is also a professor Elsevier". A search found that Professor Cornelis J. Elsevier works at the "Universiteit of Amsterdam". He did not exist at Wikidata and there was only one paper to be found for him.

Adding this one paper was done with the "Resolve Authors" tool. The Scholia tool for Mr Elsevier showed a few co-authors and in addition to this several "missing co-authors" could be found.

In order to show more papers for Mr Elsevier, more papers needed to be imported into Wikidata. This can be done for authors with an ORCiD identifier, particularly the ones with no known gender. So far they did not get much TLC. Just running the "SourceMD tool" for them will add additional papers and associate other authors to these papers as well.

This is an iterative process and I focused for no particular reason on Mrs Barbara Milani. Processing her co-authors meant that more co-authors came out of the woodwork. At this time, 13 new authors with an ORCiD identifier popped up. Once they are processed more papers will be known to Wikidata and given their relation to Mrs Milani a reasonable chance that these papers link to Mr Elsevier as well.

At this time Mr Elsevier is known to have 7 publications.
Thanks,
        GerardM

#Wikidata - the #heart of women differs from the heart of men

The assumption that the heart of women and the heart of men are the same proved to be lethal. The "Hartstichting" is a Dutch charity that raises funds to combat heart disease. One of its studies is done by professor Hester den Ruijter of the Utrecht Medical Centre. Her study aims to map those differences and it is part of an effort to provide equal quality medical support for heart matters for both genders.

As a scientist, Mrs den Ruijter was involved in the production of many scholarly papers with many co-authors and this is best presented by Scholia. Yesterday Mrs den Ruijter was only known to Wikidata through her papers. Today she has her own item, the papers have been associated with her and so have been many of her co-authors. Many other authors have their own item who are associated with the research that indicates how the heart and its diseases differs between the genders and differs based on ethnic background.

It is vital to recognise these differences, survival relies on it.
Thanks,
      GerardM

#WikiCite - Thank you #Orcid ! - #IcanHazWikidata

The question "I have an ORCiD profile, how do I get it in Wikidata" was asked on Twitter. Using Magnus's tool public information was imported and as a result information can be shown in Scholia.

Paolo Cignoni made a request using the #IcanHazWikidata hash tag and his papers were imported and it shows nicely in Scholia. It includes several of his co-authors, for the ones in white we have no indication for their gender in Wikidata. That is easy to fix.

There are probably a lot of co-authors missing.. One way of finding the missing co-authors is by adding "/missing" to the Scholia link. You can check for an ORCiD identifier and add a found identifier. You identify the papers already known to Wikidata and they are attributed to the co-author or, to a citing author.. I added a John W Goodby to make the picture more complete. It is easy and mostly obvious what to do.

What makes all this possible? Open data and a bit of effort.. As you can see in the later picture, just running Magnus's tool for a few co-authors changes the outlook considerably.

Are you a scholar and do you want to see your initial Scholia information? Just add your Ordid ID in a tweet with the #IcanHazWikidata hash tag.
Thanks,
      GerardM

#Wikimedia - Relevance of #science - Kate Ricke

A lot of soul searching happened to determine why Wikipedia failed to notice Donna Strickland only once she received the Nobel Prize.. What is more astounding is that Wikidata failed to include her.. No Scholia information for her and her research. What we have at this is likely to be a subset of the "Stricklands papers".

We do not know who will be seen as a scientist of similar relevance but we do know that a lot of rubbish is floating around.. it is called fake science, fake news and countering this is where big organisations like Google and Facebook rely on the information in Wikipedia.

So Mrs Kate Ricke is another scientist that did not get Wikipedia attention so far. Mrs Ricke tweeted about her paper Country-level social cost of carbon. It and the papers produced by her and her co-authors are quite potent.

When you learn about a paper like this, you can add it and its authors to Wikidata. When Orcid has information about other papers, you can import these papers as well building on the web of science about of one of the most important subjects of our time. In addition co-authors of these other papers can be included as well as the authors citing these papers.

When relevance is given to the science of a subject like climate science, it becomes possible to contrast it with what some politicians want us to believe.
Thanks,
       GerardM