#Wikidata - Thomas Scheibel - a German scientist

When Wikidata is filled, it is typically content from the English Wikipedia. This adds to an existing bias. Germany is known for the high quality of its scientist and, Mr Scheibel is one of them.

Recently all the German "science awards" have their data imported in Wikidata. Mr Scheibel is only one of many Germans who's career is now better represented. Four of the awards bestowed on him are now well represented. For recent awardees Wikidata was searched for their presence; something like 25% of these people already existed.

The diversity of Wikidata is better served when more data from the "other" Wikipedias is imported. This is best done by people who know a language and for me Dutch, German and French are obvious targets. I can manage in many other languages but it is easier to make mistakes.

What we need is champions for the data for countries and cultures. They can ensure that we are truly of global relevance. This is one way of ensuring that we will be of relevance in 2030.
Thanks,

      GerardM

#Wikimedia #GLAM - donation of pictures from #Syria

The Tropenmuseum was asked to make available pictures they have from Syria. Today, it is my pleasure to inform you about a donation by the "Nationaal Museum van Wereldculturen,

At the time we celebrated the Erasmus Prize and, at the time we worried about Bassel Khartabil. There is little hope for Bassel but there is hope for us to become informed about Syria.

It is Ramadan, and whether you believe or not, this is an auspicious time to consider the information we have on Syria.

Share the pictures you hold in Commons. As we learn just a little more about the country, its peoples and history we may find them to be just like us.
Thanks,
       GerardM

#Wikidata - Theodor Eschenburg award

Mr Eschenburg was a German journalist. Mr Eschenburg received nine awards, you will not (yet) find this in Wikidata and had one award named after him; the Theodor-Eschenburg-Preis.

All the information about award winners etc is in the article of the conferring organisation; the Deutsche Vereinigung für Politikwissenschaft. That works fine in Wikipedia but the award is surely not an alias for the award in Wikidata.

When I find such issues, the situation is easily by creating a new item.

NB when you look at the Reasonator page for Mr Eschenburg, check out the long line of notable people he is part of..
Thanks,
       GerardM

#Wikidata - Chuck Davis and #VIAF

Mr Chuck Davis used to dance, and make people dance. He came first to our attention because he was awarded the Capezio Dance Award and consequently a Wikidata item was created on March 26. His Wikipedia article was linked on 22 May 2017‎ seven minutes after the article first appeared.

The most fabulous thing is that when I checked on May 23, VIAF already had a link to his Wikidata item. It is proof positive that librarians are actively including Wikidata to VIAF. This is the perfect argument to intensify the collaboration with librarians to give readers of Wikipedia and readers of library books the best of our shared sum of all knowledge.
Thanks,
       GerardM

NB Mr Davis died on May 14, 2017.

#Wikimedia - Presenting #authors in #Scholia

In a fairly rapid pace more and more literature and its authors are included in Wikidata. Many publications are used as sources in a Wikipedia and others get included because scientific "facts" supported by sources find their way in Wikidata as well.

Scholia is a tool that indicates where authors fit in (it does more <grin> but this blog post is only about this </grin>).

When multiple publications are known for an author, it shows the distribution of the publications in time, the number of pages (when known), venue statistics, a co-author graph, the topics, associated images, a topics-works matrix, education, employer/affiliation, academic tree, locations, citation statistics, citations by year and finally citing authors. There are two ways of expressing an opinion, it is exhaustive or it is a bit much. Whatever your choice, a tool like Scholia is awesome. Just the thought that Wikidata already has a relevance that justifies a tool like this.
Thanks,
      GerardM

#Wikidata - One size fits all but only size 47 serves me well

When a Wikipedia decides on its policies; in the end it is a "one size fits all". It is the policy wonks who decide and all editors have to abide by it and all readers suffer the consequences. Shoes are made for walking but you only get the best mileage out of shoes when they fit.

When you look at the categories for different Wikipedias they are not the same. Some explicitly exclude the standard information of other Wikipedias. As a result there is no universal standard and this is detrimental to readers who frequent multiple Wikipedias.

At the same time, a Wikipedia community may define its policies and practices as they see fit. This does not mean that they define what individual readers actually prefer only what they get presented. The amount of categories in use and their structure is a good example how editors define information given or withheld from readers. Increasingly the combined information from categories from Wikipedias find their way into Wikidata. When a Wikipedia does not include a category, by using the definitions for a category it is possible to present many if not most of what a category could have been.

The question is not can we show what articles of a Wikipedia would be in a category, the question is if our readers will be supported and if not what arguments we have to disallow readers the structures they personally prefer.
Thanks,
      GerardM

#Wikidata - Manfred Rudersdorf has no #Wikipedia article

Professor Manfred Rudersdorf (left) has no Wikipedia article. As an historian he is expert on the history of "his" university. In the picture you see the presentation of this book to the rector of the University of Leipzig.

When you inspect the Reasonator page for Mr Rudersdorf, it is remarkably complete. It demonstrates that the inclusion from sources external to the Wikimedia Foundation slowly but surely results in proper information.

When you think of it, finding people like Mr Rudersdorf is obvious. There is only one sum of all knowledge and much of it is connected in one way or another. In fact it is a puzzle and we Wikimedians are all too familiar with puzzles.
Thanks,
     GerardM

#Wikidata - Johanna Mestorf is not a #German

Johanna Mestorf was the first "German" female Professor. She was however not German as Germany did not exist; Mrs Mestorf was from the Kingdom of Prussia. Wikipedia has it that Prussia existed from 1701 to 1918 and Mrs Mestorf died in 1903. In the totality of the German speaking world Mrs Mestdorf was prossibly the first female Professor.

Current nationalities and previous nationalities do not match. Trying to understand historic facts from a modern perspective produce a fake perspective.

Not calling Mrs Mestorf German may be problematic for some. But hey is that not what a neutral point of view is about?
Thanks,
      GerardM

#Wikipedia - #German #Science #Awards II

Adding awards to scientists makes it obvious that there are many scientists out there. The German Wikipedia knows about some 366 German science awards and, they are not provincial. For many awards any deserving scientist may be recognised.

As you move through the list, German Wikipedia practices are different. Some Wikipedians do not like red links so the award winners are just text. Luckily for me, others still allow for red links and this helps a lot.

The Heinrich-Emanuel-Merck-Preis article sees a lot of red. When an effort is made to connect these red links, Wikidata already knows about many of them. Petra Stephanie Dittrich is one such. Many scientist like her have been included because they are included in AcademiaNet.

When I add missing people, given that this is about German data I prefer to add the labels in German. Mr Jonathan V. Sweedler is of the "University of Illinois" and therefore likely American but that is a detail I frequently leave to others.

There is yet another group of scientists finding their way in Wikidata. They are the authors of papers that are used in citations or to establish fact in Wikidata. Awards are another relevant aspect of these scientists.
Thanks,
     GerardM

#Wikimedia - #Classifying Saadia Zahidi

Mrs Saadia Zahidi came first to the attention of the Wikimedia movement because she featured in the BBC's 100 Women both in 2013 and 2014.

The BBC is really British but the conclusion that Mrs Zahidi is British is a stretch. She studied at three universities; two in the USA and one in Switzerland. She grew up in Pakistan and is a member of the Executive Committee of the World Economic Forum also in Switzerland.

It is easy to claim relevant people as being part of a group. The urge to classify is obvious but classification is inherently discriminatory. With people this is more or less accepted. For Mrs Zahidi her affiliation with the World Economic Forum is missing but she is at least recognised as an author, It was easy enough to add {{authority control}} in her Wikipedia article.

Classification is a hot button subject at Wikidata. There are those like me that resent this weird notion that subclasses are a good thing to have. There is a lengthy discussion about the validity of subclasses for guns, spacecraft and such stuff. It is so convoluted that you need to be an expert to understand the classes in the first place. What makes this nonsense so infuriating is that it makes Wikidata solidly a one maybe few language resource. The argument that it combines things that are the same can be easily ignored because proper statements and a query provide the same result.

Classification is discriminatory. In the past an explanation was asked and not forthcoming. It is wrong to call Mrs Zahidi British. At best she lived or lives in the UK. It is wrong to have tiny subclasses it largely prevents the use and usefulness of Wikidata.

As a movement we should hold back our urge to classify. Classification is a judgement; we should be more descriptive.
Thanks,
      GerardM

#Wikipedia - #German #Science #Awards

There are many different awards known on the German Wikipedia. The category for Science awards alone includes some 366 entries.

For whatever reason most of the implied data has not been transferred to Wikidata. It is probably because there are no or few categories for people who received an award. This is where Awarder, yet another tool by Magnus can make a difference.

The Aby Warburg Prize for instance included much information and by running the tool missing recipients were added including the date it was awarded. The Adolf Windaus Medal did not know any recipients and it takes as long to add all of them. When you run on data from both the German and the English Wikipedia, the result is even better as it was for the Berlin-Brandenburg Academy Award.

To complete the information, there is the "conferred by" and the "named after" property to consider as well as looking for people the Wikipedia does not know. You then find the missing links and people known on another Wiki project. It is easy to add new items for the "red links".

The Albrecht-Ludwig-Berblinger-Preis is a redirect. There are no links in the article for the people who were awarded an award. Adding an item for the award is easy adding at least one recipient is easy as well. This is where Awarder does not help.

The Augsburger Wissenschaftspreis für Interkulturelle Studien award information is in two parts. The first part with data until 2007 can be read by the Awarder. The second part includes a more complex table and cannot be read. In the past the Linked Items tool did the job. It did not include all the associated dates but it did produce a list of all the Wikilinks. They could be processed by PetScan.

Adding information like this from the German Wikipedia takes some effort. In this way we improve the global reach of Wikidata. For awards like the August-Lösch-Ehrenring there is the occasionally new information in the sources for the award. At some stage bots will pick up new information added in Wikidata to make suggestions to Wikipedia editors.

As a rule the quality of Wikipedia articles like this is good and it is worth the effort to promote science.
Thanks,
      GerardM

Teaching #Wikipedia using local #news

One of the functions of Wikipedia is providing a background and, to understand what is in the news, you need a lot of background. This is one of the first things to overcome when children start reading the news.

When newspapers are introduced in the class, a first exercise is to just read and have the children select a few articles that are of interest to them. As a follow up they analyse the text for concepts that you have to know about to understand the article. They make lists for the selected articles.

On another day they select new articles, make similar lists but are asked if there is an overlap with other lists. They are asked to write a few lines for all the concepts in such a way that there is enough to understand the article coming from every original news article.

This is when Wikipedia is introduced. The children is shown that it provides basic and neutral information that help them understand, for instance, the news. Their next challenge is read Wikipedia and see how its articles help understand the news. When subjects are missing, they make a list.

The last thing to do is write stubs for missing Wikipedia articles. What then may follow is the standard course ware for writing Wikipedia articles. The objective for this approach is that it helps children to better understand the news; understand that news is a continuum. The news is compact and assumes basic knowledge and such information can be found in Wikipedia.
Thanks,
       GerardM

#Wikidata - Steven E. Petersen

Some say that Wikidata is only there to support Wikipedia. Maybe. Wikidata includes information about Mr Steven E. Petersen. The English Wikipedia has three red links for the Grawemeyer Award for recipients in the field of Psychology.

Mr Petersen was already known to Wikidata as the author of four publications. Some will argue that publications are the bread and butter of Wikipedia and they are.

The sum of all knowledge is one whole and as such all Wikimedia projects together are tools that bring all the information, all the knowledge to everyone. All do it in their own way and as such Wikidata does support Wikipedia and it supports Wikipedia among all the other things it is useful for.
Thanks,
      GerardM

#Wikidata - Award for Scientific Freedom and Responsibility

Mrs Elizabeth Loftus won the Grawemeyer Award in 2005. When you read her Wikipedia article, she has been celebrated frequently for her work.  One way to consider the relevance of people is in the similarities people people share with others and Mrs Loftus shares many awards with many scientists.

As we all stand up for science, several of the awards celebrate science and taking a position that is not popular with the powers that be. One such award is the Award for Scientific Freedom and Responsibility it includes Mrs Jean Maria Arrigo and in my opinion her Wikipedia article does not do justice to the cause that got her this award. Often the true heroes of science do not get the recognition they deserve.

Not everyone goes out to march for Science. I am not in the USA and I do sympathise with this cause. What Wikimedians can do for science is document science, scientists and the scientific process and use scientific practices to ensure that Wikipedia does not carry the false flags some !@#$ insist on.
Thanks,
      GerardM

#Wikidata and #Libraries - RAMP and #WorldCat identifiers

There are books and there are authors. Libraries are first and foremost in the book business. They register their books because otherwise they do not know what they have. Authors are important but they are secondary. Particularly the not so well known authors, authors with one book do not always get the full treatment. There is a registration, sort of, and it is waiting in the wings to be fully registered.

Libraries and librarians are Wikimedia's friends. A presentation from the IUPUI University Library shows how their wish for good documentation works for them. They release the rights to their "finding aids" and add missing "authority records" for people and companies. They then create Wikipedia articles based on their "finding aids" and add Wikidata records. They have it down to an art so much so that their tool, RAMP (Remixing Archival Metadata Project) lives as a web-based tool on WMFLabs. This invites any librarian anywhere to join the fun.

One of the articles is about Hugh Ned Brown. The article is good and the Wikidata is quite good as well. RAMP is a tool for librarians. It is wonderful and if there is one question left, it is how Wikimedians can contact librarians like the ones at IUPUI to fix the issues we find at our end.
Thanks,
      GerardM

#Wikipedia #Research - World Famous in Holland

When category names are well chosen, they predict similarity between what is in a category. A research paper named: "Recognizing Descriptive Wikipedia Categories for Historical Figures" came to this conclusion, it is complete with a lot of mathematics. They did their panel research so it must be good.

At the back of the paper there is a list of English categories and their "Surprise level". It focuses on balancing the effect of both size of the category and the probability of inside-category pairs become close neighbours.

This makes size of the category relevant. One of the categories is "International Tennis Hall of Fame inductees", it has 222 entries. The German category knows about 22 additional inductees. The S-level is 163.84. For "24 Hours of Le Mans drivers" there are 1,247 entries and the German category knows about 501 additional drivers, the S-level is 138.47.

Categories in Wikidata may include a definition of its content. For in stance: "is a list of" - "human" with a qualifier of "award received" - "International Tennis Hall of Fame". This definition can be used in tools even bots to include all the missing statements in Wikidata.

The absence of articles shows a bias; they are what editors found notable enough to write articles about. It is however not that relevant. One question is: does this research translate to other Wikipedias and its categories another is if there is a predictive value for the relevance of missing articles in other Wikipedias for the same category.

For some categories, relevance exists because of the interest in a specific culture. For me Johan Cruyff is more relevant than any "wide receiver" in American Football; I cannot name one. This research is interesting but it does not give us the most famous people ever. This is obvious because of the distribution of topics of English Wikipedia.
Thanks,
       GerardM

#Wikidata user story - The Golden Brain #Award

I have added people who won the Grawemeyer Award. This award has many categories and I concentrate on the category "psychology". The people in this category get extra attention; all the information from categories and awards are included as well.

Often people turn out to be connected through multiple awards like Mrs Anne Treisman and Mrs Leslie Ungerleider. They both received the Golden Brain Award as well.

When you read the article on the Golden Brain Award, the winners are all in a nice table. For each of them there is either a blue or a red link and for some there is only a string of text.

2015

Okihide Hikosaka

National Eye Institute

US

Adding the missing people in Wikidata is not hard, just some additional work. For Mr Okihide Hikosaka there is enough information to add an item to Wikidata. When this is done for all the award winners, it is possible to create a list with the same information in any Wikipedia. 

By adding all this information, people who are into what I concentrate on are better connected. They have more near links to data that links to other people who are relevant in the field of psychology and my hope is that this will trigger people to give attention to missing articles and information.

Thanks,

     GerardM

 

#OCLC, #VIAF and #WorldCat - I love them and, they could be even better for me

Jimmy Wales is doing his thing for proper news and it is welcome news. When it pans out it will work but people have to read what WikiTribune will bring. As always it takes education and access to information. Libraries have always been the bedrock of available information to people and the OCLC is what connect the worlds libraries. So it is important for it to be as good as it can be when it is to bring more people to libraries and read.

The OCLC brings two programs that are important to me as a person and as a Wikimedian. They are VIAF and WorldCat. VIAF is the "Virtual International Authority File"; it is a system that brings together the information the world's libraries have in their system and aims to connect them. VIAF is largely maintained by software but there are processes to fix issues that do occur. Wikidata is connected to VIAF because it is the link to information about authors that exists in Wikipedia and Wikisource in many languages. There are bots that do find VIAF identifiers thanks to identifiers known at Wikidata and once a month Wikidata identifiers are updated in the VIAF registry. Using VIAF on its own, you will find for instance a Uilyam Şekspir.

WorldCat is where it becomes interesting to readers. For me its information is available in Dutch. Echoing a blogpost on the OCLC blog we can bring more joy to the library's website and for people who come to the library world from a Wikipedia there are opportunities. I have a profile at WorldCat; it knows my library because I entered it as one of my favourites. WorldCat assumes that it knows my location and suggest a library that is not near to me and that is not useful. So picking up on the cookie information it does not need to know my location and allow for an easy link to my library. This will help me. What WorldCat could do is ask people if the suggested library is indeed their library.

The blogpost mentioned earlier talks about web analytics. I would absolutely love to know how many Wikipedia readers get to VIAF or WorldCat. It would be wonderful to know if we get readers connected to their libraries. When we do, the effect of improvements will show and that will motivate Wikimedians even more to get people their facts, and have us share in the sum of all knowledge.
Thanks,
      GerardM

#OSM - Districts of #Kerala

A Wikipedian asked me to blog about this map. The map is shown from within the English Wikipedia. It works really well on my mobile (an i-phone). The next step, integrating multi layered maps in articles.. and on a mobile?
Thanks,
       GerardM

For some documentation..

#Wikidata user stories - Suggesting Henry Putnam, a great #Librarian

As software suggest what articles to write, it is relevant to understand what logic it is based on. Phenomena like the "six degrees of separation" made popular around Kevin Bacon has its scientific approach in graph theory "betweenness centrality". This is used as a basis in the research that what articles are important and what automated suggestions to make.

Mr Putnam is one of the more relevant librarians. He developed an eponymous classification system, continued its development as the Librarian of Congress (it is still in use), was twice president of the American Library Association and was a knight of the order of the Polar Star. When weight is applied to references to a person, all this is of relevance in the right setting.

When an article is to be written or improved, it helps when it can be suggested what it is that can be improved. By including statements in Wikidata suggestions can be made based in the local language. Facts like date of birth and death are also easy and obvious.

So when people consider a particular subject to be of universal relevance, it helps when associated subjects are well developed in Wikidata. When for all the presidents of the American Library Association many facts like where they studied, where they worked and what awards they received are included. When this is done for all the people who share categories, the betweenness of many influential librarians increases. This will have its influence on what is suggested for people to do.
Thanks,
       GerardM