#Wikidata - What to do in a #Datathon III

One goal for a datathon is to demonstrate, to teach the use of the various tools. When you want to be effective individually or as a group, you have to use tools. The Wikidata statistics make it obvious; the numbers of items, statements and labels are huge. To have an impact it is important to use the tools that are available.

The mathematics involved explain how you can have the most impact. Set theory helps you understand how to approach this effectively. When you add one label and it affects 10,000 items it is powerful. When you add every known lawyer of a country in one go and it affects 10,000 items it is powerful.

Choosing the tools that help you be effective is therefore what you teach the participants of a datathon. They go home and they are likely to continue using the tools.

The most obvious tool to introduce is Reasonator. For it to function well, it needs to be configured. This is done partly from the personal settings. This ensures that you Wikidata data will show as information in Reasonator in *your* language by preference.

The other part to configure Reasonator is Widar. Widar is a tool that authenticates the edits you do in Reasonator to Wikidata. In the screenshot above there is a picture that was added to Wikidata in this way. The most relevant use case is adding labels in your language. The missing ones are underlined in red.

AutoList is probably the second most relevant tool to demonstrate. It provides an interface to several tools. One of them is the WDQ or Wikidata Query another is the CatScan. Combining these tools allows you to find every human in a category that is not known in Wikidata for what the category indicates is true about this human... and then add the statement that does just that.

There are other tools that are extremely useful. In a datathon it is important to have a mix of people. People who know the tools well, people who are interested to learn and people who have a "mission". When the activities concentrate on the "missions", it means that you zoom in on a subject and apply the skills and labour on doing good. This makes it clear how relatively little effort can have a huge impact. Not only for a language but also for a subject domain.
Thanks,
       GerardM

#Wikidata - What to do in a #Datathon II

There is little point to a Datathon when the results have no practical impact. By implication there is little point to Wikidata when it has no practical application. Luckily most of the Indian languages use Magnus's extension to search making any and all advances in Wikidata immediately useful.

The next thing is to decide for a datathon is what it is you want to expose in your language, your script. The result will be biased but the difference is in not sharing this information. That option is even worse.

Having said that, there is one upside to concentrating on a subject domain. Take for instance the "King of Nepal", you will see that it is referred to "List of monarchs of Nepal". All these listed monarchs are now a "king of Nepal". It now takes one person to add a label in Nepalese to make this label visible on all the monarchs of Nepal. It is a subclass of "king" and, it takes one person to add a label in Nepalese for all subclasses of king.

This is the beauty of adding labels in Wikidata. Once it has been added, it is used everywhere. A label for "politician", "lawyer", "date of death" are added once and are in use on hundreds of thousands of items. Adding labels is therefore really satisfactory and effective.
Thanks,
      GerardM

#Wikidata - What to do in a #Datathon

I was asked for pointers for a "datathon". It is adding data to Wikidata for a specific purpose. The most obvious thing is to be clear what it is you want to achieve.

What to add to Wikidata:

• adding labels to items in a language
• adding statements for existing items
• adding items and statements based on a Wiki project
• adding missing items to create links among items

Realistically, it is always a bit of all of that. The people attending are not all the same either, they differ in interest and they differ in skills. One goal for a "datathon" may be the transfer of skills. When this is the case, start with the basics of Wikidata. How to add labels, how to add statements. how to add items. 

Another goal is to add information for a specific domain. This may be based on information known to a Wiki project but that is optional. When information for a specific domain is to be worked on, Working together and use as many tools as available makes a real difference.

As a blogpost should not be too long, more later..

Thanks,

      GerardM

#Wikidata HOWTO - It is in the news

The "concept cloud" of what is in the news, the right livelihood award is topical. According to the article, it is a prestigious international award. One purpose of a concept cloud is to make sure that the information relevant to a subject is well presented and that statements are added.

Awards like this one have been given over many years. Wikipedia often has a category with all the laureates. This is a perfect opportunity to use Widar to add the fact to all the laureates that they received this award.

Obviously you can use it for other categories as well.
Thanks,
      GerardM

#Wikidata HOWTO - #Lists

Lists are evil but Wikipedia contains many of them. The question is how to deal with them. The problem is that Wikipedia often uses a list as an item of a list; the "president of Armenia" is actually the "List of presidents of Armenia". To make it worse, the interwiki links bundle these together as if they are one and the same.

The solution is simple; create a singular item, split up the interwiki links as seems obvious. The next thing to do is to add "is a list of" on the list item and refer to the singular item.

As the Italians are all having Wikidata search results available to them, I was disambiguating "Michael Skinner". An article about the biologist Michael Skinner had me look if he was already known to Wikidata..
Thanks,
      GerardM

#Wikidata HOWTO - Some properties are best used as a qualifier

Some Wikidata properties are practically by definition qualifiers. Consider time for instance, there is the "point in time", the "start date", the "end date" and all of them are in relation to something else. For instance when a Noble prize was awarded, when a King ascended to a throne and when for whatever reason he was no longer the ruler ... "Le roi est mort. Vive le roi !!".

Working on Wikidata items is very much a learning process. As you go, you learn and come to conclusions. For me it is now obvious; properties about time and dates are qualifiers.. always.
Thanks,
      GerardM

#Wikidata HOWTO - micro tasks

When you have some spare time, there is always something that does not take long to do. The main page of the English Wikipedia mentioned the scientist Michael E. Brown. In 2012 he was awarded the Kavli prize for astrophysics. It does not take much time to make a statement about this prize on the "item" for Mr Brown and on the the items for the other recipients as well.

Yes, many of them received other prizes, but that is another job well worth doing.
Thanks,
       GerardM

#Wikidata HOWTO - generated descriptions

#Disambiguation in Wikidata is typically done based on the descriptions of items. Most items do not have descriptions so it is typically a struggle to select the right items. Enter a nice little hack by Magnus called "autodesc"; it automagically creates descriptions on the fly based on existing statements.

It is one of the most valuable hacks I know off. All it takes to activate it is adding this one line to your common.js page.

• mw.loader.load('//tools.wmflabs.org/wikidata-todo/autodesc.js');

Many hardcore Wikidatians do not yet know about this little tool. Once they find out how useful this is, they will not go back to adding descriptions but they will add the missing statements that identify the items in any language. Like me they will consider this an obvious improvement in the Wikidata user experience.

Thanks,

       GerardM

#Wikidata HOWTO - Add value by labelling what is in the #news

If there is a purpose to Wikidata, then it is to share in the sum of all knowledge. Wikidata provides a service to over 280 languages and if they are all to share in the same sum of all knowledge we have a challenge on our hand.

Take Typhoon Haiyan for instance, A lot of specific information can be given. The date it became recognised as a typhoon and the date when it was no longer a typhoon. The country or countries it passed maybe even maps that show this progression. When everything is said and done, there is the potential for a substantial number of statements and qualifiers.

Obviously there are other items that are still of interest; typhoon, Philippines, United Nations are all related to the aftermath of this typhoon. When we ask attention for the information we can currently provide in Wikidata and for the associated items, we will be better prepared for a next tropical storm.

Only a few are needed to set up the data properly but we need 280 times attention to make sure that people can find our information in all our languages. That attention is our biggest challenge.
Thanks,
      GerardM

#Wikidata #HOWTO - Nelson Mandela

Nelson Mandela was the President of South Africa. Many statements have been made about him on Wikidata in the past. At the Diversity Conference Wikidata was a topic in several conversations. One question was how Wikidata could be leveraged in the many languages of South Africa. In that same conversation the question was asked how can we give people micro-tasks that have a big impact.

I asked the chairman of the South African chapter to add all the labels used on the item for Nelson Mandela in his native language of Tsonga. He did get some instruction but he was left very much to himself to do this. When he had a look at Jacob Zuma, he noticed that because of his earlier work several labels were already available in Tsonga.

What was really clear to him was that adding labels to statements and items are micro-tasks and, that kids can do them. Anyone can do them. Seeing the effects of the work done is really motivating.

As a thank you I wanted to present Nelson Mandela looking good in Tsonga. To do this I had to learn from Magnus how to show the Reasonator in other languages. My choice was to use Chinese as the fall back language. This is just to make obvious that there are still a few labels missing :)
Thanks,
        Gerard Meijssen

#Wikidata #HOWTO - Lilavati, the curious daughter

Lilavati was the daughter of the famous mathematician Bhāskarāchārya. The first part of his book was dedicated to her and from its text the love for his daughter is obvious and the wish for his daughter to follow in his footsteps.

The book Lilavati's Daughters very much celebrates the daughters of India who became scientists. These fine ladies are the subject of an editathon in India. The objective is to write articles in the 20 languages of India that have a Wikipedia or an Incubator projects.

It is not easy to coordinate what work has already been done. By adding the "Lilavatis's daughters" as the subject of the book in Wikidata, it becomes a place that links all the articles for them together. It does not take much time for someone to add the names for these fine ladies in their own language. It does not take much time to have a look at the statements made for them to see how much could be added.

Some of these ladies received awards like the Jnanpith Award and, when you think it is relevant for the whole world to know who won this award, you could add the other price winners as well. When you add statements describing these ladies and their achievements, you create pointers to what could be in the article. When you state that they are a "scientist" and "female", people like Emily will find them and get a growing understanding about the lady scientists that have a Wikipedia article in any language.
Thanks,
      GerardM