#Wikidata - my #workflow enriching Wikidata using tools

As I have other commitments, I do not have the same amount of time to do what I used to do. The workflow I use is now quite stable and dependable so I am happy to publish it. It is fairly easy and obvious. You can do this too.

Important are objectives; mine are:

• make Wikidata more informative by adding relevant statements
• Provide the basis for further usage of data

My workflow is based on the people who died in 2014. This is reported in categories. ToolScript informs me about all items that do not have a date of death. Every line represents an item; typically they are human but there are also horses and other critters included. I click the Reasonator icon and, the links to articles provide me with the first lines of that article. Typically the date of birth and death are included. I copy this text when it is not English and use Google translate. From the translated text I copy the dob dod. I click on the Qnumber in the Reasonator and add these dates in Wikidata.

The ToolScript can easily point to 2013 or any other year. Obviously you can make your own script to do whatever.

Once somebody is a registered dead, I look at the article for interesting categories. They can be anything from "Alma mater university x" to "player of Whatever FC". Most interesting are the implied facts NOT reported from the dearly departed. Any category may contain hundreds of other items for whom we are not aware about said fact. The first thing to do is to document said category, this category can be on any wiki. Documenting is done by including a statement with "is a list of" "human" and have a qualifier like "alma mater" "University X". Reasonator will show at most the first 500 entries of the resulting query.

When many entries are still missing, Autolist2 is the tool to use. From the Reasonator page of the category, copy the name of the category, the P and the Q value to the appropriate spot. Do not forget to make sure that the right Wiki has been selected (en in the example). Consider the depth; depth 0 is safest. Make sure that the WDQ mode is on "AND" and press "Run". This will generate the list that is selected for processing. Check the list and copy the P and Q values to the control box. Click "Process commands" when you feel comfortable with the results. Once the process starts, you will find the changes in the Reasonator page for the item you add statements for, in the example of the illustration it is the New Zealand Order of Merit

For best results most entries are often in the "local language" like this example for people who work(ed) at the university of Innsbruck.

With a workflow like this you are more effective. The work is documented and slowly but surely Wikidata becomes truly informative.
Thanks,
     GerardM

#Wikidata - giving a #category an application

Many #Wikimedia categories have interlanguage links. Obviously the content of all these linked categories do not have the same content. Someone has to add the articles, sometimes it gets done and sometimes it doesn't. Often articles just do not exist.

When the facts that are implicit in what a category is about make it to all the items in all the categories, typically you have a superset in Wikidata. It does not stop there; items in Wikidata may be included that are not in any of those linked categories.

This is all theoretical unless ... unless you can query Wikidata and use the results. Much data has been added to Wikidata based on the content of categories and queries have been used to identify missing items this is done using AutoList2. This is one application; it is used by some of the "advanced" users of Wikidata.

What is even more interesting is showing what Wikidata things should be in a category. This is done using Reasonator. At this time for over 690 categories statements are included that define a query. This query is already complex enough that the Wikidata functionality will not be able to express the results..

These queries could be of use to "advanced" Wikipedians because it is a basis for identifying articles that have not been categorised or articles that still need to be written in their Wikipedia. For everyone else it is just interesting; this information exists and it is readily available. It is one way of learning that Wikidata knows for instance about 121,922 politicians.
Thanks,
      GerardM

#Wikidata - many more edits

It is so easy to add a lot of information to Wikidata. Mr Wekwerth died for instance. You read his article and, you find a category indicating that he was awarded the order of Karl Marx. They were 437 edits for me because I added all the people in the category using Autolist2.

There are many more categories on the profile of Mr Wekwerth and arguably each one establishes Mr Wekwerth more in who he was and the people, places and occurrences he was connected to.

Typically I do only one category for one person who died. When that someone was a bishop, I know him to be a priest. They are some 777 edits I am adding at the moment. It could have been a diplomat or Wikidata does not even know that the person is "human"..

Adding an additional 100K edits is not that hard. It does enrich Wikidata and the results are obvious when you regularly wander using the Reasonator or when you add the dates of death to those who died like I do.
Thanks,
    GerardM

#Wikidata - the order of the Red Star

Mr Anatoly Kornukov died. He was a Soviet and Russian general, he was a fighter pilot. His story is quite interesting, it includes that he was in charge of the downing of the Korean Air Lines Flight 007.

Mr Kornukov was highly decorated and, among the awards he received was the "order of the Red Star". It is easy to add it for Mr Kornukov but that leaves out the 9,242 other recipients of this award.

As you can imagine, the category on the Russian Wikipedia for recipients of the order of the Red Star knows the most. It takes a little more effort to have AutoList2 add all the missing recipients.

It takes a while for all of them. You can see how many are already done here.
Thanks,
     GerardM

#Wikidata - Who is Howard N. Potts

Stephanie Kwolek, the inventor of kevlar died. The death of someone notable is often a reason to flesh out the Wikidata item with relevant statements. For Mrs Kwolek none of the awards she received were mentioned.

Once these statements were made for Mrs Kwolek, the available information about those awards was added. The category "National Medal of Technology recipients" contained 125 recipients Wikidata did not know about. The "Lemelson–MIT Prize" was named after Jerome H. Lemelson. Similar information for the "Howard N. Potts Medal" is not available.. Who is Howard N. Potts?

Tools like AutoList2 and Reasonator make it easy to add information and to have the instant gratification of well presented information.

It will be wonderful when WikiData adopts these features in the user interface that is being designed.
Thanks,
      GerardM

Authorising #oAuth in Widar

Tools like AutoList and Reasonator get a boost from their ability to apply changes to Wikidata. Reasonator shows labels in the languages you know and missing labels in your language can be added. AutoList enables you to add multiple statements to items that it shows in a list.

This is powerful stuff. It helps when you understand how it works. Widar is the tool that does handle the authorisation for oAuth. It remembers the authorisation by using cookies. These cookies are associated with your browser. When you use multiple browsers, you have to authorise multiple times.

As Reasonator is used everywhere, people will authorise often. As the cookies persist, it is important to end the authorisation for Widar. The functionality to do so has been added recently.
Thanks,
     GerardM

#Wikidata - the 3th earl of Mayo

Joseph Deane Bourke, 3rd Earl of Mayo has a Wikipedia article. It is largely filled with his genealogy and his ecclesiastic career.

Wikidata used to know him as a "list of" "person". An automated process added "instance of" "human" to Mr Bourke. These two claims are obviously mutually exclusive. Thanks to AutoList it is possible to find the items that have both claims.

At this stage you have to remove the wrong claim one at a time in Wikidata itself. The automated process operated on the presumption that an entry in a category that is named like "1794 deaths" are humans. As can be expected, this is mostly true.
Thanks,
      GerardM

#Export of a #Wikidata #query

AutoList is the tool where you can operate on the results of a query based on Wikidata data.

It is quite magical that you can now actually download a file with Wikidata data. In this example, you find 22 of the more than 3000 people who Wikidata knows to have died in 2014.

Downloading the data is a new feature that was created so that people do not have to copy and paste values to a spreadsheet any more. No more typo's and no more copy errors but best of all it is so convenient.
Thanks,
      GerardM

#Wikidata - its sex ratio

In a perfect world, Wikidata knows the sex for each person where Wikipedia has pertinent information; every Wikipedia. In a perfect world you query Wikidata for the sex ratio of each Wikipedia.

As we know, the world is not perfect; Wikidata currently knows about 1,332,383 "humans"  760,616 are male and 154,455 are female. This makes for 57% males,  12% females and 31% unknowns. Many items still need to be identified as human as well.

With a selection like the 12,800 known Harvard alumni, we find that there are 5,359 males and 840 females. This is 42% male, 7% female and 51% unknown. Before we compiled these numbers missing items were created for each known alumni and all of them were made human and a Harvard alumni as well.

The problem Wikidata faces is not only with the under representation of women, the problem is with the lack of data about the gender of known humans. The nice thing about statistics is that now that we have some numbers, we can track how Wikidata evolves in its information about the sexes.
Thanks,
      GerardM

#Wikidata - the replication to #Labs works again

The #Reasonator uses Wikidata data and to make sure that its data is always close to "up to date", a replication processupdates Reasonator every 10 minutes or so. To do this, it needs a Wikidata dump and, incremental backups are really nice to have. Once the latest available back ups are included, replication will pick the later changes up and, the result can be something like all the members of the Lok Sahha.

The Lok Sabha is the lower chamber of parliament in India. Reasonator showss the first 500 members known in Wikidata and, the rest you can see using AutoList.

Saturday there is a edit-a-thon in India. They will write about the female members of the Lok Sabha. We can make a query for this as well. As labels in the languages of India are added to Wikidata, these parliamentarians will be found when you search for them because all the Wikipedias of India make use of Wikidata extended search.

In this way, we make another step in sharing in the sum of all knowledge.
Thanks,
       GerardM

#Reasonator does lists

What is the point of defining in #Wikidata the "is a list of" property when it does not provide a benefit. So far there was no point. With the latest functionality of the Reasonator, it shows what the list contains based on the definition.

Obviously that is not what the different Wikipedias may have in mind. Typically a list contains of existing articles and the odd red-link. Querying Wikidata will provide you with all items that conform to set criteria... all of them. It is the perfect list when all the items that should be on the list conform.

Obviously, many lists are incomplete because many items have not been populated with statements that make them show up. In the example, the English category "List of Indian film directors" is a great place to start adding the statements "instance of" "human", "occupation" "film director" and "country of citizenship" "India". This is what you can do using the AutoList. It results in what you can see above.

To make the result look pretty, there is FIST, this tool allows you to use the same category to add images that are available on Commons and are used in an image in a single click.

When you are really into a specific subject, these are great tools that help you set up basic information. Friends who know different languages can help open up the information in their language.

When there is no information about specific subjects, Wikidata is your best bet to make it widely available and, Reasonator is what makes it look good.
Thanks,
      GerardM

#Wikidata - The George Polk Awards

It is in the #news that the George Polk Awards have been awarded. So far the English Wikipedia has not caught up to that fact.

None of the other recipients of the award were known in Wikidata. By using the "AutoList" it was easy enough to add them all. Of the three new recipients only two were known to Wikidata. They have also been included as well. Many of the people were not known to be humans and this has been remedied.

Given the wonderful tools that are available, it does not need to take much effort to add a lot of data to Wikidata.
Thanks,
       GerardM

An update to #WDQ, the tool that queries #Wikidata

WDQ is the tool where you define and run queries on the Wikidata data. It is not on official tool, it runs on replicated data in Labs and, it works really well.

While you prepare your query, you will see the number of results and the first 500 results. They are the maximum number of results that Wikidata provides when you request for information through its API.

When the query definition is satisfactory, you could create a "permalink" for future reference. What is new is that you can move on to the "AutoList:". This is where you can page through all the results and select items for special attention.
Thanks,
       GerardM

Women's History Month, #India-2014

On March 8th several edit-a-thons will be held in India to celebrate "International Woman's Day". In preparation a list of women whose articles need to be created or expanded has been created.

When you look at it from a Wikidata perspective, the first thing is do they have an item. When you start from an English perspective, you can search for them using the Reasonator; all of the women mentioned now have an item.

WDQ is a tool that really helps; it allows you to query the number of Indian women in Wikidata. It provides a nice interface where you can construct queries. A constructed claim like (claim[27:668]_AND_claim[21:6581072]) can be used in yet another tool, the AutoList.

The AutoList provides much more informative results and, it has the added advantage that you can work with all the items on the list even when there are more than 500.

Both Reasonator and AutoList are great tools to coordinate multi lingual projects.
Thanks,
      GerardM

Mickaël Larpe - A #bicycle racer from #France

There is nothing more boring than getting only the name of an article when you are roaming in a random manner through #Wikidata. Adding information one at a time may satisfy for a moment but you are unlikely to see the same item again.

Mickaël Larpe was not know as being from France, neither was he known to be male nor a bicycle racer. This information is however implied in the category "Coureur cycliste français" on the French Wikipedia. Thanks to the AutoList and Widar this information is now explicitly known in Wikidata.

You may want to add an image when the Reasonator indicates that there may be one like I did for Mr Larpe.
Thanks,
      GerardM