6.3 KiB
Wikidata
Wikidata is a large collaborative project (a sister project of Wikipedia, hosted by Wikimedia Foundation) for creating a huge noncommercial public domain database containing information basically about everything. Well, not literally everything -- there are some rules about what can be included that are similar to those on Wikipedia, e.g. notability (you can't add yourself unless you're notable enough, of course you can't add illegal data etc.). Wikidata records data in a form of so called knowledge graph, i.e. it connects items and their properties with statements such as "Earth:location:inner Solar System", creating a mathematical structure called a graph. The whole database is available to anyone for any purpose without any conditions, under CC0!
Wikidata is wildly useful and greatly overlooked in the shadow of Wikipedia even though it offers a way to easily obtain large, absolutely free and public domain data sets about anything. The database can be queried with specialized languages so one can e.g. get coordinates of all terrorist attacks that happened in certain time period, a list of famous male cats, visualize the tree of biological species, list Jews who run restaurants in Asia or any other crazy thing. Wikidata oftentimes contains extra information that's not present in the Wikipedia article about the item and that's not even quickly found by googling, and the information is sometimes also backed by sources just like on Wikipedia, so it's nice to always check Wikidata when researching anything.
Wikidata was opened on 30 October 2012. The first data that were stored were links between different language versions of Wikipedia articles, later Wikipedia started to use Wikidata to store information to display in infoboxes in articles and so Wikidata grew and eventually became a database of its own. As of 2022 there is a little over 100 million items, over 1 billion statements and over 20000 active users.
Database Structure
The database is a knowledge graph. It stores the following kinds of records:
- entities: Specific "things", concrete or abstract, that exist and are stored in the database. Each one has a unique ID, name (not necessarily unique), description and optional aliases (alternative names).
- items: Objects of the real world, their ID is a number prepended with the letter Q, e.g. dog (Q144), Earth (Q2), idea (QQ131841) or Holocaust (Q2763).
- properties: Attributes that items may possess, their ID is a number prepended with the letter P, e.g. instance of (P31), mass (P2067) or image (P18). Properties may have constraints (created via statements), for example on values they may take.
- statements: Information about items and properties which may possibly link items/properties (entities) with other items/properties. One statement is so called triplet, it contains a subject (item/property), verb (property) and object (value, e.g. item/property, number, string, ...). I.e. a statement is a record of form entity:property:value, for example dog(Q144):subclass of(P279):domestic mammal(Q57814795). Statements may link one property with multiple values (by having multiple statements about an entity with the same property), for example a man may have multiple nationalities etc. Statements may also optionally include qualifiers that further specify details about the statement, for example specifying the source of the data.
The most important properties are probably instance of (P31) and subclass of (P279) which put items into sets/classes and establish subsets/subclasses. The instance of attribute says that the item is an individual manifestation of a certain class (just like in OOP), we can usually substitute is with the word "is", for example Blondi (Q155695, Hitler's dog) is an instance of dog (Q144); note that an item can be an instance of multiple classes at the same time. The subclass of attribute says that a certain class is a subclass of another, e.g. dog (Q144) is a subclass of pet (Q39201) which is further a subclass of domestic animal (Q622852) etc. Also note that an item can be both an instance and a class.
How To
There are many libraries/APIs for wikidata you can use, unlike shitty corporations that guard their data by force wikidata provides data in friendly ways -- you can even download the whole wikidata database in JSON format (about 100 GB).
The easiest way to retrieve just the data you are interested in is probably going to the online query interface (https://query.wikidata.org/), entering a query (in SPARQL language, similar to SQL) and then clicking download data -- you can choose several formats, e.g. JSON, CSV etc. That can then be processed further with whatever language or tool, be it Python, LibreOffice Calc etc.
BEWARE: the query you enter may easily take a long time to execute and time out, you need to write it nicely which for more complex queries may be difficult if you're not familiar with SPARQL. However wikidata offers online tips on optimization of queries and there are many examples right in the online interface which you can just modify to suit you.
Here are some example of possible queries. The following one selects video games of the FPS genre:
SELECT ?item ?itemLabel WHERE
{
?item wdt:P31 wd:Q7889. # item is video game and
?item wdt:P136 wd:Q185029. # item is FPS
# this gets the item label:
SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],en". }
}
LIMIT 100 # limit to 100 results, make the query faster
Another query may be this one: select black holes along with their mass (where known):
SELECT ?item ?itemLabel ?mass WHERE
{
{ ?item wdt:P31 wd:Q589. } # instances of black hole
UNION
{ ?item wdt:P31 ?class. # instance of black hole subclass (e.g. supermassive blackhole, ...)
?class wdt:P279 wd:Q589. }
OPTIONAL { ?item wdt:P2067 ?mass }
SERVICE wikibase:label { bd:serviceParam wikibase:language "[AUTO_LANGUAGE],en". }
}