This chapter shows some SPARQL queries that can be handy with a wide variety of datasets. Many of these queries will work with just about any set of triples out there, including those which you know nothing about. These queries are especially useful in those situations, helping you to learn more about exactly what you have to work with when exploring a new set of data.
In this chapter, we’ll learn about:
SPARQL offers a few simple features, covered earlier in this book, that you can use to enhance most of this chapter’s queries. This section reviews them.
This section has queries to see what you’ve got in a particular dataset—for example, how much structure has been defined there, how much of that structure is used, and, if there isn’t much structure, how you can still get a feel for what kind of data is there.
Some changes to a dataset would be tedious to make by hand and very simple with the right UPDATE query, especially when you need to perform various kinds of global replacements.
The queries shown in this chapter fall into several themes, and there are several variations than can apply to many of them. For example, sorting your output by the values in one or more columns of query output can make it easier to see patterns, especially if you get a lot of results; see Sorting Data for details of how to use the ORDER BY phrase. You’ll see it used here and there in this chapter when the sample ...