Beyond the Triple Count by Leigh Dodds.
From the post:
I’ve felt for a while now that the Linked Data community has an unhealthy fascination on triple counts, i.e. on the size of individual datasets.
This was quite natural in the boot-strapping phase of Linked Data in which we were primarily focused on communicating how much data was being gathered. But we’re now beyond that phase and need to start considering a more nuanced discussion around published data.
If you’re a triple store vendor then you definitely want to talk about the volume of data your store can hold. After all, potential users or customers are going to be very interested in how much data could be indexed in your product. Even so, no-one seriously takes a headline figure at face value. As users we’re much more interested in a variety of other factors. For example how long does it take to load my data? Or, how well does a store perform with my usage profile, taking into account my hardware investment? Etc. This is why we have benchmarks, so we can take into account additional factors and more easily compare stores across different environments.
But there’s not nearly enough attention paid to other factors when evaluating a dataset. A triple count alone tells us nothing. They’re not even a good indicator of the number of useful “facts” in a dataset.
Watch Leigh’s presentation (embedded with his post) and read the post.
I think his final paragraph sets the goal for a wide variety of approaches, however we might disagree about how to best get there!
Very much worth your time to read and ponder.