Re: How to use LOD for practical purposes?

I would say it depends on what you are trying to achieve.  Rather than focusing on data, I find it preferable to focus on services with a federated open market of suppliers and consumers of services.  A service can combine different sources of information including data from sensors, and control of actuators (see the web of things). Its output can be data for other services to consume or a user interface e.g. a web page.

Services can be implemented as scripts that follow the links in the graphs and map between different vocabularies as needed. Of course the details depend on the amount of data to be processed, whether a simple script is sufficient, or whether you need massively scalable distributed processing for really Big data. Another distinction is between processing static information and processing streams of dynamic information, or some combination of the two.

> On 19 Nov 2018, at 10:28, Laura Morales <lauretas@mail.com> wrote:
> 
> As a newcomer to LOD, I find using LOD very very very confusing and impractical. To be clear, I think that by now I understand the model pretty well; the theory behind it. My problem is that most *practical* uses of LOD have been a really bad experience, in particular when linking different data sources coming from different places. It's pretty easy to reason about a single graph, that is a consistent graph that was built in one piece, since everywhere around the graph the structure is usually fairly constant and predictable. But when I want to get information from two or more linked graphs... oh boy... they can be using different types, different ontologies for the same thing (or even custom ones!), different ways of linking, different conventions, ... As a human, I can more or less navigate through the graphs: I start somewhere and I follow the links, and I find something that makes sense to me. But I can't see a computer doing this kind of work; it's a hard problem that has got to require some kind of intelligence.
> So my question really is: what am I, the user, supposed to do to get information out of linked graphs? I download 2, 3, o 4 graphs from various sources, then what? Am I supposed to make my own graph by inferring/reasoning/extracting data from those sources in order to make them more reasonable? In a perfect world all those graphs would be all perfectly linked and plug-and-play but this clearly is not how people publish their data. Or is there a magical way to make all this information *practical* to use, something that a computer can use without requiring an ultimate AI?
> 

Dave Raggett <dsr@w3.org> http://www.w3.org/People/Raggett
W3C Data Activity Lead & W3C champion for the Web of things