I have this database, currently everything is stored within basic Excel tables (yes quite boring). But it works. The type of data I have is numerical. These are measurements people have done to plants in the field - so the values of the cells are pretty much always going to be numbers.
The columns of this excel can be anything: plant height, root position or root surface texture. Again the values are all numbers, so the data would look something like this (CSV):
My first initial thought, as a passionate Semantic beginner, was to use Semantic practices, well, to link with other data and therefore make our data more discoverable. But, I'm having issues telling my boss (and others in my team), the benefits of this.
What is, in your opinion, the best way to showcase the benefits of Semantics, from a business/non-technical point of view? All my boss cares about, is making things easier for the user, therefore the user-experience. Whenever I talk to him about RDF, triples or common-schema he gets confused. So I need to showcase a positive scenario for the end-user.
asked 20 Feb '13, 04:44
Hi, some of the benefits of data with explicit semantics are:
# Easier integration & interoperability.
Suppose in other data you may have "height" as the attribute name, meaning the same as "plant height". Unfortunately, your machines could not really understand if they actually have the same meaning. But, with Semantic Web, you may model: "height" equivalentProperty "plant height", in a machine-readable schema such that computers will figure out if they are representing the same thing. Also, the alignment between Semantic Web data is quite easy in Semantic Web since you just have to care in the schema level, not in the data level.
# Explicit modeling
With Semantic Web, it is easy for people to understand the structure of the data. Say, if I want to know what these specific concepts and properties mean, I can just look at the ontology to see the relationships among them.
# Inference computation
Yes, Semantic Web can think. Say, if we tell/declare that a plant can be no more than 25 of height but our data contains a plant with 30 of height, then the system will detect this inconsistency.