One of the real problems that pervades all routes to Linked Data value prop. incomprehension stems from the layering of its value pyramid; especially when communicating with -initially detached- end-users.
Note to Web Programmers: Linked Data is about Data (Wine) and not about Code (Fish). Thus, it isn't a "programmer only zone", far from it. More than anything else, its inherently inclusive and spreads its participation net widely across: Data Architects, Data Integrators, Power Users, Knowledge Workers, Information Workers, Data Analysts, etc.. Basically, everyone that can "click on a link" is invited to this particular party; remember, it is about "Linked Data" not "Linked Code", after all. :-)
Problematic Value Pyramid Layering
Here is an example of a Linked Data value pyramid that I am stumbling across --with some frequency-- these days (note: 1 being the pyramid apex):
Basically, Linked Data deployment (assigning de-referencable HTTP URIs to DBMS records, their attributes, and attribute values [optionally] ) is occurring last. Even worse, this happens in the context of Linked Open Data oriented endeavors, resulting in nothing but confusion or inadvertent perpetuation of the overarching pragmatically challenged "Semantic Web" stereotype.
As you can imagine, hitting SPARQL as your introduction to Linked Data is akin to hitting SQL as your introduction to Relational Database Technology, neither is an elevator-style value prop. relay mechanism.
In the relational realm, killer demos always started with desktop productivity tools (spreadsheets, report-writers, SQL QBE tools etc.) accessing, relational data sources en route to unveiling the "Productivity" and "Agility" value prop. that such binding delivered i.e., the desktop application (clients) and the databases (servers) are distinct, but operating in a mutually beneficial manner to all, courtesy of a data access standards such as ODBC (Open Database Connectivity).
In the Linked Data realm, learning to embrace and extend best practices from the relational dbms realm remains a challenge, a lot of this has to do with hangovers from a misguided perception that RDF databases will somehow completely replace RDBMS engines, rather than compliment them. Thus, you have a counter productive variant of NIH (Not Invented Here) in play, taking us to the dreaded realm of: Break the Pot and You Own It (exemplified by the 11+ year Semantic Web Project comprehension and appreciation odyssey).
From my vantage point, here is how I believe the Linked Data value pyramid should be layered, especially when communicating the essential value prop.:
- HTTP URLs -- LINKs to documents (Reports) that users already appreciate, across the public Web and/or Intranets
- HTTP URIs -- typically not visually distinguishable from the URLs, so use the Data exposed by de-referencing a URL to show how each Data Item (Entity or Object) is uniquely identified by a Generic HTTP URI, and how clicking on the said URIs leads to more structured metadata bearing documents available in a variety of data representation formats, thereby enabling flexible data presentation (e.g., smarter HTML pages)
- SPARQL -- when a user appreciates the data representation and presentation dexterity of a Generic HTTP URI, they will be more inclined to drill down an additional layer to unravel how HTTP URIs mechanically deliver such flexibility
- RDF Data Stores -- at this stage the user is now interested data sources behind the Generic HTTP URIs, courtesy of natural desire to tweak the data presented in the report; thus, you now have an engaged user ready to absorb the "How Generic HTTP URIs Pull This Off" message
- RDF Data Sets -- while attempting to make or tweak HTTP URIs, users become curious about the actual data loaded into the RDF Data Store, which is where data sets used to create powerful Lookup Data Spaces (e.g., DBpedia) come into play such as those from the LOD constellation as exemplified by DBpedia (extractions from Wikipedia).