Open data is neither a subset nor a superset of linked data or the Web of Data but the topics clearly overlap.
The vision of the semantic Web and linked data is to create an infrastructure of connectable and exchangeable information sources in the web.
This means that data endpoints are interoperable, even if they never knew about each other, because the technology is independent of a concrete serialization format, query language and structure of the concrete information.
The semantic data technology stack deals with
- mapping different data formats and structure
- querying over a lot of independent data sources
- providing logic (semantic) to infer new knowledge
- developing domain specific vocabularies, meta vocabularies (also referred as ontologies) and concepts
- deal with data validation, data expiration and versioning of volatile data
- making data independent of the tools, that produce or visualize them
- dealing with live data, sensor data, knowledge, archived data,... in a standardized way
this is not a complete list but there have already been various posts that try to line out the coverage of semantic web technologies.
The following graphics show this:
(taken from the-power-of-semantic-technologies-to-explore-linked-open-data)
open vs. private data
In fact linked data can be private and should be private in a lot of areas (think of the semantic desktop, private information management or cooperate data, classified information, user data,...). Ideally private, partially private and open data can be merged or treated in the same way.
If the vision of the semantic web comes into reality sharing of arbitrary information and knowledge, would be as easy as exchanging and sharing files today using Versioning systems or online collaboration software, where users form groups of people and people can share information among those groups and single individuals, but also with virtual actors like organizations, services, data pools,... It is still a long way until all of it reaches a more user friendly way that spreads further from the research labs, enthusiasts and cooperate labs to the public. But until now serious afford has been done by the research community to solve a lot of issues and sub problems that arise from that vision. Standardization is one of the processes, that helps to keep a stable base, where the volatile semantic technology can emerge.
why people should care about the web of data
One important part is to help people to understand how to properly prepare their domain specific data structures, interfaces and algorithms to easily integrate it into the web of data universe. The benefit for all would be, that using and mixing of specific services, data sources and tools
would be much easier and certainly would not need programmers knowledge
or knowledge about vocabulary and ontologies if properly done.
Often it is much easier than a lot of users may think, if they hear all those complicated sounding terms out of the technology stack. In fact you don't need to know much, if at all about reasoning, higher order logic, triples and open world concepts, just to make a former JSON structure or REST service produce JSON-LD or semantically describe the resources it provides.
That is exactly the reason why I would like to see a stable community around all those tools that already exist. The open data-community would be the entry point for all those enthusiasts and experts the seek for an easy to use solution to get their domain specific data or where to put there own if they want to share it. The Web data-community would be the place where people ask about more technically related questions, concerning the whole technology stack, certain database systems, about ontology and vocabulary engineering tools, query languages, data structures, serialization formats, ...
Open Data - high level user perspective
Web Data - implementation, engineering low level perspective
A comparsion to a diffrent topic: