The words open and link have ultimately brought something huge upon us!

In my twitter stream with Richard MacManus, recently read in his post titled It’s all semantics, I pointed out  that the difference between open data and linked data is in the Web of Data paradygm.

Richard submits a new post: Open Thread: What would you build with a Web of Data.

Ops, forgive me, Richard for using the title Web of Data: what I would build, which is nearly the same of your latest post!

Here are my ideas.
1. Health care.

The Linked Data approach holds much potential for enabling  connectivity between data silos, I mean drug and clinical trials related data sources, thereby enabling pharmaceutical companies to meet the urgent needs in society for more tailored health care.
The amount of publicly available data that is relevant for drug discovery has grown significantly over recent years, and now  the present tools are no longer effective. Scientists need new more efficient ways to interrogate data than simply jumping from one public data source to another. This is because  scientists, let alone mastering the different user interfaces, have  too many disparate data sources to conceptualize there relationships. Further, the prevalence of single query input fields makes it difficult for scientists to retrieve precise information of interest, and to retrieve data that spans different data sources. Linked Data give the  access to these data for scientists and managers by making the connections between the data sets explicit in the form of data links. This can be through the development of algorithms for discovering the links between data sets, usage of RDF as a standardized data representation format and  HTTP as a standardized access mechanism. Such explicit links allow scientists to navigate between data sets and discover connections they might not have been aware of previously. The standardized representation and access mechanisms allow generic tools, such as Semantic Web browsers and search engines, to be employed to access and process the data. The Linking Open Drug Data (LODD) task within the W3C’s Semantic Web for Health Care and Life Sciences Interest Group1 gathered a list of data sets that include information about drugs, and then determined how the publicly available data sets could be linked together. It would be interesting to incorporate data relating to epidemiology, as that could provide information relating to geographical areas (thinking of geolinkeddata) in which diseases are prevalent, and where there is a strong need for the development of a drug that meets the needs of a specific population. Pharmaceutical companies need to make decisions based upon both internal and external data, it is therefore important that companies begin to make internal data available in a linked representation, easily connect those ones with external data.

2. Education.

I want consider three areas of impact for Education: knowledge construction, personal learning network maintenance, and personal educational administration.

Knowledge Construction. If a student have to research a topic, like  pollution, he might begin by searching Wikipedia, but inevitably  he turns to searching the vast information storehouses of the entire web using… Google (!).  Googling the term “pollution” returns a gazillion hits, many of which link to complex data resources that link to other resources and so on. Unless the topic is very important to him, he won’t explore much beyond the first 10 hits returned in a Google search. The presumption of knowledge in this approach to information gathering and evaluation is faulty, if not potentially dangerous in its limitations.
The Web of Data includes a search feature that would return a multimedia report, from many sources, rather than a list of hits. The report include websites, information stored on cell phones, gaming scenarios played out in virtual realities, articles from scientific repositories, chapters in textbooks, blog dialogue, speeches posted on YouTube. And  knowledge areas’ll emerge naturally from the research, with keywords identified and listed conveniently off to one side as links.
The information in the report would be compared, contrasted, and collated in a basic way, presenting points of agreement and disagreement associating these with political positions or contrasting research. Web of Data alerts the researcher to local lectures on related topics, books he might want to read, TV programs available through his cable service, blog relevant discussions and so on. The net result is that we spend less time searching and sifting and more time absorbing, thinking, and participating.

Personal Learning Network. Each one of us sits at the hub of a personal learning network (PLN) that connects us to our interests.  Under Web of Data PLNs are built primarily around subjects, not services. Personal learning agents identify relevant information from any source that is semantically accessible and provide an information synthesis tailored to our personal learning objective. The objective is to spend less time searching for information and more time trying to understand, critically assess, and creatively expand it.
Educational institutions tend to be stand-alone entities that don’t facilitate working with each other. Crafting a multi-institutional education from a student perspective would still be logistically very difficult because schools and other education providers for the most part do not share common languages in describing course or degree requirements.
Web of Data could  challenge this kind of institution-centeredness in the same way that distance learning technologies challenged place-centric education. Institutions will describe courses and degrees semantically, making many of the components of education at least somewhat comparable across institutions. Let me point out that students could be  able to identify comparable coursework and experiences from several educational providers and, in the process, even meet the graduation requirements of yet another.

3. Public consultation in Open Government.

If citizens have a single point of access for all central government consultations, they are able to find out about and engage with Government. Adding RDF data to consultation descriptions means the information will be picked up automatically by that single point and means  all existing web published consultations should be searchable through it.