I have to confess. I don’t like THE Semantic Web.
Not the idea of it. I’m fascinated, intrigued, sceptical, excited, doubtful and very interested in the idea of connecting data in more meaningful ways. I love the potential and pour many hopes into it even as I doubt the reality and slightly fear the possible pitfalls and unintended consequences that may seep out beyond our ability to cope.
It’s the language I can’t quite come to embrace.
For something that is about making things more meaningful The Semantic Web is not an intuitively meaningful moniker for most people. Not like Social Networks. People intuitively understand that people are social and they participate in networks. The hinterland of theory, terminology and “grammar” that makes up social networks and the participatory web, short coded as Web 2.0, is now well hidden from everyday usage.
Ordinary people talk about tweeting, liking, friends, followers, connections, blogging, sharing and reusing. They don’t talk about nodes, degrees, graphs, path lengths, scale free, preferential attachment or clustering.
I think The Semantic Web will also need its own ‘language of ordinary activity’ rather than its current dense conceptual vocabulary for it to cross into mainstream discourse and practice. I need to understand it as a LIS professional, but I also need to be able to explain it to my Partner, my Mum, my friends down the pub and help them see how it fits into their lives.
From Concepts to Embedded Ecosystems: Getting New Things to Succeed
It is difficult to understand why some products succeed and others fail and even harder to predict which will do so in the future. There are several theories that attempt to model pathways to success including the technology acceptance models, Rogers’ innovation diffusion theory and Gartner’s hype cycle.Tom Fishburne. Source: Marketoonist (Free Use for Blogs Licence). Seriously – go read his comics. They’ll make you laugh … and make you think.
During the 1970s and 1980s two competing video cassette recording standards emerged: VHS and Betamax. Betamax was generally accepted to be technically superior but VHS triumphed in mainstream adoption. Jack Schofield explains this by looking at a “whole product approach”.
The point is that when someone buys and uses a product, the technological aspects are a small and often uninteresting part of the decision. When you choose compact cassette, you are also buying into a vast infrastructure of capabilities, services and support. – Jack Schofield (The Guardian)
Innovations take off because societies understand what to do with them. People understand how to do useful or entertaining things with them. Businesses understand how to profit from them. Governments understand how to utilise them for the public good and regulate them to prevent public harm.
For me The Semantic Web has yet to ‘cross the chasm’, some already think it’s dead. It is still too weighed down by its dense frameworks and grammar to fully soar into mainstream thinking and markets. Jargon like taxonomy, ontology, linked data, RDF, OWL, SKOS, SPARQL is necessary for the mechanics of The Semantic Web but obscures an understanding of the possibilities they open up. These standards are hard to learn and even harder to master which could be why the diffusion of the idea remains modest when compared with the growth of the web overall. Even Internet of Things (IoT) and Web of Data (WoD), more user friendly terms, are becoming increasingly fashionable but are diluted by their very vagueness.This presentation by Marin Dimitrov provides a useful overview of some of the issues.
As a LIS geek with an interested in building knowledge architectures these things are incredibly important and the investment in unpacking them is worthwhile. But for mainstream adoption and innovation diffusion the possibilities need to be encapsulated and exposed more succinctly. We need more use cases for and friendlier ways of speaking about The Semantic Web.
In Search of an Alternative Frame of Reference
For example, could we compare knowledge ecosystems to transport ecosystems to distinguish between ‘drivers’, ’designer’s and ‘mechanics’?
Everyone understands the idea of the car and can relate it to concepts like driving, maintenance or safety because we have evolved the categorisation of it into common knowledge. Many people know how to drive having the necessary skills, knowledge of laws and credentials. If a car needs servicing or fixing most people take it to a garage. Most people would also buy a car rather than make one from scratch. Few people have a clue about the mechanical and electronic components that go into making a modern car.
We might not know the (30,000 or so) pieces of car or how the fit together but we know what to do with cars once they are assembled and how to be careful with them. We might talk about facets of cars like make, model and colour they, how fuel efficient or how good they are to drive. Other things we need to know about the wider driving ecosystem are encoded into simplified schema such as vehicle excise duty bands, insurance groups or The Highway Code.
Most people are not designers or mechanics they are drivers or passengers.
Interestingly, it this kind of understanding, meaning making and associate knowledge and encoding that The Semantic Web is all about. How could we code this understanding we humans have about cars and driving and represent on the web in a way that computers would also not only read but also understand?
The Semantic Web is attempting to encode our common knowledge so computers can share it but in order for The Semantic Web to be fully embraced by us humans it needs to decode its technicalities into common knowledge.
The Sensing Web
Rather than The Semantic Web I prefer to think of Web 3.0 as The Sensing Web. It means giving our computer networks better sensory and sense-making abilities.
By The Sensing Web I mean sensing in two ways:
- a sensory web
- a sense making web
This is the ability to monitor, receive, process, organise and store a huge range of stimulus from an external environment. For humans this is our eyes, ears, nose, tongue and skin and the many millions of signals we take in every day that are then processed by our brain and neural networks and either discarded, used or committed to our memory.
For Web 3.0 this is similar to The Internet of Things. A growing network of pervasive sensors that can monitoring anything and everything in our worlds and sending that data via their network connections to vast stores of big data for processing and then discarding, using or being committed to digital memory for further analysis or future recall. This gives rise to a kind of social sensing that goes beyond anything we’ve seen before in terms of the volume, velocity and variety (plus veracity and value) of data points processed. This isn’t necessarily a revolution but does represent another key shift in the history of ‘documents’.
2. Making Sense
Having lots of input in not sufficient for understanding. Many of our brain functions happen automatically for the running of our bodies and subconscious thoughts but much of the data and information we as humans received is processed by the brain via the complex networks of neurons and synapses. This is where we require a semantics to help us turn data into information and information into knowledge.
This could be seen as the difficult work of converting the subjective tacit knowledge within our heads into objective and codified knowledge so it can be shared and communicated more easily (a shift from Popper’s World 2 to World 3).
For Web 3.0 it is The Semantic Web that will provide this architecture of understanding and epistemological basis for computation that will allow machines to more easily and automatically convert data into information and information into knowledge without human intervention or vast resources devoted to mining and wrangling data sources.
I do not know how correct or useful conceptualising Web 3.0 in this way will prove to be as it and my knowledge about it develops; it’s still not an easy thing to digest but for now it is helping me explore, understand and ‘play about with in my head’ the theories, technologies and dynamics of Web 3.0.
Having limbered up with some theoretical context, in my next post on The Semantic Web I’ll take a closer look under the hood and explore some of the principles, concepts, standards and technologies involved and consider some alternatives for arriving at web semantics.