Astronomy, Semantics and Linked Data
So why, you might ask, am I - an Astrophysicist - interested in semantics,
specifically the semantic web
and linked data. Am I not just
buying into the
AI hype of the 80s,
repurposed for the 21st century? It’s quite possible, but if we ignore some of
the more extreme claims made about this approach,
there is already
plenty that we can do to help us in our work,
as shown by the Virtual Solar and Terrestial Observatory.
I encourage you to read
Jim Hendler’s Nature Network blog article
What is the Semantic Web really all about?,
for an overview of this area.
An obvious place to start is the literature since we are fortunate to have
two major portals for accessing this data online -
pre-prints at arXiv.org
and published material at ADS - which are
already inter-linked and provide a wealth of data that we can take advantage
of. There are a number of interesting developments in this space - some more
“semanticy” than others - including (but not limited to)
arxivsorter - and then there’s work that
I am involved in, funded by the
US VAO project, to combine literature and data
into a bowl of semantic goodness at the ADS. I’ll leave further discussions
on this to
a later post, since what I really wanted to talk about was Outreach.
I have been convinced for several years now that Semantic technologies can,
and should, be used to improve access to Education and Outreach
efforts in Astronomy and Astrophysics. The application of simple
such as the
Ontology of Astronomical Object Types
to data collections including
Astronomy Picture Of the Day,
astronomical images on flickr,
images from the Las Cumbres Observatory Global Telescope Network
and the press releases from observatories like
can, I believe, enhance the reader’s understanding and enjoyment of the material,
as well as providing more avenues for enquiry and understanding.
In my spare time I’ve
explored several avenues - such as
semantic tagging with Astro MOAT -
and have grand visions, but have yet to get anything really working.
A case study
One of the first examples in this area (that I know of), has been provided
by Stuart Lowe,
who combined observational data from the Las Cumbres Observatory telescope network with the
education data provided by the UK Government
to look at where the users of the telescopes are,
at least for schools in England and Wales.
For this particular example I’m sure Stuart would have found it easier just to be
able to access simple tabular data sets2
rather than learn a whole new technology
stack3. In fact, I think this is often true
of many “simple” semantic applications; there’s always a simpler approach if you
already understand the format and layout of the data you are given. The reason for
using these semantic technologies is when you do not know, ahead of time,
exactly what you want or how the data is stored4.
In this regard I see Semantics as being synonymous with
“Data Integration and Exploration”, but I don’t really see this particular
Three-Letter Acronym becoming very popular.
I have been noodling around trying to use the vocabularies we are writing
for the ADS project - in particular those dealing with observational data - to
try and model the LCOGTN data such as
this observation of
Shoeburyness High School.
This work has fallen by the way side, so I’m hoping to write up my steps
following the approach of
Keith ALexander’s LOD by hand,
as a way of re-starting the work.
If I do, you’ll be the first to know :-)