In this post I am using the context of the Mathematical Knowledge Management 2007 conference to try to construct similarities in the MathML and CML communities and their thought processes. I’ll show this list in my presentation tomorrow – I may not cover all the points. Similarities:
- both are evolving languages – MathML is not “finished” and won’t be for some time.
- smallish part of the main community, often struggling to get the message across.
- absolute belief that computer mechanization is essential and beneficial.
- belief this will happen, but timescales are unclear
- need for a formal, somewhat arbitrary, selection of core components. e.g. geometry has 42 formal concepts; CML has 100 elements. Often pragmatic.
- extension is through dictionaries (OM has ContentDictionaries, CDs; CML has convention-based dictionaries (CML/Golem))
- systems are still evolving and will continue indefinitely. Need versioning and flags.
- Correctness checking (e.g. of publications) is important, but undervalued by the mainstream communities.
- Fragmented support for development. Have to concentrate limited resources to aim in communal direction.
- Would revolutionise publication process but difficult to get mainstream involvement including learned Socs.
- Problems with browsers – how do we transmit rich content? And every browser release things break.
- Legacy – can we extract useful info from Bitmaps? PDF? LaTeX/ChemDraw
- Commercial organizations are often apathetic or even antagonistic
- Virtual communities can flourish. Openness is critical
- Both have a strong bottom-up approach. MathML has enough pragmatists to make it work in practice.
- both are needed by other disciplines – sometimes the support comes from them rather than the mainstream.
Some differences:
- Maths is relatively poor – although there are commercial companies providing tools and services.
- Maths sometimes produces proof of concept without later sustainability.
- Maths believes in standards. Chemistry doesn’t (yet).
Possible joint activities:file:///D:/wwmm/presentations/standalone/resources/golem/indexFrame.html
- workshop on combined infrastructure of MLs, tools, examples
- joint projects (inc. students presented with “toy” systems)
- synergy in developing tools (esp. client side)
- blogs etc. aimed at joint activities.
- minimal level of infrastructure for OM CML interoperability. Converters? libraries? stylesheets?
- rich client
I’ve gone over these with Michael Kohlhase and we roughly agree on them.