To achieve the aims of Web Taxonomy Creation examined in my last post, a collaborative modelling approach is required. The literature on collaborative modelling is extensive. Huhns [1] and Paternò [2] both explain that alternatives to current software development approaches are required for ease of model creation. The need is to translate from a model-based visual representation understood by users to software. This makes it possible to engage with end-users and non-specialists in general. Johnson [3] explains that successful interaction requires mapping between levels of abstractions and that translation between these abstraction levels required by people and computers is difficult. Johnson explains that this problem often means systems are created that make users cope with the problems of mis-translation. The representation of rules and information can be illustrated diagrammatically and it is possible to describe algorithms through concrete examples rather than abstractly. Models must be designed and visualised so that they convey to users a representation of a problem that assists with their vision of it. This modelling approach is explored by Crapo et al [4] and is the basis of our visualisation techniques allowing the creation and understanding of taxonomies and models.
Scaffidi et al [5] show that most people who develop software are de-facto programmers lacking a formal computing background, this will often be the case for scientists and the public contributing to taxonomies. End-user programming is particularly important in this research as we are making software development accessible to non-experts. Research by Ko [6] explains the need for engagement of end-users, including non-specialists by providing them with the capability to interact and amend software. An e-science interactive environment is ideal for involving anyone interested in science to amend or produce personal content. The environment will benefit from an interactive e-learning approach influenced by 'Semantic Learning Webs' [7]. The capabilities we will provide over the web are similar, but more collaborative and advanced than provided by spreadsheets for modelling, and web editors for knowledge sharing. We will produce an alternative methodology for scientific modelling that hides the complexity of low-level programming code from users. This is a kind of meta-design, as explained by Fischer [8] that can be standardised to create a collaborative environment for sharing information among scientists. This builds on research we have undertaken to enable end-user programming. We will visualise scientific information and make this editable online. The system created must be judged accessible and user friendly by users. In addition, it must share information successfully with other software and people. So interoperability is extremely important, examples of interoperability research we will make use of are INTEROP [9] and MOMOCS [10], and combine this with a model driven approach. In order to achieve interoperability, the utilisation of open formats should be favoured in order to maximise chances of forward compatibility with evolving scientific models. We will also create or customise editing tools such as wikis [11][12], blogs, and Semantic Web editors [13] to document the models and collect user's feedback. We will visualise scientific information and make this available online.
Web Taxonomy Creation -
http://userdrivenmodelling.blogspot.com/2008/01/web-taxonomy-creation.html.
References
[1] Huhns M, 2001, Interaction-Oriented Software Development, Journal of Software Engineering and Knowledge Engineering.
[2] Paternò F, 2005, Model-based tools for pervasive usability, Interacting with Computers Vol 17(3), pp 291-315.
[3] Johnson P, 2004, Interactions, Collaborations and breakdowns, ACM International Conference Proceeding Series, 3rd annual conference on Task models and diagrams Vol 86.
[4] Crapo A W, Waisel L B, Wallace W A, Willemain T R, 2002, Visualization and Modelling for Intelligent Systems, Intelligent Systems: Technology and Applications, 1, pp 53-85.
[5] Scaffidi C, Shaw M, Myers B, 2005. Estimating the Numbers of End Users and End User Programmers. IEEE Symposium on Visual Languages and Human-Centric Computing, 21-24 September, Dallas, USA.
[6] Ko A J, 2007. Barriers to Successful End-User Programming. End-User Software Engineering Dagstuhl Seminar.
[7] Stutt A, Motta E, 2004. Semantic Learning Webs. Journal of Interactive Media in Education, 2004(10), Special Issue on the Educational Semantic Web.
[8] Fischer G, 2007. Meta-Design: A Conceptual Framework for End-User Software Engineering. End-User Software Engineering Dagstuhl Seminar.
[9] INTEROP -
http://interop-vlab.eu/newsletter/newsletter-nb02/[10] MOMOCS - MOdel driven MOdernisation of Complex Systems -
http://www.viewzone.org/momocs/index.php?option=com_content&task=blogcategory&id=20&Itemid=17[11] Hale P, 2007. Protégé Wiki
http://protege.cim3.net/cgi-bin/wiki.pl?UserDrivenProgramming[Accessed 29 Nov 2007].
[12] Visual Knowledge, 2007. Semantic Wiki
http://www.visualknowledge.com [Accessed 29 Nov 2007].[13] Quint V, Vatton I, 2005. Towards Active Web Clients. DocEng Bristol United.
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