1. New Directions in e-Science for the Arts and Humanities Stuart Dunn Tobias Blanke Centre for e-Research, King’s College London www.kcl.ac.uk/iss/cerch British Academy, 12th May 2010
8. The idea of synchronicity is that the conceptual relationship of minds, defined as the relationship between ideas, is intricately structured in its own logical way and gives rise to relationships that are not causal in nature. These relationships can manifest themselves as simultaneous occurrences that are meaningfully related. -http://en.wikipedia.org/wiki/Synchronicity Synchonicité
28. Vision: Virtual Data Centre … JDBC/ODBC Client OGSA- DAI HGV - MySQL German-English join table
29. Mapping e-Science to the Digital Humanities Documenting Process Linking datasets Developing new research questions eSAD E-Dance MSpace LAQUAT Purcell VERA S. Dunn, S. Anderson and T. Blanke (forthcoming): ‘Methodological Commons: Arts and Humanities e-Science Fundamentals’. Phil Trans. A, Proceedings of AHM2009.
30. - Technology provides new opportunities to document process E-Science in the A&H - Documentations of process thus produced can become part of the research outcome - How? - Processing data - not necessarily on Grids - Linking data - (probably necessarily) in Clouds
Notes de l'éditeur
This is a simplified architectural diagram showing the set-up for the first case study, with the 2 databases – along with separate databases for annotations to the main ones. This uses the SQL Views – which allows views on a read only database, columns to be renamed and so forth – and the DQP functionality that was described in the earlier session today – in fact you may recognise this diagram, which is very similar to one you saw earlier. This set-up allows the multiple tables in the multiple databases to appear as tables in a single database, and allows researchers to make join and union queries over the tables. ----------------------------- . Can do joins and unions over the tables. SQL views can handle the following requirements: V.1 Expose TEXT date column types as DATE date column types. [Mike: I’m not sure if this is possible using SQL views]. V.2 UNION N tables so they are treated as a single table. H.1 Expose German column and table names as English handling any spaces and German characters. DQP can handle the following requirements: V.3 Expose multi-lingual column contents as English. V.4 Perform text searches over the contents of individual fields. H.2 Expose multi-lingual column contents as English handling any language-specific characters. H.3 Perform text searches over the contents of individual fields. HV.1 Perform a join across both of the databases. Our current design, based on the experiences and issues outlined in LaQuAT Experiments is as follows:
The data resources used in the project are just three examples – there are many small, scattered yet related data resources that would benefit researchers if we linked them up along the lines described above, to form a sort of virtual data centre for researchers, uniting scattered and inaccessible data resources and enabling them to ask questions that they would not have been able to ask otherwise. The whole in this case has the potential to be much more than the some of the parts – the utility of these datasets would increase greatly once a certain critical mass was reached. As an analogy, you might think of a map where each dataset represented a small part – say a few houses within a street. If you integrate a few of them it is of limited use, but after a certain point is reached you will have enough information to navigate your way through the streets.