Digital Humanities, e-Science, Research Objects, OAI-ORE
by Niels-Oliver Walkowski
on the 11. November 2011, 10:07 o'clock
As pointed out in the short introduction to this blog some weeks ago the blog will be the core of a demonstrator to an evaluation and adaption of what I call the Aggregating Research Representation approach for the so called Arts and Humanities. Not invented by the OAI-ORE 1 model but increasingly promoted by it the idea to extend the entities of publication within science led to different realizations of what van de Sompel describes as Compound Information Objects 2. The goal is not only to publish an article in the end of a research process summarizing the results but additionally the whole package of material and information which supported this research process like Data, Algorithms, Stuff Information and so on. There are two main ideological patterns by which these ideas are driven: a) to guarantee transparency of research in the way that people can follow up and question the process behind a conclusion presented in a text. b) to offer the possibility of reuse in the way that other people can transfer parts of others work to their own research context without the need to start from the scratch. Therefor the concept of Aggregating Research Representations is strongly linked to the e-Sciene theme and an epistemological leitmotif introduced by Microsoft as the fourth paradigm 3 of research and generally denominated as data-driven-science.
Until today most implementations of Aggregating Research Representations represent research of the sciences. There is the myExperiment example 4 which curates Aggregating Research Representations mainly produced by scientists of Life Science, Bioinformatics and Chemistry, there is the Open Notebook or Open Laboratory Book 5 approach heavily linked to the chemistry community, there is the Compound Information Object example mentioned before introduced by van de Sompel with Embedded Networked Sensing research data and there is the Enhanced Publications model 6 of the EU funded project DRIVER applying its model to natural sciences from different areas and to other statistical oriented disciplines like quantitative social sciences and linguistics.
This list is only a short introduction but the main point why I enlisted it is obvious. It raises the question if and to which extent the idea of Aggregating Research Representations can be transferred and applied to arts and humanities research. This question by which my PhD project begins is situated in different playing fields. First it has a political dimension thinking of what Bruno Latour is eager to call the Science Wars 7. Speaking of constructivistic vs. positivistic epistemology this “battle” is often used in political conflicts between humanities and sciences research. Giving the point of Latour that this battle is grounded in an epistemical missunderstanding and that constructivism and positivism are only two different perspectives on the same research process we nevertheless must admit that these two perspectives play a different role in humanities and in sciences and that former has to justify its existence and viability in research and science policy on a different level. This has consequences on the one hand for the funding of humanities research which has no comparison to natural sciences funding and which becomes increasingly attached to unholy conditions 8. On the other hand and even more important for the question of my PhD is the consequence that humanities researchers are under continuous pressure by the e-Science community to be more collaborative, to finally adapt a culture of sharing, to leave their literally dark room of solipsism and to embrace the new digital possibilities. One could argue that this is the reason why there grew a loosely connected community called Digital Humanities: to support the adaption of digital environments to humanists needs and to create digital practices specific to humanities research. But one shouldn’t forget that the Science Wars mentioned before has its battle lines not only between disciplines but also within disciplines or in other words that there is not such thing called arts and humanities as referred to by the Digital Humanities. And in fact the strong players in the Digital Humanities are disciplines like Linguistics, Empirical Literacy and so on. On the other hand David Berry records that: In the digital humanities, cultural criticism-in both its interpretive and advocacy modes-has been noticeably absent by comparison with the mainstream humanities. The same applies to the Aggregating Research Representations discussion as the given list only show examples of empirical oriented humanities research.
Sally Wyatt once said that analyzing the so called Non-Adapters of a media or an invention is a good method to uncover the limitations of this invention by itself often forgotten in the euphoria of its appearance 9. In fact humanities researchers often have well developed reasons why they refuse to make use of digital tools and possibilities. It’s revealing that researchers of e-Science normally don’t ask what are existing practices of sharing and collaboration in the humanities or under which conditions it make sense for humanists to collaborate, where do they do so, under which conditions results of humanities research are sharable, what is the epistemic of Opennes and so on but just demand that humanists have to change their research culture. Doing this will reveal new ways of engaging into the digital for the humanities. Consequently Digital Humanities is not only about bringing the Humanities into the pre-existing digital world. There is no digital nativity as pointed out by a lately published study 10. One always has to arbitrate between the digital and the non-digital and within the digital itself to gain a digital identity. Hence Digital Humanities is also about relations and frontiers between the digital and the non-digital. To aim in this direction a reflection of e-Science and its paradigms has to include methods and epistemics used within humanities itself. An issue which is not self-evident when looking at Berrie’s observation. Therefor my research will involve a cultural-science-based reflection of networks as culture techniques and an epistemological critique to the extent and nature of use of data in what is called data-driven-science.
There are several reasons why an investigation of Aggregating Research Representations is a research object of preference. As underlined in this post such Representations have not only grown on the theoretical background of e-Science but modelers of Aggregating Research Representations formulate their implementations as a contribution to this discourse. Additionally they are progressively implemented in an Linked Open Data environment which seems to be the most convincing architecture so far representing the idea of Opennes, Sharing and Collaboration. Finally to connect these issues to Aggregating Research Representations – and not to remain standing in a pure e-Science perspective – offers the possibility to transfer some of the results into an operational level. Although following former argumentation it has to be pointed out that results won’t only effect the design of Aggregating Research Representations but its integration into (e-)research in general. By doing so I want to apply my idea of Digital Humanities as reflexive coding between media theory, cultural-science, epistemology etc. and informatics, information sciences etc. where reflexivity means to code not only to achieve an objective but also to make an object out of the code at the same time. This is how we get to a setting which is typical for humanities research and which enroll its activity between the object in its positive objectivity and the priority of the object as Adorno would describe it 11.
2Carl Lagoze and Herbert Van de Sompel, ‘Compound Information Objects: The OAIORE Perspective’, (Open Archive Initiative, 2007) <http://www.openarchives.org/ore/documents/CompoundObjects-200705.html> [accessed 23 July 2011].
3A.J.G. Hey, S. Tansley and K.M. Tolle, The Fourth Paradigm: Data-intensive Scientific Discovery (Microsoft Research Redmond, WA, 2009) <http://iw.fh-potsdam.de/fileadmin/FB5/Dokumente/forschung/tagungen/i-science/TonyHey_-__eScience_Potsdam__Mar2010____complete_.pdf> [accessed 23 May 2011].
5Jean-Claude Bradley and Kevin Owens, ‘Chemistry Crowdsourcing and Open Notebook Science’, in Nature Precedings, 2008 <doi:10.1038/npre.2008.1505.1>.
6Barbara Sierman, Birgit Schmidt and Jens Ludwig, Enhanced Publications?: Linking Publications and Research Data in Digital Repositories (Amsterdam: Amsterdam University Press, 2009), p. 212 <http://dare.uva.nl/document/150723>.
7Bruno Latour, Die Hoffnung Der Pandora: Untersuchungen Zur Wirklichkeit Der Wissenschaft (Suhrkamp Verlag; Auflage: 3, 2002).
8Daniel Boffey, ‘Academic Fury over Order to Study the Big Society’, The Observer, 27 March 2011 <http://www.guardian.co.uk/education/2011/mar/27/academic-study-big-society> [accessed 4 November 2011].
9S Wyatt, ‘Challenging the Digital Imperative’, Development (Maastricht: Maastricht University, 2008) <http://www.narcis.nl/publication/RecordID/oai:dare:16649/Language/en> [accessed 8 July 2011].
10Nishant Shah, ‘In Search of the Other: Decoding Digital Natives’, DMLcentral, 2011 <http://dmlcentral.net/blog/nishant-shah/search-other-decoding-digital-natives> [accessed 4 November 2011].
11Theodor Wiesengrund Adorno, Negative Dialectics, 2nd edn (London, New York: Continuum, 1981).