Change & Permanence – a Walk around Science 2.0
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Transcript of Change & Permanence – a Walk around Science 2.0
8/13/2019 Change & Permanence – a Walk around Science 2.0
http://slidepdf.com/reader/full/change-permanence-a-walk-around-science-20 1/5
paintitscience.com http://paintitscience.com/change-permanence/
Source: Paul Harris (1996) HYPER-LEX: A Technographical Dictionary.
Change & Permanence
Change & Pe rmanence – a Walk around Science 2.0
by Lucas Frede rik Garske
Lucas Frederik Garske is a research asso ciate and member of the “digital humanities and educationial
media research” cluster at the Georg-Eckert- Inst itute f or International Textboo k Research. He blogs on
paintitscience.com.
Disclaimer: This blog wasn´t designed fo r long texts . If you f ind it hard to read the article on this template
there is a small “print f riendly” button at t he bottom of the article that should make it easier f or you to read
(unf ortunately the print f riendly version doesn´t support f oo tnotes).
Credits to Tom for cleaning the mess up.
0. From Web 2.0 to Science 2.0
8/13/2019 Change & Permanence – a Walk around Science 2.0
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Talking about Science 2.0 is much more than adopting a f ancy and successf ul concept: What we are f aced
with is a change of communication in which the web plays an important and decisive ro le. The internet has
always been more telephone than radio, more exchange than inf ormation. The change on the web we
commonly refer to as Web 2.0 is specif ically concerned with interaction and collaboration. As science is
embedded in communication processes, it is part of this change. Obviously it wouldn’t make much sense to
talk about collaborat ive or interactive science, as science has always been based on tools and
infrastructure that imply interaction and communication (paragraph I). While it seems easy to address
ongoing changes, it’s worth ref lecting not only on flow but also permanence of current developments
(paragraph II). I will argue that instead of claiming paradigm change based on t echnology we should rather
demystify our t erminology and f ocus on t he cont inuity we are f acing in 2.0 culture (paragraph III). I
propose to describe the most relevant change in science as a shift from invent ion towards perpetual β-
Science as elaborated in paragraph IV.
I. Changing conditions: tools & infrastructure
Science is an activity that takes place. The underlying metaphor of spat iality was highlighted by Karl
Schlögel f or the case of histo ry. 1 However, let’s start to reconsider science in a broader sense by
ref lecting on the conditions under which science is done.
For so me fo rms of science you don’t need much more t han a piece of paper, a pen and some time. For
other science you need a particle accelerato r or a giant server farm. Dif f erent too ls imply and allow f or
dif f erent types of science. In order to trace back conditionality in science it seems usef ul to s tart with the
development of to ols rather than with abstract thoughts on scientif ic paradigms or attitudes.
Let’s think of tools as resources that help us do whatever we do when we say we do science . 2 A
to ol does not have to be a material thing, it can equally be an inspiring discusss ion, a usef ul theory or a set
of good conditions at your work place. On the other hand, material things play an important ro le as well:
think of certain IT equipment, a specialist library right o n one’s doors tep or simply the money to f inance
your research. The use of to ols was and st ill is st rongly related to spatiality, however, not in the sense of
distance but rather in the sense of infrastructure and communication. 3 Inf rastructure can be considered as
a workshop that provides us with the neccesary too ls to take our research to a dif f erent level. 4 Yet, since
not everyone has access to every workshop, we must shed some light on the accessability of tools and
infrastructure. Mos t o bviously, access to tools is rest ricted legally and economically, but it is also
inf luenced by certain research st andards and traditions. 5
A tradit ion of “stable” ref erences , has excluded and is st ill excluding a great part of “dynamic” scientif ic
activity generated on the web. Inf ormation and sources seem much harder to contro l and archive and they
appear less credible in terms of content and authorship (especially Wikipedia, the nightmare of many
teachers and scholars). For a long t ime, blog entries and online discussions were neglected in “serious”
scientif ic discourse. This is mirrored by the f act that only recently the quotation of electronic sources,especially blogs and podcasts, was addressed by well-respected style guides like the MLA Style Manual
(2008) or the Chicago Manual of Style (2010). The work of major platf orms like scienceblogs, hypotheses
or SciLogs cont ributed to the reputat ion o f “web science”. On the o ther hand, certain web phenomena and
practices have helped highlight the f ragility and instability o f traditional research, with users harnessing
so f tware and collaborative platf orms to detect plagiarism. We can also observe how new projects are
working creatively on the lack of contro l and assessment o f information in digital media. Hypothes.is to me
is one of the mos t interest ing and ambitious projects in this context.
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However, most restrictions imposed by tradition are much less sophisticated and simply based on a lack of
practice. The fact that tools are t echnically ABLE TO make things easier, more e ff icient or more
sustainable does not mean that they will eff ect ively do so. Rather than adopting and learning how to
use new tools, users need to discover and appreciate them f irst. Without an intrinsic need f or change,
the discovery of new potential stays with online pioneers (nerds?) willing to take risk – that is, to invest
time. This includes t ime to get comfort able with live collaboraton in documents (Google Docs, Zo ho), new
correspondence technology (instant messaging, Videoconf erencing, Wave/Rizzoma) o r new techniques of
data treatment (Data Mining, Visualization, Coding).
II. Has anything changed?
But how prof ound is the change f rom Science 1.0 to Science 2.0? I will use the example of hypertext to
argue that in most cases the term Web 2.0 bottles old wine in new wineskins. While this might sound
provocat ively negative it can also be interpreted positively as a discovery of old t reasures. Innovation is
of ten f lawed or challenged by the theory that t here are no pro f oundly new ideas, but merely translations,
remixes, revamps.
I remember one of my project members commenting that o ne shouldn’t be too o ptimistic about the
acceptance of Web 2.0 f eatures in science. He argued that in the late 90s there was a big fuss about
hypertext and everyone predicted that in the f uture there will only be hypertext, which – in his opinion –
turned out to be a rash statement. One can argue that the prediction was in fact wrong, however, f or a
dif f erent reason: Even though stro ngly connected to infrastructures like Wikipedia, hypertext can be traced
back to the f irst uses o f reference systems like indices, quotations o r f oo tnotes centuries ago. So in f act,
long bef ore hyperlinks and Wikipedia became part of our vocabulary, science was s trongly based o n
hypertextual s tructures. 6 In particular, the f act that researchers usually refer to other researchers in the
middle of their work contradicts the assert ion that scientif ic texts are usualy organized in a strictly linear
and categorical way.
Of course, ref erences and feedback on the web work much f aster and discussions have a structure that
allow f or f lexible responses. What changed are certain habits we integrated into the way we arecommunicating. Iconic and deictic use o f language on the web have become more popular and common.
Obviously, we are dealing with a new technology. However, rather than enabeling us to do things dif f erently,
new technology makes us look at old practices f rom a new perspective. As Manuel Lima pointed out on his
speech at the Royal Society of Arts (with amazing visual support f rom Andrew Park), we are currently
undergoing a shif t f rom categorical thinking towards thinking in networks. Beyond statements and causes
we are becoming more inteterested in connections and relations. Network-based scientif ic communities and
scientif ic blogging may be seen as a practical implementation of how we do science dif f erently – but they
are merely a translation of practices we had before (e.g. publishing an article in a journal & discussing the
issue o n a conf erence). In the end, the medium is t he message and new media do not subst itute o lder
ones: A letter is not an email and an email is not a text message – you f eel it as you write it. But you speedup communication a lot when the channel is less important and you can f ocus o n content.
The f act that new technologies most likely won’t create anything essentially new doesn’t mean they aren’t
wort h playing around with. Quite the cont rary, by experimenting with new media we continuously update
scientif ic language. This may raise quest ions t hat can only be answered with those new too ls. That alone,
of course, does not imply that t he results are generally better or more precise, but they might be potentially
more suitable to present problems.
III. The Scientist as Songwriter vs. the Scientist as DJ
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Let’s come back to the idea that scientists use and produce inst ruments to do their work and that those
tools are resources that help us do whatever we do when we say we do science . This means that
everything and everyone can become a tool f or science and if we’re lucky we or o ur work becomes a to ol in
someone elses work. This makes science an ongoing process of working with and working on t oo ls. We
can’t help falling back to science done by others in the past, we are standing on the shoulders o f giants .
But there is a problem with the idiom: While it makes things way easier to think of the history o f science as
the histo ry of great men and great inventions we tend to f orget about the simple fact that things come
hardly out o f nowhere (at least – as a physicist might not e – in mos t cases) and that t he concept of
autho rship might be reasonable in a practical sense (reference & archive), but in the end it is implausible if
the work is not o nly(!) done by individuals but in f act by many individuals. Sticking with the image of giants,
we would probably agree with the image of the Leviathan depicted on T homas Hobbes’ famous tit le – a
giant imagined and made up o f many.
The so-called “death of the author” (Barthes, Foucault and – with less theory – Twain) predates current
phenomena like the f lux of mass ive data induced by search engines like the Web of Knowledge and Google
Scholar or digitilization, but today it becomes more relevant than ever. How are we treating these new
circumstances? One metaphorical approach could be changing our understanding of the scientist more and
more f rom songwriter to DJ. While at f irst s ight this might appear as a devaluation of the scientist it is
rather a revaluation of the DJ: the work of the DJ does not only consist in playing records o f others, s_he
draws up narratives, samples old bits of pieces and f inally turns them into something new (check this
speech by DJ Spooky on Remix Culture). The DJ is creating and inventing but the relations betwen his_her work and the work of others is more visible than it is in the case of the person that claims to be the creator
of his_her own ideas. S_he is more node than author, more conclusion o f successf ul practices than lone
standing monument. The metaphor enables us t o rethink authorship without discrediting creation as the
essential part of our scient ific work. It also gives way to recons idering mixing and merging as eclecticism
that doesn’t need to end up in a blended, unrecognizable and indecipherable melange. More than ever we
are able to locate ourself in the network of knowledge that we are working in.
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Autho rship played and s till plays an import ant ro le in our society and in science, culturally and legally, but we
can argue that authorship is merely the consequence of cutting of f the remixing process that has been
done to f inish the creative process. 7 Certainly, by using ref erences we already confess the hypertextual
condition o f our work, but st ill the own work is crucial to what we are doing. There might be a slight chance
that the way we locate ourself s in the work we do will change in the f uture. Referring to knowledge could
transf orm f rom pointing to the work of certain authors t o t he identif ication and construction of networks
of their ideas. If the humanities take the direction that has already anticipated by web technology we will
see more collaborative projects and networks of researchers but also the decrease of the authors
relevance in scientif ic work.
IV. Summing things up: (Perpet ual) β-Science
The production o f science can learn f rom so f tware releasing st rategies commonly practiced in web 2.0
environments. One is the shif t f rom a teleological release process towards a cyclical one. In their f requently
quoted article “What is Web 2.0” Tim O’Reilly and John Battelle prognosed the “End of the Sof tware
Release Cycle” (t raditionally proceeding f rom PreAlpha taking Alpha, Beta, RC to the Final Release). O’Reilly
and Battelle argued that in Web 2.0 not products but operations must become a core competence and
users are treated as co-developers. Instead of proceeding f rom Beta t o Final, products s tick in a
perpetual Beta process, were they are continuously e laborated. A short look on current web 2.0 productsshow that perpetual beta is already the most f requent case even if release terminology st ill recurs to Alpha,
Beta, Final.
Now, learning f rom changes o n the web does not necessarily imply the end of the publication release cycle,
but it def initely challenges the idea of the “f inal release”. Publication traditions st ill support the idea of the
“stable version” as the main medium to perf orm science. In many disciplines, especially in Historiography,
the monography is still a kind of gold st andard. And yes, there are good arguments to produce grand
narratives o f science instead of short art icles depending on whatever you work on. But β-Science does no t
mean a retreat f rom greater to smaller narratives but a turn towards more hybrid ones. Indeed, Wikipedia is
a good example for hybrid narratives that are equally gigantic. 8 It reads much dif f erent than a book but it is
technically capable to do t he same. 9
We can understand β-Science as a fundamental acceptance of “science in progress”, hybrid
narratives and the increased use of “bits and pieces” as valuable parts in collaborative
productions. β-Science is a habit, thus part of our socializat ion. A mundane and certainly not very
philosophical illust ration for the dif f erent f orms of socialization is the existence of “Let me google this f or
you” (you don’t know what is? click here or – less inf antile – here). Lmgtf y is symptomatic for a peer group
where stupid questions actually do exist, namely when you can answer them on your own – via search
engines/Google. There is a gap between those who are using and experimenting with digital to ols
constantly to work with their questions and problems and those who primarily fall back upon non-digital
sources of knowledge. As f ar as I see this gap is go ing to be closed as t ime goes by. Until then it’s worthdiscussing it critically.