Discoverability and Web-Enabled Science - #ScholarAfrica

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Information about Discoverability and Web-Enabled Science - #ScholarAfrica

Published on March 10, 2014

Author: kaythaney



Presentation as part of the Discoverability of African Scholarship workshop in Nairobi, March 10-11.

kaitlin thaney @kaythaney ; @mozillascience #scholarAfrica, nairobi / 10 march 2014 discoverability and web-enabled research


doing good is part of our code

help researchers use the power of the open web to change science’s future.

discoverability what the web offers role of data, sharing challenges around “open”


research cycle idea experiment lit review materials publish share results retest analyze collect data

types of information hypothesis/query protocols parameters content non-digital “stuff” articles proceedings negative results analysis code datasets models (added complexity) prof activities mentorship teaching activities

blocking points idea experiment access attaining materials publish share results retest analyze collect data (to name a few ...)

discoverability: ability to access (but also to reuse, disseminate)

technical needs metadata standards discoverability services dissemination platforms APIs, tagging

rewards, incentives, reputation


leveraging the power of the web for scholarship

- access to content, data, code, materials. - emergence of “web-native” tools. - rewards for openness, interop, collaboration, sharing. - push for ROI, reuse, recomputability, transparency. “web-enabled science”

wasted ... $$$ time opportunity

communication access, reuse, scale community-building the web as a platform

early forms of knowledge sharing

emergence of new communities, practice

broader access, engagement, reach

there’s still friction in the system. and duplication out of frustration.

traditions last not because they are excellent, but because influential people are averse to change and because of the sheer burdens of transition to a better state ... “ “ Cass Sunstein

our systems need to talk to one another. both human and machine, globally.


thinking beyond the PDF. role of data, code, methods.

3 GB/year

9 GB/PhD 3 GB/year

30,000,000 GB/all* 9 GB/PhD 3 GB/year * roughly

how much made available? 9 GB/PhD 3 GB/year * roughly 30,000,000 GB/all*

Source: Michener, 2006 Ecoinformatics.

code as a research object what’s needed to reuse ?

Source: Piwowar, et al. PLOS.


is open enough? necessary but not sufficient.

access versus deluge how to reconcile?

our systems need to talk to one another.

we also need to build capacity.

digital literacy

“Reliance on ad-hoc, self- education about what’s possible doesn’t scale.” - Selena Decklemann

education as a means of building community ... globally, as well as across disciplines.

current activity: 129 instructors (60+, training) 109 bootcamps 3700+ learners

in an increasingly digital, data- driven world, what core skills, tools do the next-generation need?


shifting practice (and getting it to stick) is challenging. and we’re here to help.

tools and technology cultural awareness, best practice connections, open dialogue skills training what are the necessary components?

coordination and collaboration are key. design for interoperability. remember the non-technical challenges.

operating in isolation doesn’t scale.

help shape the conversation. teach, contribute, learn.

questions? @kaythaney ; @mozillascience

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