David De Roure

The Future of Scholarly Communications

A revolutionary idea…Open Science!

rstl.royalsocietypublishing.org

Overview

1. Shifts in scholarship

2. End of the article

3. Research Objects

4. Social Machines

The Big Picture

More people

More

mach

ines

Big DataBig Compute

Conventional Computation

“Big Social”Social Networks

e-infrastructure

Online R&D(Science 2.0)

InformationSociety

@dder

?

(Social Machines)

Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552

Chr

istin

e B

orgm

an

F i r s t

Big Data Network

New Social Process

http://www.theguardian.com/uk/series/reading-the-riots

Interdisciplinary and “in the wild” *

* “in it” versus “on it”

www.zooniverse.org

Scientists

TalkForum

ImageClassification

data reduction

Citizen Scientists

http://www.scilogs.com/eresearch/pages-of-history/ David De Roure

http://ww

w.scilogs.com

/eresearch/pages-of-history/D

avid

De

Ro

ure

1. It was no longer possible to include the evidence in the paper – container failure!

“A PDF exploded today when a scientist tried to paste in the twitter firehose…”

2. It was no longer possible to reconstruct a scientific experiment based on a paper alone

3. Writing for increasingly specialist audiences restricted essential multidisciplinary re-use

Grand Challenge Areas:• Energy• Living with Environmental Change• Global Uncertainties• Lifelong Health and Wellbeing• Digital Economy• Nanoscience• Food Security• Connected Communities• Resilient Economy

4. Research records needed to be readable by computer to support automation and curation

A computationally-enabled sense-making network of expertise, data, models and narratives.

5. Single authorship gave way to casts of thousands

6. Quality control models scaled poorly with the increasing volume

Filter, Publish, Filter, Publish, …Like big data, publishing has increasing volume, variety and velocityBut what about veracity?

7. Alternative reporting necessary for compliance with regulations

One piece of research may have multiple reports and multiple narratives for multiple readerships, in multiple formats and languages(Computer are readers too!)

8. Research funders frustrated by inefficiencies in scholarly communication

An investment is only worthwhile if• Outputs are discoverable• Outputs are reusable…and preferably outputs accrue value through use

Using an obsolete scholarly communication system impedes innovation and hence return on investmentWhat are we doing about it?Trying to fix it using an obsolete scholarly communication system!

data

methodscript

program

workflow

model

protocol

…

Nei

l Chu

e H

ong

www.myexperiment.org

Research Objects

ComputationalResearch Objects

The Evolution of myExperiment

WorkflowsPacks O

AIO

RE

W3C PRO

V

Social Objects

The R Dimensions

Research Objects facilitate research that is reproducible, repeatable, replicable, reusable, referenceable, retrievable, reviewable, replayable, re-interpretable, reprocessable, recomposable, reconstructable, repurposable, reliable, respectful, reputable, revealable, recoverable, restorable, reparable, refreshable?”

@dder 14 April 2014

sci method

access

understand

new use

social

curation

Research Object

Principles

www.researchobject.orgJun

Zha

o

Real life is and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration... The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid. Berners-Lee, Weaving the Web, 1999 (pp.

172–175)

Social Machines

SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org

ScholarlyMachinesEcosystemDavid De Roure, JCDL 2013

1. Shifts in scholarship– A “turn” or ongoing transformation?

2. End of the article– Don’t retrofit digital, think post-digital

3. Research Objects– Inevitable with automation– How do we cite them, how are they curated?

4. Social Machines– Humans in the loop, empowered– Can you view your projects as social machines?

Thanks to Christine Borgman, Iain Buchan, Neil Chue Hong, Jun Zhao, Carole Goble, FORCE11, myExperiment, Software Sustainability Institute, wf4ever and SOCIAM

david.deroure@oerc.ox.ac.ukwww.oerc.ox.ac.uk/people/dder

@dder

www.oerc.ox.ac.ukwww.force11.org

www.researchobject.orgwww.software.ac.uk

sociam.org

www.oerc.ox.ac.uk

david.deroure@oerc.ox.ac.uk@dder