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A tour through four topics related to

The Web in Science and Research

KMi Podium – July 24, 2012

Peter Kraker

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Collaborators

Nicholas Balacheff

Günter Beham

Erik Duval

Ronald Fellmann

Angela Fessl

Denis Gillet

Nina Grabowski

Michael Granitzer

Eelco Herder

Patrick Höfler

Kris Jack

Fleur Jeanquartier

Christian Körner

Barbara Kump

Derick Leony

Stefanie Lindstaedt

Sandra Murg

Gonzalo Parra

David Pocivalnik

Wolfgang Reinhardt

Peter Scott

Thomas Ullmann

Bram Vandeputte

Claudia Wagner

Fridolin Wild

Jerome Zeiliger

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Scientific Activity on the Web

Online literature search

Collaborative writing and reference management

Dissemination via preprints and open archives

Knowledge transfer in social networks

Crowdsourcing approaches

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ResearchContext

Web ScienceThe interdisciplinary science

of the web

Research 2.0E-Science

Science online…

Studying the use of the web in the scientific

process

Social Networks

Privacy

Online Learning

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Overview

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

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Overview

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

The change in scientific practices and the open science movement

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The STELLAR Network of Excellence

The STELLAR Network of Excellence in Technology Enhanced Learning (http://stellarnet.eu)

Aim: unifying the diverse community of Technology Enhanced Learning (TEL)

Key activity: supporting researchers with web tools and infrastructure

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Study on Practices

Two exploratory focus groups with researchers from Technology Enhanced Learning

14 participants from all major disciplines involved in TEL

Qualitative analysis

Goals

Determine the research process in TEL

Collect web-based practices within the research process

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Results

Kraker, P., & Lindstaedt, S. (2011). Research Practices on the Web in the Field of Technology Enhanced Learning. Proceedings of the ACM WebSci’11. Koblenz, Germany.

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Results

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Results

Identified practices are mostly within the design and the publication process

Existing practices on the web do not necessarily work in research

Tools and technologies must be backed by existing practice,

or solve an obvious shortcoming in the existing practice

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Problems in Technology Enhanced Learning

Disjoint scientific communities (Gillet et al. 2009)

Low-cross citation rate, low cross-authorship rate (Kirby et al. 2005, Maurer and Khan 2010)

Multi-disciplinarity instead of inter-disciplinarity

Can an Open Science help?

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Open Science

“Open Science means opening up the research process by making all of its outcomes, and the

way in which these outcomes were achieved, publicly available on the World Wide Web”

Open Data Open Source

Open AccessOpen

Methodology

Open Science

Kraker, P., Leony, D., Reinhardt, W., & Beham, G. (2011). The Case for an Open Science in Technology Enhanced Learning. International Journal of Technology Enhanced Learning, 6(3), 643-654.

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Potential Benefits of an Open Science

Connect research communities – exchange and discussion

Enables reproducibility of research – increase validity, efficiency and comparability

Benefits stakeholders – results are earlier available, fosters open innovation

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Overview

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

The provision of web tools for opening up the research process

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Open Archive

E-print archive

Publication metadata aggregation and dissemination site

TEL Thesaurus and TEL Dictionary

http://oa.stellarnet.eu

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TEL Europe

Social network

Profiles

Groups

Blogs

Podcasts

Project results

Personalisable dashboard

http://teleurope.eu

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Stream: Mobile Learning (#mlearning)

Widgets on TEL Europe

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Overview

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

The development of an online infrastructure to connect the tools

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Publication Feed System

Publication metadata has to be entered in different locations all the time

Institutional repository

Project reporting

Social reference management system

Goals

Entering the details only once

Web standards compliant

Can be used with existing infrastructure

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Publication Feed System

Kraker, P., Fessl, A., Hoefler, P., & Lindstaedt, S. (2010). Feeding TEL: Building an Ecosystem Around BuRST to Convey Publication Metadata. Proceedings of the 2nd International Workshop on Research 2.0.

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Overview

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

The analysis of data generated by researchers on the web

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Price 1961Extended by Leydesdorff (2008)

Analysis of Science

Information overload is NOT a contemporary problem in science

Science has been growing exponentially forthe last 400 years (Price 1961)

Number of papers (Larsen/von Ins 2010)

Number of researchers (NSF 2010)

Problems

Missing overview of research fields

Missing awareness of currentdevelopments

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Kraker, P., Wagner, C., Jeanquartier, F., & Lindstaedt, S. (2011). On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection. Proceedings of the 6th European Conference on Technology Enhanced Learning (pp. 220-232).

Awareness of Current Developments

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Tweet visualisations: Streamgraph

Hashtag: #www2012

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Tweet visualisations: Weighted Graph

Hashtag:#arv11

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Missing overview

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Missing overview

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Visualisation example

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Cited together 10 times

Cited together 2 times

Never cited together

Paper 1

Paper 2

Paper 7

The usual way of doing visualisations

Basis: Citations

Co-citations as a measure of subject similarity (Small 1973)

Problem: Citations take very long to appear in meaningful quantities (~3-5 years)

Visualisations actually a look into the past!

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Read together 10 times

Read together 2 times

Never read together

Paper 1

Paper 2

Paper 7

A new approach

Visualisations based on the readership of publications

Assumptions: Publications that are often read together, are of a similar subject (Rowlands & Nicholas 2007, Bollen & van de Sompel 2008)

With collaborative reference management systems such as Mendeley, we can measure readership

Readership statistics are much earlier available than citations

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Kraker, P., Körner, C., Jack, K., & Granitzer, M. (2012). Harnessing User Library Statistics for Research Evaluation and Knowledge Domain Visualization. Proceedings of the 21st International Conference Companion on World Wide Web (pp. 1017-1024). Lyon: ACM.

Results

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Summary

The Web in

Science and

Research

Practices

Tools

Infra-structure

Analysis

The change in scientific practices and the open science movement

The development of an online infrastructure to connect the tools

The provision of web tools for opening up the research process

The analysis of data generated by researchers on the web

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www.know-center.at

Thank you for your attention!

http://twitter.com/PeterKrakerhttp://science20.wordpress.compkraker@know-center.at