scaling community information systems

Lehrstuhl Informatik 5 (Information Systems)

Prof. Dr. M. Jarke 1

Learning Layers

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Scaling Community Information Systems

Ralf Klamma Advanced Community Information Systems (ACIS)

RWTH Aachen University, Germany [email protected]



Learning Layers

RWTH Aachen University

• 512 professors, 4675 academic and 2443 non-academic colleagues

• Annual budget around 884 million Euros, 445 million Euros funded by third parties

• 1,250 spin-off businesses have created around 30,000 jobs in the greater Aachen region over the past 20 years

•  260 institutes in 9 faculties as Europe’s leading institutions for science and research

•  Currently around 40,375 students are enrolled in over 130 academic programs

•  Over 6,300 of them are international students hailing from 120 different countries



Learning Layers

Responsive Open

Community Information

Systems

Community Visualization

and Simulation

Community Analytics

Community

Support

Web Analytics W

eb E

ngin

eerin

g

Advanced Community Information Systems (ACIS) Group @ RWTH Aachen

Requirements Engineering



Learning Layers

Agenda

Comm

unity

Infor

matio

n Sys

tems

Scali

ng C

ommu

nity I

S

Use C

ases

Conc

lusion

s & O

utloo

k



Learning Layers A Brief History of

Community Information Systems

Digital Media Technology

Communities of Practice

(Web 2.0) Business Processes

Meta Data

Media Traces

Semantic Web

(XML, RDF, Ontologien)

Multimedia (XML, VRML, DC, MPEG)

Organisational Memories

(XML, HTML, XTM)

Groupware / E-Learning (XML, LOM, XML-RPC)

Workflows (XML, BPEL)

Web Services (XML, WSDL, SOAP,UDDI)

Klamma: Social Software and Community Information Systems, 2010

Social Software

(XML, HTTP, RSS)



Learning Layers

The Fragmented Nature of the Web

The Web is a scale free, fragmented

network

•  Power Laws (Pareto Distribution etc.) •  95 % of users are in the long tail

(Communities) •  Collaboration and Learning is based

on trust and passion

Islands Tendrils

IN Continent Central Core OUT Continent

Tubes

Barabasi: Linked – The New Science of Networks, 2002 Anderson: The Long Tail: Why the Future of Business is Selling Less of More, 2006



Learning Layers

Communities of Practice Communities of practice (CoP) are

groups of people who share a concern or a passion for something they do and who interact regularly to

learn how to do it better (Wenger, 1998)

Characterization of Large Scale Professional Communities on the

Web

Shared expertise/practices over time in similar domains leading

to clusters as a social learning process

Deep community concerns about sustainability, security, legacy, and

scaling

Struggling with existing social software solutions by mashing-up & extending existing solutions as well

as searching & researching new solutions

How to support highly dynamic, clustered communities?



Learning Layers

ATLAS – A Reflective Community Information Systems Design Approach

Communities of Practice Clusters of Community Networks

Community Observation

Community Modeling

CESE: Talmud as a Hypertext

SOCRATESX: Chat for Communities of Aphasics

MECCA: Collaborative Movie Annotations

VEL 2.0: Virtual Entrepreneurship Lab

Virtual Campfire: MPEG-7 based Multimedia Management

ACIS: Cultural Heritage Management

youTell: Non-linear Digital Storytelling

ROLE – Self-regulated Learning Communities

TellNet - Teacher Communities

AERCS/TELMAP - Scientific Communities

GALA – Serious Gaming Communities

Open Source Software Development Communities

MobSOS – Real-time Mobile Communities

LAYERS – Informal Learning Clusters

Community Information Systems



Learning Layers

Challenges Privacy & Security

How can we share and how can we preserve privacy?

How trustworthy is the transfer of information in the infrastructure?

Sustainability What happened after the solution is developed?

Who is giving us support?

Legacy We need to integrate with our old system

We have found today a new fancy app we want to integrate immediately in our ecosystem

Scaling Why it does not work in the UK?

It is perfect for us. We want to sell it to anyone else



Learning Layers

las2peer Mission Statement

las2peer is a distributed, highly reliable and secure platform for creating community

information systems and community services. The main goal of las2peer is to provide a fast

and flexible way to create services which may communicate with each other and their users

through standard protocols. The used and stored information is handled in a trustworthy way and

within full control of the communities.



Learning Layers

From LAS to las2peer and Beyond

Social Software

LAS – Integration of Researchers into Communities

las2peer – Integration of Developers and Researchers into Communities

Societal Software



Learning Layers

Related / Prior Work

Collaborative Work/

Learning

BSCW – still part of our own

CIS

Technology Enhanced Learning

Semantic Web

Social Machines

Trust

Social Engineering

Nudges – UK Nudge Unit –

Bundeskanzler-amt – White

House

Crowdsourcing

Social Computing

Social Networking

Sites

User Behavior Analysis

Web Engineering

Peer-to-peer protocols

Web service architectures



Learning Layers

Must-Haves (Domain-Independent)

Community Information Infrastructure •  User – Community – Medium - Artefact Management •  Cloud – p2p – IoT – Cyber-physical

Read/Write Technologies •  Micro-Blogging, Blogging, Messaging, … •  Tagging, Sharing, Commenting, Rating, …

Gamification & Marketplace Technologies •  Sustaining & Exploiting Communities •  Valorisation Models - Apps / Content / Practices

Simple Community Analytics Technologies



Learning Layers

ACIS Offerings

End-User Platform

•  Scalable platform on cloud-based infrastructures •  Large-scale social requirements engineering with Requirements Bazaar •  Web-based, mobile, distributed interfaces with real-time collaboration support

Security & Privacy

•  Industrial strength single-sign-on solution OpenID Connect •  End-to-End encryption integrated •  Flexible and Configurable Delivery Model

Developer Support

•  Complete open source software friendly software engineering process •  Open source software development and community involvement •  Strong DevOps Support

Analytic Support

•  Advanced community analytics with community detection and expert identification •  Built-in qualitative and quantitative data acquisition and analytics •  Dynamic visual analytics in community dashboards



Learning Layers Interdisciplinary Multidimensional

Model of Communities ■  Collection of CoP Digital Traces in a MediaBase

–  Post-Mortem Crawlers –  Real-time, mobile, protocol-based (MobSOS) –  (Automatic) metadata generation by Social Network Analysis

■  Social Requirements Engineering with i* Framework for defining goals and dependencies in CoP

Social Software Cross-Media Social Network Analysis on Wiki, Blog, Podcast, IM, Chat, Email, Newsgroup, Chat …

Web 2.0 Business Processes (i*) (Structural, Cross-media)

Members (Social Network Analysis: Centrality,

Efficiency, Community Detection)

Network of Artifacts Content Analysis on Microcontent, Blog entry, Message,

Burst, Thread, Comment, Conversation, Feedback (Rating)

Network of Members

Communities of practice

Media Networks



Learning Layers Community SRE Processes–

i* Strategic Rationale



Learning Layers Requirements Bazaar & LASSRE

(Klamma et al. 2010, Law et al. 2012, Renzel et al. 2013)

§  Available online: http://requirements-bazaar.org §  Active use & development in Learning Layers Project §  Connection to Learning Layers Issue Tracker §  Further development taken over by István Koren §  IEEE STCSN E-Letter vol. 2, no. 3:

§  “Large-Scale Social Requirements Engineering“ (LASSRE) §  4 Main Articles (RWTH, FIT, Universities of Aalto & Leicester) §  4 Short Technical Tool articles (Hannemann, Koren, Renzel) §  Published Sept 6, 2014



Learning Layers

ROLE Requirements Bazaar – Community-aware Requirements Prioritization

Factors influencing requirements ranking

User-controlled weighting of ranking factors

Community-dependent requirements ranking lists

http://requirements-bazaar.org



Learning Layers

Learning Layers: Scaling up Technologies for Informal Learning in SME Clusters

§  7th Framework Programme §  Integrated Project §  Informal Mobile Learning §  http://learning-layers.eu/

Projects ROLE: Responsive Open Learning

Environments (until 2013) §  IST 7th Framework Programme §  Integrated Project §  Scientific coordination §  Self-Regulated & Social Learning §  http://www.role-project.eu BOOST – Buisness PerfOrmance

imprOvement through individual employees Sklls Training

§  LLL – Leornado Da Vinci §  Exploitation of ROLE Results §  http://www.boost-project.eu/

GaLA: Games and Learning Alliance

§  IST 7th Framework Programme §  Network of Excellence on Serious

Games & Learning §  http://www.galanoe.eu/



Learning Layers

SAGE: Serious Games Pathway within the Undergraduate IT Programs

§  EU TEMPUS Joint Project §  Serious Games §  http://www.sage.ps/

Projects METIS: Meeting Teachers' Co-

Design Needs by Means of Integrated Learning Environments

§  EU LLP KA3 Multilateral Project §  Learning Design §  http://metis-project.org/ UMIC: Ultra High-Speed Mobile

Information and Communication

§  DFG Excellence Cluster §  Mobile Web Services and Cloud

Computing §  http://www.umic.rwth-aachen.de/



Learning Layers Engineering & Analytics

Competences

•  Network Models •  Social Network

Analysis •  Actor Network

Theory •  Communities of

Practice •  Expert

Identification •  Community

Detection •  Web Mining •  Recommender

Systems •  Multi Agent

Simulation

Web

Ana

lytics

•  Advanced Web & Multimedia Technologies •  XMPP • WebRTC • HTML5 • MPEG-7

• Web Services • REST •  LAS

• Cloud Computing

• Mobile Computing

Web

Eng

ineer

ing

• MediaBase • MobSOS • D-VITA

• Requirements Bazaar • Direwolf • AERCS/CAMRS

•  yFiles • Repast • AERCS

• LAS & LAS2peer Web Services

• ROLE SDK •  youTell Storytelling • SeViAnno 2.0 Video

Annotation Responsive

Open Community Information

Systems

Community Visualization &

Simulation

Community Analytics

Community Support

Requirements Engineering

•  Large-Scale Web-Based Social Requirements Engineering •  Agent and Goal Oriented i* Modeling •  Participatory Community Design •  Gamification & Social Software Methodologies •  Open Source Developement

scaling community information systems

Science

rss lehrstuhl informatik

social software xml

bpel web services xml

xmlrpc workflows xml

xtm groupware elearning

clustered communities

web shared expertisepractices

ontologien multimedia