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<div>We apologize if you receive this message more than once.<br>
<br>
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We are happy to inform you that the program for the keynotes is
available at the conference web site: <a
class="moz-txt-link-freetext"
href="http://tinyurl.com/ieee-edoc16"><a class="moz-txt-link-freetext" href="http://tinyurl.com/edoc16-keynotes">http://tinyurl.com/edoc16-keynotes</a></a></div>
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More information:<br>
============================================================ </div>
<div>IEEE EDOC 2016 - The 20th IEEE International EDOC Conference</div>
<div>============================================================ </div>
<div><br>
</div>
<div>EDOC 2016 - Vienna, Austria</div>
<div>September 05-09, 2016</div>
<div><a href="http://edoc2016.univie.ac.at/">http://edoc2016.univie.ac.at/</a></div>
<div><a href="http://twitter.com/ieee_edoc">http://twitter.com/ieee_edoc</a></div>
<div><br>
</div>
<div>IEEE EDOC 2016 is the twentieth conference in a series that
provides the key forum for researchers and practitioners in the
field of enterprise computing. EDOC conferences address the full
range of models, methodologies, and engineering technologies
contributing to intra- and inter-enterprise application systems.
Since 1997, EDOC has brought together leading computer
scientists, IT decision makers, enterprise architects, solution
designers, and practitioners to discuss enterprise computing
challenges, models and solutions from the perspectives of
academia, industry, and government. The EDOC conference series
emphasizes a holistic view on enterprise applications
engineering and management, fostering integrated approaches that
address and relate business models, business processes, people
and technology.</div>
<div><br>
</div>
<div>EDOC 2016 welcomes high quality scientific submissions as
well as experience papers on enterprise computing from industry.
The main theme of EDOC 2016 is ”Enabling innovative business
models in the enterprise of the future” and seeks to explore
innovative approaches synthesizing concepts of (1) data science,
(2) enterprise computing and (3) social computing.</div>
<div><br>
<br>
Keynotes<br>
======<br>
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<h2 style="box-sizing: border-box; font-size: 39px; margin: 21px
0px 10.5px; font-family: Lato, 'Helvetica Neue', Helvetica,
Arial, sans-serif; font-weight: 500; line-height: 1.1; color:
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text-indent: 0px; text-transform: none; white-space: normal;
widows: 1; word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);"><small>Technologies for
Happiness - and their Impact on Enterprise Application
Architectures</small></h2>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><strong style="box-sizing: border-box;
font-weight: bold;">Fabio Casati</strong></p>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">University of Trento</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Abstract</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Technology has profoundly changed all aspects of
our personal and professional lives, and is continuing to do
so at an ever increasing pace. Most of these changes help us
be more efficient, effective and flexible. What is still
unclear is whether this change has made us happier, that is,
if it has improved our quality of life or whether it has made
it more hectic and stressful.Pursuing happiness is considered
a goal worthy in its own right, and happiness has a wide range
of "side" benefits as well: happier individuals are healthier,
more social, more giving, more collaborative, and so on. It is
therefore not surprising that research on happiness has
intensified in recent years, with the rise of scientific
fields such as positive psychology that studies how we can
live more fulfilling lives. This talk is about positive
technology, that is, technology that can directly contribute
to people's happiness. I'll start by presenting what science
today considers as important determinants of happiness, both
as adults and as we age, and how it can be "measured". We'll
then discuss how technology can affect these determinants and
what are the potential and the key ingredients of positive
technology as a science. Finally, we'll assess the impact
positive technologies can have on enterprises, by enabling
employees to become more effective at what they do and more
capable of living in a constantly and sometimes "disruptively"
changing environment.</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Speakers's Bio</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Fabio Casati is professor of social informatics
and senator at the University of Trento. Until 2006, he was
technical lead for the research program on business process
intelligence in Hewlett-Packard USA, where he contributed to
several HP commercial products in the area of web services and
business process management. He then moved to academia, where
he started a research line on technologies for happiness,
delivering results that have a direct impact on people’s life.
The research results are available at<span
class="Apple-converted-space"> </span><a
href="http://lifeparticipation.org/" style="box-sizing:
border-box; color: rgb(0, 102, 153); text-decoration: none;">lifeparticipation.org</a>.</p>
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border-top-style: solid; border-top-color: rgb(236, 240, 241);
color: rgb(51, 51, 51); font-family: Lato, 'Helvetica Neue',
Helvetica, Arial, sans-serif; font-size: 15px; font-style:
normal; font-variant: normal; font-weight: normal;
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white-space: normal; widows: 1; word-spacing: 0px;
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255, 255);">
<h1 style="box-sizing: border-box; font-size: 39px; margin: 21px
0px 10.5px; font-family: Lato, 'Helvetica Neue', Helvetica,
Arial, sans-serif; font-weight: 500; line-height: 1.1; color:
rgb(0, 102, 153); font-style: normal; font-variant: normal;
letter-spacing: normal; orphans: auto; text-align: start;
text-indent: 0px; text-transform: none; white-space: normal;
widows: 1; word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);"><small>Enterprise
Computing in the Context of Networked Business Paradigms</small></h1>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><strong style="box-sizing: border-box;
font-weight: bold;">Paul Grefen</strong></p>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Eindhoven University of Technology</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Abstract</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">In recent years, we have seen the emergence of new
business paradigms that highlight the importance of business
network thinking. These business paradigms stress the idea
that business thinking should not be based primarily on an
intra-organizational focus, but rather on the relationships
with business organizations, such as collaborators or
customers. For example, the service-dominant paradigm is
centered at networked co-creation of value for customers
through services. The recent outcome economy paradigm revolves
around facilitating measurable business results for customers.
Combining these paradigms with the concept of agile business
leads to dynamic business networks as a first order citizen in
business engineering. These developments have a strong impact
on the domain of enterprise computing: on the one hand, it
requires an outside-in engineering to complement the
traditional inside-out approach; on the other hand, it
requires a decoupling of strategic resource-based design from
tactic value-based design. In this presentation, networked
business paradigms are illustrated and their impact on
enterprise computing is explored. <br>
</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Speakers's Bio</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Paul Grefen is a full professor in the School of
Industrial Engineering at Eindhoven University of Technology
since 2003. He chaired the Information Systems subdepartment
from 2006 to 2014. Currently, he is the research director of
the School. He received his Ph.D. in 1992 from the University
of Twente and held assistant and associate professor positions
in the Computer Science Department. He was a visiting
researcher at Stanford University in 1994. He has been
involved in various European research projects as well as
various projects within the Netherlands. He is an editor of
the International Journal of Cooperative Information Systems.
He is an editor and author of the books on the WIDE and
CrossWork projects, and has authored books on workflow
management, electronic business and service-dominant business
engineering. He is a member of the Executive Board of the
European Supply Chain Forum. His current research covers
architectural design of business information systems,
inter-organizational business process management, and
service-oriented business design and support. He teaches at
the MSc, PDEng and PhD levels at TU/e and at the executive
level for TIAS business school.</p>
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color: rgb(51, 51, 51); font-family: Lato, 'Helvetica Neue',
Helvetica, Arial, sans-serif; font-size: 15px; font-style:
normal; font-variant: normal; font-weight: normal;
letter-spacing: normal; line-height: 21.4286px; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">
<h1 style="box-sizing: border-box; font-size: 39px; margin: 21px
0px 10.5px; font-family: Lato, 'Helvetica Neue', Helvetica,
Arial, sans-serif; font-weight: 500; line-height: 1.1; color:
rgb(0, 102, 153); font-style: normal; font-variant: normal;
letter-spacing: normal; orphans: auto; text-align: start;
text-indent: 0px; text-transform: none; white-space: normal;
widows: 1; word-spacing: 0px; -webkit-text-stroke-width: 0px;
background-color: rgb(255, 255, 255);"><small>The Role of Big
Data and Data Science within Digitization at Allianz Group</small></h1>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><strong style="box-sizing: border-box;
font-weight: bold;">Andreas Braun</strong></p>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Global Data & Analytics at Allianz SE</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Abstract</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">By Big Data Analytics we understand new
technologies and methods that go beyond how we previously
handled data and analytics. One the data side, for instance,
extremely large data sets can be stored and processed, even
real-time, and at reasonable cost. This is largely applied
also to unstructured data, for example internet and
clickstreams, bank and credit card transactions, and GPS/
geospatial data. On the analytical side, methods are no longer
limited to on hard-coded (business) rules or statistics, but
leverage artificial intelligence (AI) and particularly Machine
Learning (ML). Big Data platforms recognize recurring patterns
and act context-aware to transform the data mentioned before
into more meaningful actionable insights. In the
aforementioned scenarios ML not only typically delivers better
results than statistical approaches or rule-based systems in
particular, they can also be implemented dynamically and
adaptive; they are intelligent in a way. As a further key
element, ML allows predictions based on what has been learnt
so far—hence the term predictive analytics. The application of
Big Data today is manifold and of growing importance. However,
we believe that Big Data's most tangible and immediate impact
in the domain of business is in customer and consumer
analytics. This area has been summarized as the Digital
Consumer Journey Analytics. Such journeys are constructed from
people's movement and navigational patterns in both the
virtual and physical world. While individual data points are
at first not very expressive nor rich of content, and are seen
for themselves also anonymous in a way, the picture created by
continuous collection of ubiquitous data and their history
allows to unveil almost any identity profile [7]. This is
typically used for profiling, predictions, and segmentations.
For example, web pathways can be used to derive a
socio-economic customer profile to predict interest,
purchasing intent, or churn. Comprehensive consumer profiles
can be cataloged and used for marketing purposes. The creation
of such insight became only possible through the use of Big
Data technologies and analytics: first of all, because of the
sheer amount of data and their history being used; secondly,
because online ML allows for the continuous improvement and
fine tuning of initial profiles and models so that they
increasingly correlate ever better with reality and the real
life situation of an actual person—eventually down to the
segment of one. The broader context beyond a single
individual, on the other side, allows for various marketing
relevant predictions: What do people within a category
typically buy? What are they interested to buy next? When do
they go on holiday, and where to? What do they spend on the
location they have travelled to? How to get in touch and
address them? etc. The entrepreneurial and economic value of
such analytics is beyond doubt and proven to be immense for
businesses. Conveniently enough, various different use cases
sit on the same data eco system. For example, while fraud
analytics saves two-digit millions in fraudulent claims, the
same data is used to “white-flag” uncritical claims to pay
customers faster and identify unhappy clients. Retention
models reduce churn by more than 20%—compared to the
statistical models used previously. Meanwhile, the same data
are used to improve the conversion rate in direct insurance by
almost 25%. We argue here that the ability to improve the
customer experience and innovate the customer journey is the
most important change on the new data wave. Besides
“white-flagging” claims to pay customers faster, web-pages can
be arranged accordingly to customer interest in real-time to
optimize usability and minimize navigation effort for the
customer as customer-relevant information is prioritized. Big
Data Analytics is used to make better and more relevant offers
to customers, or to refrain offers in the wrong moment.
Customers are understood increasingly well so that a customer
need can be identified in real-time: rebates can be added to
product-bundles for specifically price-sensitive customer
profiles. The customer experience is continuously measured and
fine-tuned in the background. Customers, in turn, will also
use technology to protect themselves from unwanted
advertisements and direct marketing. In the future products
and services not only will be developed using Big data but
also tailored to a customer's specific need. Staying in the
relevant set of customers will be of utmost importance. Hence,
we believe the notion of marketing will change and broaden and
continuously blend into e.g., product service design and
improvement. While information, IT and Cyber Security is
discussed since decades the new Big Data-driven challenge will
be data privacy and ethics. Basically, this means that legacy
approached like anonymization and personally identifiable
information or PII are not sufficient any more. The task for
marketing hence is to make products relevant and trusted in
the digital age/ In this paper, we illustrate a few successful
Big Data Use Cases in Consumer Analytics and discuss Privacy
by Design as an approach to be trusted.</p>
<h3 style="box-sizing: border-box; font-family: Lato, 'Helvetica
Neue', Helvetica, Arial, sans-serif; font-weight: 500;
line-height: 1.1; margin-top: 21px; margin-bottom: 10.5px;
font-size: 26px; color: rgb(0, 102, 153); font-style: normal;
font-variant: normal; letter-spacing: normal; orphans: auto;
text-align: start; text-indent: 0px; text-transform: none;
white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);"><small>Speakers's Bio</small></h3>
<p style="box-sizing: border-box; margin: 0px 0px 10.5px;
text-align: justify; color: rgb(51, 51, 51); font-family:
Lato, 'Helvetica Neue', Helvetica, Arial, sans-serif;
font-size: 15px; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height:
21.4286px; orphans: auto; text-indent: 0px; text-transform:
none; white-space: normal; widows: 1; word-spacing: 0px;
-webkit-text-stroke-width: 0px; background-color: rgb(255,
255, 255);">Andreas Braun graduated from TU-Munich in Computer
Science and theoretical medicine and pursued an
Accenture-funded doctorate focused on software architectures
for artificial intelligence. Today, Andreas heads up Global
Data & Analytics at Allianz SE. In this role, he is
responsible for the Global Data & Analytics Competence
Center at group level. This spans big data use cases,
governance, data sciences and advanced analytics, and the
respective technology and architecture. Previously, Andreas
was Global Head, Business Applications and Technology in GfK
SE, Germany’s largest market research firm, where he was
responsible for all customer-facing business software
development and new technologies, including e.g., Big Data,
Hadoop etc. Earlier in his career, Andreas was overseeing
operations, data analytics, and off and near-shoring at TNS
Infratest in Germany and Central Eastern Europe; in the 1990s,
Andreas co-founded a company focusing on image processing,
which he sold in 2000.</p>
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