the seamless integration of the various
forms of UIs and data, as well as their
adaptation to the huge diversity of
citizens. How can these UIs be designed
as a service accessible from everywhere,
anytime, and for everyone?
• The field studies that identify
success and failure stories on how COs
are being designed and used. Which
HCI design methods are actually used
or can be used?
• The use of social-media
crowdsourcing combined with
gamification strategies that empower
millions of users to be engaged not
just as data collectors, but also in
the design and innovation process
to turn data into new, innovative
services and solutions.
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5. Karaseva, V. and Seffah, A. The human
side of software as a service: Building a
tighter fit bet ween human experiences and
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6. Capitani, S. De et al. Privacy and security
in environmental monitoring systems.
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Ahmed Seffah is a professor of HCI and
human-centered software engineering.
His interests include design patterns, theories,
and practices, especially for cyber-physical
systems and their applications for societal
challenges such as sustainable development,
homeland security, and crisis management.
He has authored six books on the bridges
between HCI design, design science
research, and software engineering,
and on UX/quality-in-use measurement.
way? It is well known in many areas,
including COs, that there are two sets
of attributes that influence the quality
of the data being collected, and in
particular, people’s preferences and
decisions: 1) the degree of usability,
trustfulness, and accessibility, which
is influenced by the past experiences
of the data provider/receiver and
by the other community members
who participated in data collection
and dissemination; and 2) the
stakeholders’ assessment of the risk/
benefit trade-offs associated with
data usage. This requires measures
of privacy, accountability, and
Figure 2 gives an overview of a
quality model for human-data
interaction in COs that we are
developing. It depicts and compares the
six quality attributes of COs and their
foci, such as the questions what, how,
where, who, when, and why, which end
users and other stakeholders ask about
the data and the way in which they
interact with it. The model is bounded
in a 6 x 6 matrix with six quality
attributes as columns and the six
W-questions as rows. The
classifications are expressed by the
cells, that is, the intersection between
the six Qs and the six Ws. Each cell
should provide an answer to a question
from the perspective of a specific
quality attribute and the experience of
The following scenario illustrates
how correlations among different
datasets can affect the quality of the
human-data interactions and influence
Suppose that an external source
releases a study about the relationship
between pollutants and the diseases of
lake fish. By analyzing environmental
data collected by a municipality and
by citizens, and comparing that data
with study results, an insurer could
decide to increase the risk associated
with citizens living in a polluted area
and re-compute their policies. The
association of environmental data
from a CO with other data sources can
be exploited for inferring human-rights/privacy-sensitive concerns.
Suppose that someone has access to
data recording the medical histories
of the community. He or she might
then link such data with pollution
data from the CO and violate citizens’
privacy (adapted from [ 6]).
This model is derived from
analogous structures grounded in the
disciplines of architecture,
construction, engineering, and
manufacturing. The model classifies
the artifacts created during the process
of designing and engineering complex
products (e.g., buildings or airplanes).
The model considers data as a design
artifact being created, stored, used,
and destroyed, enabling focused
concentration on selected aspects of
the quality of data from a human
perspective, without losing a sense of
the context of use of the entire CO.
Finally, there is no doubt that COs
are a powerful platform for collecting
data and for engaging citizens in solving
societal problems [ 7]. Their long-term
success requires addressing the
following HCI issues:
• The architecture of COs to facilitate
Data Structure Matrix
What? Who? Why? Where? When? How?
Did certain data violate the privacy of a citizen
or a stakeholder? Citizens are free to participate,
collect, and disseminate a certain dataset without
unreasonable resistance or harassment from
authorities or the stakeholders. Citizen observatories
should help citizens master the techniques needed
to initiate actions in case their rights (e.g., data privacy)
are violated, and help them solve complex conflicts.
Is the data accessible to anyone who needs it,
wants to use it, or participates in the underlying
To what extent is the data useful?
Figure 2. The Six Ws/Qs Quality Model for Human-Data Interaction.