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TABLE OF CONTENTS
01 Summary ............................................................................................................2
02 Intro: Internet of Things, Big Data Smart Cities ...................................................3
03 Resulting Technology and ECM..........................................................................4
04 Challenges created by new tech .........................................................................7
05 What this means or Content Management ........................................................ 11
06 The Future: Integration and Decision Models ................................................... 12
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01SUMMARY
The future is here, with the drive for innovation as the harbinger.
What may have previously seemed like science fiction or top
secret technology is now a reality with radar technology,
geospatial mapping, and powerful analytics and forecasting
technology joining forces.
But with the positivity associated with powerful new technology comes equally as challenging
problems around user realization and awareness of how to integrate it. The same issue arises
around the management of data and content in new IT ecosystems. Finally, as a result of this
new wave of technology, many existing sectors within IT are being challenged to evolve and
integrate in new directions that might not sit in their sweet spot. And more rapidly, firms are
realizing these factors and taking action.
In April 2015, IBM announced a 2BIL investment in Internet of Things, (IoT) technology
development, while other large giants like EMC launching new innovative offerings frequently.
For each new technology, the whole infrastructure of supporting services must make
decisions to adapt or conform – from content management and cloud applications to
analytics. For most companies the answer has been simple: they must innovate to keep in
step with the global trends. But what are these trends, and what challenges does their
realization and integration truly entail for content management? And moreover, what does
the future that can embrace these challenges look like?
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02 Intro: Internet of Things, Big Data,
Smart Cities
Internet of Things, or (IoT) is the term used to summarize the reality that now the internet in organizations
is more than just browsing websites or using Software as a Service (SaaS) applications. Devices like sensors,
automobiles, and tracking devices now use the Internet to form interconnected real-time systems, such as
smart cities with parking space sensors, as well as supply chain and manufacturing systems for corporations.
Enterprises may soon need many deployments of sensors not only grouped into standalone functional
services, but in turn those IoT services will need to be integrated into enterprises’ overall operations.
Like IoT, the term “Big Data” has received much hype of late, and like IoT, allows for intense analytic
capability in organizations, but with a focus on numerical analysis and extrapolation.
“Smart Cities” are the municipal application for the amalgamation of both sensory technology and wireless
communication made possible with IoT systems, and can even include data analysis and forecasting for
much of the incoming swath of data across various platforms. The term “smart city tech” also expands to
include integrated systems with workflows for information and requested across organizational boundaries
and technology systems.
If the future truly is in these new types of infrastructures, and with millions of online devices producing
data, IoT and big data will become necessary components in operational systems that provide true value in
day to day functions within large organizations, cities, governments and centralized Cloud applications. In
order to feed data in real-time to centralized Cloud or SaaS systems that produce data for consumption in
various forms, there needs to be an easy way to integrate these various devices and operational systems.
Connecting devices and software via real time integration between divergent systems, to increase
functionality and accessibility of required data, is not easy. This connectivity presents barriers to leveraging
Big Data to improve oversight of enterprise data or present it in various formats in any meaningful way.
This issue is particularly true with enterprise content management sector, where such integrations often
require complex export and transfer processes. IT protocols require exacting records management and the
ability to integrate, classify, and index files instantaneously with visibility and traceability.
Many technology companies must understand what these specific technologies are capable of, and some
of the latest trends and issues related to implementing them.
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03 Resulting technology and ECM
Some of the largest and newest trends on the market that have an effect on ECM sector can be divided
into the categories of Corporate Operation Platforms, Smart City Technology, and Geomatics
Corporation Operational Platforms
Manufacturing and Distribution Systems: These
systems can work with radar and tracking devices to
streamline warehouse and manufacturing processes.
Data can be used to improve efficiency, as well as to
predict future materials and resource needs.
Example: Stanley Black & Decker Connected Tools -
this platform links IoT sensing on high-end large
professional powered tools via the Salesforce1
Customer Platform to the rest of their business.
Visibility of failing tools allows Stanley Black & Decker
to offer the right support, including selling a
replacement, at a critical time for their customers. [4]
For ECM sector, this new reporting information must
be integrated with in-house and cloud management
systems in new ways that involve automated
formatting and indexing.
Big Data Analytics: Big data analytics are letting
organizations track and forecast information in new
instantaneous and dynamic ways. Its implications for
other new technologies like IoT and ECM is huge. For
content management in particular it offers the ability
to analyze trends across platforms like internal
knowledge management, social media and marketing
for large consumer enterprises as well as new forms
of managing all of the reporting and data streams
within ECM software in the cloud. They can make use
of semantic text analysis and automated
categorization. However valuable IOT and big data
driven functional services might be, if they are
standalone, then the last twenty years of IT projects
spent focused on creating automated end to end
business efficiency through integration are being
ignored. It’s vital to integrate these new technologies
into analytical and content management systems in
order to truly make them valuable.
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SMART CITIES
According to UN statistics, in 2014 more than 51% of
us now reside in urban environments. Since the turn
of this century, mega-cities in the developing world
have doubled their populations [2]. These facts
coupled with advancements in technology have seen
the natural evolution of software and technology to
better manage municipal infrastructures, however,
there's a lot of confusion over what comprises “smart
cities” technology. That’s because most are focused
on different outcomes. For example, digital cities,
driven primarily by investments from large vendors
such as Cisco and IBM, are aimed at enabling every
person and thing to be massively interconnected
through a complex array of high-speed networks,
servers, and data warehouses. Eco-cities on the other
hand, focus on environmental sustainability through
the widespread adoption of renewable resources. An
example of such is the Masdar project in the United
Arab Emirates, which aims to be a "carbon-neutral,
zero-waste" zone. Therefore, in reality, a true smart
city must be many things integrated in a holistic and
systemic way. [1]
Given the pervasiveness of geospatial information in
such new tools and services, one major component is
the use of geomatics in technology, which is a
requisite for establishing a Smart City. The growing
urbanization challenges that are part of the
governance of cities can be managed by such new
tools and may add flexibility to respond to citizens’
needs of services. A Smart City aims to deliver better
services to citizens, to give them real-time
information that may help them to make the good
choices and contributes to solve everyday problems
in a city. Transportation, security, available parking
places, water or energy consumption, information
about traffic jams, and alternative routes, snow
removal, goods, services, events. On time and well
provided information can simplify everyday life in a
city and help people make decisions.
51% of the world’s
population now lives in
urban environments
according to UN
statistics
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GEOMATICS
Since the emergence of dynamic and easily
accessible online mapping tools, there has
been a drastic increase in demand and interest
in geographic tools. Whether for personal,
social, professional or academic use, people
are using Geographic Information System (GIS)
technology to communicate information in a
map format. Whether it’s using Google Earth
to study urban change, or an energy company
creating new monitoring technologies, more
and more members of society are turning to
online mapping programs for their
visualization needs.
Geomatics and GIS enabled technologies play
an integral role in smart city technology, and
become part of the foundation for smart city
systems by providing location-centric
information. While an integral part of smart
cities, they are also the base of many more
scientific and monitoring systems used for
environmental monitoring, geology, mining,
pipelines, power lines, hazardous substance
storage and transportation, and integration to
satellite technologies. As this information is
more and more readily available, users and
managers across organizations must learn how
to make use of new systems and data.
To address the issue of spatial literacy, namely the
ability to use the properties of space to communicate
reason and solve problems, organizations,
government agencies and cities can provide location-
related information for public use. Not only should
geospatial infrastructures and technologies be
available to integrate spatial information in city
management and services, but service providers,
infrastructure operators and decision makers should
understand how to organize this spatial information
and take fully advantage of it. They should know
where, when and how to think spatially. They should
understand spatial representations, understand 3D
models and conduct reasoning based on such
visualizations. They should be able to have a critical
eye towards the reliability, relevance and validity of
spatial information. Citizen participation and
empowerment being a key ingredient of Smart Cities,
the spatial domain should also be added to city
change management and citizenship education.
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04 Challenges created by new tech
INTERCONNECTIVITY/ TECHNOLOGY ISSUES
However valuable IoT-driven, functional
services might be, experience can tell IT
and business professionals that if
these services are standalone, then
many lessons learned from the last
twenty years of creating end-to-end
operational business efficiency
through IT integration are being
ignored.
But the integration of data coming from
various application domains is not an easy task as
information does not always adhere to any
standardized format. Even within a single
domain, data is not easily integrated or shared.
Consideration of IoT data and integration within
domains needs to also be considered at the
international level. [10]
Most of the current proposed integration
mechanisms and processes on the market are
excellent frameworks: but they are only
standards that leave decision making algorithms
out of the picture, saying how to do something
but not when or how to solve integration
problems. This allows numerous
researchers and engineers to study
and develop efficient solutions for
improving flexibility needed to
meet heterogeneous
requirements. This is the case
where integrating to other
analytics systems such as big data
and corporate forecasting predictive
analytics, and requiring custom integrations in
each instance.
A recent trend report from Deloitte Consulting
warns: the analytics capabilities exist for Internet
of Things (IoT) data, either in source systems, or
through secondary applications; “It’s the
integration of systems and lack of interoperability
that will challenge organizations”, [7]. Such
quote reinforce the reality that it’s one thing to
have massive databases in the Cloud, or stored in
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silo systems, but quite another to reliably pull the
data from various sources and make it available
in a meaningful form for mission critical
applications such as first responders or for public
consumption.
According to industry reports from Oracle, in
ideal systems, such integrations result in higher
efficiencies and cost savings –where the crucial
component is the necessity of having a Service-
Oriented Architecture (SOA) approach that
facilitates a fully shared environment. [2] Taking
such a SOA approaches for local and city
government organizations will require a new way
of thinking about IT infrastructure, not only
technically but organizationally. SOA can leverage
multiple vendors who build systems and create
interoperability by using each other’s capabilities.
By interoperating and mapping an SOA approach
across IT systems, local governments can achieve
dramatic results. Such thinking will shift the old IT
model of proprietary systems that can’t be
transformed from older generations of
technology to a flexible, shared model that leaves
room for scalable, incremental growth [2]
This all spells the need for extensive integration,
testing, and validation. This can be extremely
costly, particularly when design and build project
processes for IoT services have not been clearly
defined, and lack many clearly distinct successful
cases.
SECURITY/PRIVACY ISSUES
Another major challenge is convincing companies
to give up some of their lock-down by publishing
certain aspects of their data. While proprietary
formats and APIs may give them an edge now, in
the long run, this may work against them as
competitors agree to follow standards. But until
then, it will be hard for organizations to realize
the real value of IoT analytics,
On the internal operating environment of private
and public organizations, different security issues
around privacy and data lockdown exist.
Researchers and consulting firms have both
proposed various models for adaptive data
handling, data processing, and data fusion
methods that are required to handle the
industrial IoT data emerging. [10] It can be
expected that data from IoT systems needs to be
correlated to the already available automation
and control data in organizations. For example, in
many developed markets, privacy concerns and
industry fragmentation are creating barriers to
unlocking new value in healthcare from pervasive
computing solutions. This blended information
will be needed for a specific installation, and also
available on site rather than cloud, in the case of
utilities or manufacturing companies. All this data
and information needs special attention
regarding handling and management in terms of
security and access, with migration and
import/export rules for ECM systems. While
many existing security frameworks exist, these
must be adapted to new technology on an
ongoing basis and requires constantly evolving
policies for managing information.
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SUPPLY CHAIN AND PARTNER ISSUES
Many businesses, governments and international
firms are just beginning to dive into the world of
big data, smart technology and IoT. In a study
analyzing the partnership and collaboration
between different technology and organizational
stakeholders, researchers found that it was
necessary for large technology partners to
develop working groups centered around each
technology area, and then in turn adapt their
services and solutions to each customer they
dealt with, often running pilot programs with new
customers for new technology. [13] In such
undertakings, it’s important to recognise that the
needs and aspirations of each city may be very
different; and requires partnerships (across many
clients and with other delivery partners) to
achieve the desired large-scale transformations.
Many such working groups existing at different
levels: in Europe there are initiatives like smart
city conferences and large European working
groups with members across nations. The same is
true
in
China, with many central planning initiatives with
large corporations in cities like Beijing focused on
manufacturing. While there are organizations in
the US such as the Smart City Council, there is a
relatively low amount of engagement relative to
the proportion of large cities and infrastructure
needs.
In terms of big data and internet of things, most
US firms do seem to be at the front of the pack
however, with other global organizations, and in
many cases are redefining new technologies in
manufacturing, energy, finance and the like.
In large technology consulting firms like IBM,
Cisco and HP, there is specific technology
developed for integration in each of these areas
as well as specialist service teams that extend
beyond their technical expertise into thought
leadership and areas for “Smart City”, “Big Data”,
and so on.
The dynamic found across smart city and
technology research reports seems to indicate
that engagement must be driven across
government levels, corporate service providers,
and technology development firms. In order to
create the most appropriate technologies, often
development must be run on a client test proof,
whereby organizations from across the 3
mentioned above partner to take on a new
technology challenge, which can then be
repurposed by the consulting or technology firm
for another client. This complex industry-society
dynamic by itself is both a challenge and an
opportunity – it poses a challenge insomuch as
SMART CITY TECHNOLOGY SUPPLY CHAIN INTERACTION
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that it is a barrier for organizations that aren’t
able to collaborate or gather the resources for
such large infrastructure projects. However, the
opportunity for both large and small businesses is
that it can allow for new product development
and results in a reusable product. It also creates a
lot of new value chain opportunities for firms
with specific vertical market products to fit into
infrastructure provided by larger tech and
consulting firms, and in some cases can work
independently with smaller clients if their
services suit the need and business model.
BIG DATA ISSUES
The spatial dimension introduced by geospatial
technologies accentuates the general challenges
that big data installations and governance face,
namely variability in: volume, variety and velocity
of information [7]. The differentiation of spatial
data types, (ex. points, images, polygons, etc.)
level of details, and reliability requires adapted
data integration approaches to handle
inconsistencies. Also, as sensor data tends to be
noisy, analog, and high-velocity, it creates
challenges that traditional analytics architectures
and techniques will not handle well. This is
especially true if integrating sensor data and
historical data in real time. [7]
Furthermore,
big data analytics
tools are generally not able to deliver the value
associated with spatial analyses. Such analyses
generally require dedicated storage,
manipulation and visualization functions that can
geographically organise, structure, correlate or
mine the data in order to unlock new value.
Historically, business intelligence (BI) and GIS
technologies have followed separate paths.
However, Geospatial intelligence (i.e. GeoBI) is a
new group of technology, offers solutions in its
ability to make sense out of the spatial or location
information attached to the data, to segment
data based on spatial patterns and find patterns
of spatial clustering. This adds powerful insights
into information patterns that cannot be
obtained in any other fashion [3].
PERSONAL, PHILOSOPHICAL AND LEGAL
The preservation and cultivation of human
agency in IoT is especially at stake as the innate
pervasiveness, distributed, and networked
character of connections can impair the human
ability to control the system while being part of it.
This implies creating the conditions for a dynamic
but alert integration of technical and human
dimensions in the already tangled nodes of
machines (deterministic, mechanistic action) and
user agents (nondeterministic, creative, self-
reflexive action). Traditional security solutions
like Role Based Access Control (RBAC) and
Attribute Based Access Control (ABAC) systems
may not be adequate to support the
heterogeneity and complex distributed
environment of IoT. For example, RBAC and ABAC
have very limited expressiveness considering
complex policy
rules including context-aware obligations with
temporal constraints, which are common in IoT
scenarios. In smart city systems with secured
information, this presents management control
issues.
ISSUES AROUND DATA AND CONTENT IN NEW TECH
VARIABILITY
COMPLEXITY
PLURALITY OF
SOURCES
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05 What this means for content
management
As the industry adapts, web services standards and open API’s are lowering the barrier to integration and
collaboration in content management and strategy projects. Software providers and analysts have spoken
out that it’s easier than ever to create connections between systems, storing and managing content assets
in one system and presenting them in another [5]. However, it still means that projects to design custom-
code integrations are required, creating time and cost concerns for integrations. [5]
With the continued advancement of open API’s and their coming into the mainstream in content
management systems, there are more and more opportunities for clients to work with development
partners and application developers of any software or program language strength to customize their
implementations of enterprise or cloud services. With the technical barriers to system integration being
broken down with, there is a clear trend emerging for customers to be forging partnerships with 3rd party
content providers, publishers, distributors and developers.
This means that development partners will be not only easier to identify and more available but also more
qualified in working with API’s. This is particularly true for those seeking to extend their services through
the integration of complementary applications, and true for those that have “content strategy” in their
marketing mix. Reduced technical barriers provide more incentive to integrate content from 3rd parties
and build partnerships and collaborations around a content exchange. It’s clear that Web and content
management systems that offer ease of integration and popular API’s will be at the center of these partner
relationships. [5]
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06 The future: integration and new
decision models
Industry reports that look at the requisite success factors of IoT strategies all seem to echo: it’s almost
impossible to create holistic pictures and ecosystems of IoT data, and thus a more powerful analytics
capability, when you can't get all of this data to be integrated and standardized in some way. [6] A different
question has emerged across smart city technology research: how do companies and governments select
design and implement new system strategies and technologies without experience in using appropriate
models for decision making in these new technologies? The answers seem to rest in letting the market
allow natural market forces to produce the most valuable solutions to clients at the right time, in the right
place.
SERVICE INNOVATION, PARTNERS AND
INFRASTRUCTURE INTEGRATION
Companies are competing to provide the
hardware, software, and services to implement
and expand these sectors. If the past is an
indicator, we will see different companies
providing them than they are today. We can
expect to see the winners develop high-value,
repeatable solutions at the intersection of
mobility, analytics and cloud computing - creating
new sources of value in technology.
Industry analysts at Bain and Company have
posited that all of this activity will generate
tremendous opportunity across many industries
such as telecommunications, software/IT-
enabled services and consumer electronics.
Some industries are already using pervasive
computing at scale. In many developed markets,
utilities are investing significantly in smart grids,
smart meters and smart thermostats,
encouraged by regulators and established
standards.[8] With demand and availability of
new systems, companies will need to partner
with complimentary technology to create the
most interconnected and valuable services to
clients, that can integrate and scale easily.
GOVERNANCE, OPENNESS AND PRO-
ACTIVENESS
On the other hand, the success of placing the new
technology within infrastructures such as smart
cities requires a cohesive vision, direction, and
openness from government organizations, while
corporations require education on how to
integrate such systems into their operations
models and product offerings. And it’s not easy as
there are many challenges ranging from privacy,
change management, and user awareness.
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THE FUTURE:
Bain analysts speculate that companies that create affordable, end-to-end offerings will make it easier for
others to invest in the next wave of computing. Given time and with market pressure, we'll see new
platforms emerge within sectors, followed by cross-industry solutions. As these platforms emerge,
companies creating pervasive solutions at the infrastructure level will need to manage the interaction of
millions of inputs like sensors and geomatics, and find ways to cost-effectively collect and analyse the huge
volumes of unstructured data they produce.[8]
We are witnessing a major shift in terms of global economic growth - the GDP of western cities is
decreasing, while that of major Asian cities (India and China) is increasing quickly [13]. If western cities want
to maintain and evolve in sustainable directions to have leading economic activities, they will have to find
new strategies to do so. The underlying philosophy for technologies like big data and smart city
transformations guarantees an increased attractiveness of brains and creative and innovative companies,
more efficient organization and a concern with respect to the quality of life and sustainable development.
This is the challenge presented to large and small scale vendors and service providers: to offer the most
value at the right time to clients, and to work with decision makers to design the most beneficial and
practical technologies.
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REFERENCES
1. The Future of the Future: Being smart about smart cities, Sep 29, 2011, Art Murray, Mark Minevich and Azamat
Abdoullaev, http://www.kmworld.com/Articles/Column/The-Future-of-the-Future/The-Future-of-the-Future-Being-
smart-about-smart-cities-77848.aspx
2. An Oracle White Paper June 2011 Oracle’s Solutions for Smart Cities: Delivering 21st Century Services
http://www.oracle.com/us/industries/public-sector/032422.pdf
3. Internet of Things – Converging Technologies for Smart Environments and Integrated Ecosystems,
http://www.internet-of-things-
research.eu/pdf/Converging_Technologies_for_Smart_Environments_and_Integrated_Ecosystems_IERC_Book_Ope
n_Access_2013.pdf
4. Andy Mulholland, Internet of Things; Enterprise Value = Integration, Automation and Scale, December 17, 2014,
https://www.constellationr.com/content/internet-things-enterprise-value-integration-automation-and-scale
5. Two Trends in Content Management for 2015, Posted 01.13.2015, http://dotcms.com/blog/post/two-trends-in-
content-management-for-2015/
6. Internet of Things Value Hinges on Data Interoperability, Integration, Loraine Lawson, 11 FEB, 2015,
http://www.itbusinessedge.com/blogs/integration/internet-of-things-value-hinges-on-data-interoperability-
integration.html
7. Deloite, Top Analytics Trends in 2015, http://public.deloitte.com/media/analytics/trends/analytics-trends.html
8. Bhanu Singh, Chris Brahm & Prashanth Aluru, Internet of things: The future is here, August 4, 2014,
http://www.business-standard.com/article/management/internet-of-things-the-future-is-here-
114080300624_1.html
9. Kounlis, Baldini, Building Trust in the Human– Internet of Things Relationship, IEEE TECHNOLOGY AND SOCIETY
MAGAZINE | WINTER 2014
10. Vermesan, Friess, Internet of Things Strategic Research and Information Agenda, Converging Technologies for
Smart Environments, Rivr Publishers, 2013.
11. IDC, EMC, The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things,
April 2014, http://www.emc.com/leadership/digital-universe/2014iview/index.htm
12. Rouse, Margaret, Big Data Analytics, http://searchbusinessanalytics.techtarget.com/definition/big-data-analytics
13. Jung Hoon Lee, Marguerite Gong Hancock, Mei-Chih Hu, Towards an effective framework for building smart
cities: Lessons from Seoul and San Francisco, 2008
