TDT20: Enterprise Architecture, Smart Cities and Value-Added services
A Comparison of the Top Four Enterprise Architecture Approaches in 2014 What is EA? Enterprise An organizational unit - from a department to a whole corporation Architecture Formal description of a system or a detailed plan of the system at component level to guide its implementation The structure of components, their inter-relationship and principles and guidelines governing their design and evolution over time EA A formal description of an enterprise, a detailed map of the enterprise at component level to guide its changes The structure of an enterprise’s components, their inter-relationships and the principles and guidelines governing their design and evolution over time
The open group definition EA is about understanding all of the different components that go to make up the enterprise and how these components inter-relate IFEAD A complete expression of the enterprise a master plan which acts as a collaboration force
Why does an organization need an EA? To get an overview of the business processes, systems technology, structures and capabilities. Provides a strategic context for development of the IT system in constant change Achieve competitive advantage
Value for the IT organization Deeper understanding of organizational strategic intent Correct IT investment allocation Realized economics of scale Elimination of redundancies Reduced IT delivery time due to reuse Higher quality decision making at all levels An organization that works on the right things at the right time Selection/identification of correct technologies/functionality required by the organization An understanding of what we are doing and why as well as how individual roles and responsibilities support creation of an environment for enterprise success EA key concepts Stakeholder concerns interests that are critical or important to stakeholders Principles a univocal understanding about what is of fundamental importance for the organization Models purposeful abstractions of reality Views difficult to make a univocal and comprehensive set of models that can be understood by all concerned, hence views Framework Structure to select views EA approaches
Zachman An architectural framework in which an enterprise is modeled as thirty or thirty-six cells, each of which represents an intersection between a stakeholder perspective and an abstraction. Taxonomy for describing an enterprise Matrix Aspects what how where who when why Viewpoints Planner Owner Designer Builder Subcontractor Strength Comprehensive taxonomy to describe the enterprise Weaknesses No process to get to the finished product No regards for future architecture
TOGAF An architectural methodology that is controlled by The Open Group. consists of Architectural Development Method (ADM) Foundation Architecture Technical Reference model (TRM) Standards Information Base(SIB) Building Blocks Information Base (BBIB) Resource base Architectural views IT Governance Business scenarios Architecture patterns ets. Most important part is the ADM Method for creating EA Sessions calls TOGAF process Complements Zachman Benefits flexible about architecture generated Weakness TOGAF tells you how to generate A EA - not necessarily a good one
FEAF - Federal Enterprise Architectural Framework An enterprise architectural framework used by the United States federal government to describe how the various governmental agencies and their IT systems are related to each other. VRF - Value realisation framework Enterprise is modeled as collection of capabilities Each capability performs a function for the enterprise Goal is to identify capabilities in need of improvement
Capability Consumes consumebles creates resources expends fuel Agile EA: Oxymoron or new vision: Introduction: Enterprise Architecture involves both textual and graphical representations that comprise an integrated set of composite models that are normally built using one of the major EA tools.
Once the models are contained in a tool it allows decision makers in an organization or extended enterprise the ability to query across all models the rippling effects of any actual or planned change. Architectures, Ontologies and Frameworks John Zachman describes how architectural instantiations such as buildings (and enterprises) are the result of architectures In that result we can see the Architect’s “architecture” Architecture is the set of description representations for characterizing complex objects, such that an instance of the object can be created and serve as a baseline for changing it
Each of these perspectives relate to six different columns associated with the Aristotelian questions – what, how, where, who, when and why. The “what” refers to the entities involved, the “how” to processes, the “where” to locations, the “who” to roles and responsibilities, the “when” to timing and the “why” to motivations and business strategies.
So, for instance in the “what column” the executive perspective addresses a bill of materials or things relevant to the business, the management perspective would treat these as data entities in a semantic data model, the architect would understand these as logical data model, the engineer as a physical data model, etc. The enterprise conundrum Emergent and Agile enterprises are inconsistent with the traditional ontological view of an organization as an objectively observable activity This objective view sees the enterprise as something that can be measured, labeled, classified, and related to other organizational processes From this perspective, EA considers the enterprise as a static snapshot to serve as a baseline for target architectures James Thompson (1967) and Jeanne Ross (2011) describe how organization structure is affected by types of technology - which differs depending on the degree of interdependence (integration) in the transformation process.
The Complex Adaptive System (CAS) Perspective Contrary to the objective view is the recognition of organizations as complex adaptive systems that give rise to considerations of emergence, leading to a derived definition of emergent and agile enterprise architectures. This approach identifies organizations as non-linear and highly complex systems This necessitates a rethinking about how they are to be represented within the context of EA
Dealing with Organizational Messes rather than Problems In a real sense, problems do not exist. They are distractions from real situations. The real situations from which they are abstracted are messes. A mess is a system of interrelated problems. We should be concerned with messes, not problems. The solution to a mess is not equal to the sum of the solution to its parts. The solution to its parts should be derived from the solution of the whole, not vice versa Science has provided powerful methods, techniques and tools for solving problems, but it has provided little that can help in solving messes. The lack of mess.solving capability is the most important challenge facing us. - Russ Ackoff Enterprise Messes and the Need for an Emergent EA Problems have solutions. Messes do not have straight forward solutions. Messes are more than complicated and complex. They are ambiguous. They contain considerable uncertainty - even as to what the conditions are, let alone what the appropriate actions might be They are bound by great constraints and are tightly interconnected, economically, socially, politically, technologically. They are seen differently from different points of view, and quite different worldviews. They contain many value conflicts. They are often a-logical or illogical. The Gartner View of Emergent EA
A Case of TOPEND: Knowledge Spaces and Knowledge Modeling In the early 90s the NCR Corporation owned TOPEND - a transaction-oriented middleware platform that was eventually sold to BAE Systems and incorporated into Tuxedo Although there was an active TOPEND consulting practice there were only a few designers who had the reputation of being TOPEND Gurus. NCR wanted to capture their expert knowledge and sent them to a location in Norway and had them define a set of best practises. Bellman was tasked with modeling thos best practises into METIS. When the models were shown to the TOPEND architects they agreed the knowledge was correctly modeled. However, they argue the models were analogous to learning to paint by numbers. One can paint a Picasso painting by the numbers, but this does not infer one is a Picasso. This points to a need for another approach to deal with corporate memory and understand the phenomenological nature of knowledge spaces.
Define the Lines rather than the Boxes
Implications for the TOGAF ADM To-be is a moving target Continual iterations of the ADM Phases as the enterprise adapts to transitional architectural steps. Areas of Focus transform into ellipse change cycle patterns. - Interaction and interferences from different areas of focus is expected. Requirements Management begins to take on a “hive intelligence” structure.
A Representation Imagine that exchange “planned” information system (IS) change is like an ellipse going out from the initial point in time and ending on a planned end time. Now, move forward a unit in time, and a new change in the IS becomes necessary. If the change can be found within the first eclipse, then it would expand somewhat. Otherwise, it would be a new ellipse layered on top of the old one. If you repeat this n times for n changes, then you will see a pattern of overlapping ellipses stretching forward. A wave front is revealed, if you draw two (curving) lines connecting the outer edges of the ellipses. This model is close to one of the supersonic sound wave barriers. Architecting for emergence is a naturally disruptive process Change cycle Ellipses
Change ellipse has a beginning and a release; there is no “end” Internal change path is not necessarily linear Change can be interrupted, redirected or ended at anytime Many changes can and will occur at once. They can interact or interfere with one-another Yet, Maintaining Quality of Service is mandatory Emergent Architecture must consider how to balance system integrity with ongoing complex changes There is no “to be” end state in architecting for emergence Emergent Change Cycle Patterns
Change ellipses can overlap, split and recombine - Look for the emergent, yet repeated, patterns of change They exist, change or “die off” due to either - Endogenous change (Internal stakeholders, resources, time, policies, directives...) - Exogenous change (External related or competing systems, operational environment, external stakeholders, policies, change in technologies, mergers and acquisition, etc…) Active and work-centric knowledge have important intrinsic properties found in mental models including reflective views, recursive tasks, repetitive roles, and replicable knowledge architecture elements. This points to the need to discover the rules of change cycle complexity. Conclusion In conclusion we need to consider architecture as a crucible(smeltedigel) that entails the trade-offs between resource availability and constraints, along with meeting organizational/enterprise goals and user experience.
Agile is a set of actions that focuses and models the results to meet acceptance criteria, while enabling ongoing adaptation and accounting for emergence. Architecture is the representative artifact of the solution. We must consider how agile augments(make greater, more) and changes architecture methods to produce solutions that embrace greater user experience, while enabling adaptation. We must recognize how architecture brings focus and system discipline to agile.
Reflection How is this applicable to my project? Startups are small enterprises. They are emergent and develop FAST! Especially for me, using lean, this article shines a light on the fact that the architecture of my business is a crucible that entails the trade-offs between resource availability and constraint. The requirements for the enterprise is ever changing, as well as the resources, the stakeholders, the enterprise goals and user experience.
Many consider Agile EA to be an oxymoron. For me it is highly relevant. Yes, EA could be the blueprints and the plan for the enterprise, but all businesses do eventually need to change and adapt, and it is especially relevant for startups.
Framework to develop a business synergi through EA Research problem: There is a waste of resources and data owned or produced by organizations Applying analysis in the EA concept can convert data into valuable info that again can be used in decision making Leads to competitive advantage in production; improve profitability by implementing insight in the production activities
Related work: there is a lack of analysis of enterprise complexity lack of clear model og mapping to goal a virtual EA Lack real case applications Proposal: Virtual organizations are built by collaborations and partnerships between organizations. Create synergy and satisfy the strategic needs: making profit from handling data and processes.
This paper study integration between organizations through the concept of EA Exploiting the knowledge obtained from processes, data and technology
Characteristics of framework Evolvability: capacity to change according to demand in market and customer demands. Flexibility: Demand, Integration, Cooperation, Agility, Adaptability EA Components: Make use of data to conveniently integrate and offer flexible products demanded.
Conclusion Data is taking an important role in the management and development of big enterprises. In the era of e-commerce, it is necessary to leverage knowledge through the value chain in the virtual organization to enhance performance.
Reflection: How is this relevant to my task? The Software I am developing for my master thesis could become the groundwork for a startup company. As a small time company, the fact is that I may not be able to afford good IT infrastructure. At the same time, I have little to no data or information about customers. By creating a virtual enterprise with one of my competitors, I may both save resources on IT infrastructure, as well as share data with them, creating information and knowlegde on the field and creating a product for the potential customers. Defining Smart City Architecture for Sustainability Introduction Smart city definition is dependent on perspective. Close to a common definition: Innovation–not necessarily based on the information and communications technologies (ICT)-, which aim to enhance urban performance in terms of people, governance, mobility, economy, environment and living.
Smart city domain has emerged massively, with 40B EUR in 2016 and 3 trillion USD by 2025 Most investments in the smart city market are public, as there is still a resilience to invest from private investors.
Governments are positive to standardization. Standards have been developed for smart city solutions, but not for smart cities as a whole.
The aim of this paper is to define a common smart city architecture to serve government purpose for innovation and sustainability
Background A smart city is divided into 6 dimensions: People: in terms of discovering and meeting today and future requirements; Living: enhancing quality of life and social coherency, as well as efficiency regarding energy, food, water etc. Environment: protection, waste and emissions control and resilience against climate change; Governance: in terms of ensuring urban utility and service availability; Economy: in terms of sustainable growth and city competitiveness; Mobility: addressing transportation and traffic management issues.
Existing smart city architecture approaches Next the paper talks about module definition:
Module definition for a smart city is an extremely complex process and it has to consider both the type and the architecture According to the mentioned analysis of previous research, soft urban infrastructure (people, data and applications) is flexible and can easily extend and interconnect. Difficulties rise from requirements, which deal with hard infrastructure and environment.
Modular architecture approach:
- Networking Infrastructure and Communications Protocol: addresses necessary infrastructure to deploy smart services and enhance living within the smart city Cities from scratch have innovations based on hard infrastructure
- New Songdo in South Korea is one of these from scratch cities, and has a waste disposal, recycling and tele-heating factory installed and interconnected with all buildings in the city. They also have fiber-optic networks connect all local buildings with a central operating center, while smart buildings are accessible by their inhabitants via specific applications In existing cities there is innovation with existing hard infrastructure with the IoT and basically with sensors that exchange data with specific applications.
- Applications Module concerns all smart applications available in the smart city Good method for analyzing the module could be classifications in the four smart city dimensions, including a separate group for mobility
- Business Adresse the business groups available in the city
- Management Contains rules and procedures for managing smart city elements. Elements include:
Servies Concerns all types of smart city services offered with the contribution of the ICT from smart city supplier-side users and requested by demand-side users (inhabitants)
The paper suggests that the architecture of the smart city must be multi-tier in order to be clear and sustainable, in terms of standardization and communication of these standards. This because the examined cases in this study mostly use N-tier architecture.
Layer 1) Natural Environment: it concerns all the environmental features where the city is located (landscape, rivers, lakes, sea, forests etc.).
Layer 2) Hard Infrastructure (Non ICT-based): it contains all the urban features, which have been installed by human activities and are necessary for city operation (buildings, roads, bridges, energy-water-waste utilities etc.)
Layer 3) Hard Infrastructure (ICT-based): it concerns all smart hardware, with which SSC services are offered (i.e., data centers, supercomputers and servers, networks, IoT, sensors etc.)
Layer 4) Services: all types of smart city services, grouped in the smart city six dimensions and organized according to international urban key-performance indicators.
Layer 5) Soft Infrastructure: individuals and groups of people living in the city, as well as applications, databases, software and data, with which the SSC services are realized.
Conclusion Addressing lack of standardization, grounding RQ1 Used literature findings and data from well-known smart cities Findings suggest a common architecture must be multi-tier with 5 layers This architecture can be the baseline for smart city standardization Reflection How is this paper relevant to my task? It really isn’t. This paper mainly reviews previous research regarding EA for smart cities, and suggests a standardization for Smart cities, but I can’t relate this to my project as my project doesn't deal with smart cities.
A CONCEPTUAL ENTERPRISE ARCHITECTURE FRAMEWORK FOR SMART CITIES A survey based approach Definitions and goals Smart city: “A city well performing in 6 characteristics, built on the ‘smart’ combination of endowments and activities of self-decisive, independent and aware citizens”
Goals: Discover important quality properties for smart cities and propose a conceptual architectural framework for smart cities with these properties. This framework can be used as a starting point for actual smart city architectures.
Understand the current state in business aspects in relation to the IT support infrastructure for smart cities’ projects.
The survey Five groups of questions: Architectural relative questions Data sources Smart city management - organization and funding. Smart city management - critical issues/milestones Smart city management - project mission and objectives.
Concluding this Section The most prominent quality drivers that we need to consider are in the order of importance: Interoperability; Usability Authentication and Authorization Availability Recoverability; Maintainability Confidentiality (should be possible).
The framework Identify Prominent Architectural drivers and Select architectural patterns per driver Interoperability – API Façade
Useability – Model View Controller (MVC) pattern
Authentication and Authorization –Integrated application + Layered Architecture pattern
Availability and Recoverability – Messaging Architecture pattern
Maintainability – Layered Architectural pattern
Apply pattern to pationing the system the application these patterns to partition the system. The result is the conceptual application architecture framework
Assess impact on drivers: Assess if framework has desired impact on architectural drivers
Interoperability – Web Services (WSDL) interface at the Business Logic layer Useability – Access from different channels Authentication and Authorization - Application’s and web server’s provided mechanisms Availability and Recoverability – smart city integration host Maintainability – Layered architectural style + use of messaging
Conclusion Identified important quality properties for smart cities Proposed conceptual architectural framework The framework can be used as a starting point but needs tailoring Created an understanding of the current state in business aspects in relation to the IT support infrastructure for smart cities projects
Reflection How is this relevant to my project? The survey uncovered different quality drives for the smart city architecture that might be relevant to my choosing of architecture. The survey also revealed preferences on architecture patterns per drive, which again gave me a clue to which I might select.
A Framework for a Smart City Design: Digital Transformation in the Helsinki Smart City Introduction: Smart city initiativ goals: Streamlining processes Make city services more accessible Enhance resource management efficiency Reduce the cost of city services Improve the return on investments Accelerate economic growth, competitiveness and transparency Foster knowledge creating Enhance social inclusion Prevent inequality among citizens
Objective of this paper: Shed light on the elements relevant for robust digital transformation, ecosystem creation and orchestration in a smart city
Digital transformation: Perceived as a paradigm shift Technology-induces change Ubiquitous impacts on organizations and industry functions Strategic focus needed for long-term digital transformation Specific digital strategy for organizations Digital strategy a holistic view
Framework for a smart city design:
Strategy - capabilities: Strategy for a digital or smart city Identifies changes national and global Considers the impact of social and technological changes Envisions future state of city Sets guidelines on how a city must develop Integrates digital technologies to infrastructure Climate change and emission Considered the goals, resources and capabilities Capabilities Technical and human Technology - Digital technologies and data Digital technologies Emerging digital technologies rapidly expanding Rapidly increasing online city services ICT connected city infrastructures Fast adoption of Internet-connected technologies Cloud computing Data Open city data Capability to process and analyze city data needed Technology - experimentations in smart cities Technology experimentations in smart cities Cities must develop and apply urban experimentation policies City-level experiments enable iterative technology and service deployment Ten relevant dimensions for robust smart city technology experimentation platforms: Openness Real-world experiments User/public involvement Vertical and horizontal scope Scalability Sustainable value creation Continuity IoT/data heterogeneity System Architecture design Technology - security and privacy - horizontal and vertical scope Security and privacy Increase in the potential for security and privacy vulnerabilities Security and privacy important Vertical and horizontal scope Vertical scope - specialization Horizontal scope - variety Focusing on verticals may lead to data silos Enabling ubiquitous access to heterogeneous and interconnected city data Governance Smart city governance A body that envisions the future state of the smart city Provides strategic leadership and resources Ensures dialog and decision making in smart city ecosystems Assesses the performance of a smart city and the quality of its citizens’s lives Consider long term financial needs Funding Major investments needed EU allocation funding to improve infrastructure Metrics How to evaluate the performance of a smart city Guidelines and key performance indicators are developed Smart city standards provide step-by-step guides to transit a city towards being a digitized smart city Stakeholders Smart city stakeholders Collaborative innovation ecosystems Enterprises using cities to experiment Public-private dominated Integrating citizens and civil society Quadruple helix Stakeholder value Smart city projects tend to decline after funding is obtained Smart city development, a long-term process, require added value for stakeholders Methodology Foundation for the framework presented by Hämäläinen & Tyrväinen(2018) Data obtained by interviewing persons and stakeholders involved Additional data collected from workshops and seminars, as well as reviewing official Helsinki data
Helsinki: The most functional city in the world Strategy of the Helsinki Smart City Smart Kalasatama (neighbourhood in Helsinki) Facilitated by Forum Virium Helsinki (FHV) Helsinki commits to take concrete actions to produce high quality city services with strong citizen inclusion Trust safety and social coherence
Helsinki aims to improve its personnel’s capabilities in emerging digital technologies like AI Robotics and Smart Education
Technology: Data The city actively experiments and benefits from data analytics, AI sensor and IoT technologies in multiple city domains Key Issues The content of data How information is distributed to relevant target groups How information is utilized in decision-making processes The concept of open data was introduced to the Helsinki administration in 2009 Technology experimentations Forum Virium Helsinki (FVH) Helsinki will be an attractive and leading city for agile smart city technology experimentations, thereby stimulation new business activities in the city 2015-2018, FVH har organized 21 agile smart city technology and service experimentations in Kalasatama Smart-mobility services Effective waste management Food waste reduction Fail fast, learn fast Vertical and horizontal scope Mobility-as-a-service is one of the most extensive efforts that have taken place in Helsinki Whim Common mobility app for city bus, taxi, car and bike share Security and privacy New ICT training programs must focus on smart city development by enhancing security and privacy issues in diverse city domains City lawyers are used to consulting diverse city organizations Governance General The notion of a smart city is related too the manner in which cities govern their ICT systems and data and how they integrate new digital technologies into city infrastructure. There is no organization that governs the development of the Helsinki smart city and the related initiatives. Development should progress from agile pilots to a more mature smart city governance approach Funding and metrics Smart Kalasatama is funded by Helsinki The agile smart city pilots and experimentations are funded by diverse EU funds In addition, local and national public organizations have participated and invested in the Helsinki smart city pilots None of the international smart city standards are applied in Helsinki Estimated that open procurement data has resulted in 1-2% savings in city procurement activities
Stakeholders Stakeholder value FVH’s role is to be facilitator during agile pilots and the goal is to start agile pilots that must create value for the stakeholders of a smart city Stakeholders experiences contributes to the success of agile pilots and willingness to participate in pilot activities Stakeholders enjoy the increased transparency that Helsinki open data gives, and benefits of internal saving and resource efficiency The open data hopes to stimulate new businesses and improve the competitiveness of companies. Summary The smart city design framework considered Helsinki smart city through four dimensions: Strategy Emphasizes digitalization, user-centric development, civic society engagement and agile technology pilots. Technology Manages to create a specific experimentation culture for novel digital technologies like IoT solutions and data usage within diverse city organizations Governance Stakeholders The development of a smart city in Helsinki is rather scattered, which makes the governance of the smart city confusing Numerous Helsinki smart city initiatives are funded through diverse EU funds, Helsinki city and private organizations.
Big data driven multi-tier architecture for electric mobility as a service in smart cities Introduction eMaaS Electric Mobility as a Service There is an increase in urban residents causing need for better transportation eMaas will mitigate(lessen) environmental issues Results in noise reduction Interoperability Wish to connect current applications into one. Wish for standardized approach to accessing data
Big Data Data collected from: Citizens Sensors companies API Today there are very many different formats, which results in little interoperability
There is a need for one common approach Multi layer Architecture A combination of the following:
STS - Socio-technical systems Technical and social aspects must work together Organizational Social Technical Human factors
ANT - Actor network theory Examine the relationship between human and non-human Actor Links Network Action
Layer architecture of digital technology Content Services Networks Devices Combined - Multi-tier architecture Context Service Business Application and data processing Data space Technologies Physical infrastructure
Proposed architecture - layers Context Main feature → eMaaS Stakeholdes Main target → Ease of transport + Reduce polution Service All individual services that ensure mobility Provide communication module between municipalities transport companies other parties offering mobility services Aids trusted third-party mobility data providers Routing location Weather services Business Strategies by each enterprise to reach goals of sustainability Create Virtual Enterprise to align with businesses' approach to provide a medium for IT. Application and data processing Software and APIs used to provide eMaaS services Integrates APIs to process, provide and manage eMaaS data Should provide trusted software to citizens to push and pull transport information Layer facilitates developers with existing API to use in new eMaaS applications. Data space Comprises of all types and sources of data Deploys variety of datamanipulation, storage and management to maintain data continuum Contains both SQL and non-SQL databases Historical mobility data Technologies Software and hardware infrastructure Process data from physical devices Describes how data layers are linked Physical infrastructures Physical devices Collects data Data transferred to technology layer
Research methodology Methodology Identify problem and motivate Define objectives of a solution Design and development Demonstration Evaluation Communication
The interview: Steps: Thematization the Interview Design the interview Conducting the interview Transcript of recording Analysing of transcript Verifying follow up with informants Prepare interview data
Conclusion Multi-tier architecture is applicable APIs foster innovation and ease of use Enables new opportunities Potential improvements
Reflection How is this applicable to my task? It isn’t, and I have no idea how to reflect over this papers finding
The City as a Service Platform: Typology of City Platform Roles in Mobile Service Provision Introduction Explores roles of city governments in the platformization of the mobile services industry. Takes an experimental approach that applies existing typology for mobile service platforms to the context of the city. Forms a starting point for research into platform strategies in the context of the city Four city platform types Enabler Integrator Neutral Broker 1. Goal Verify whether a general typology or mobile service platforms would hold up to scrutiny in the more applied and specific context of the city and to what extent city agencies could take up platform roles within the value network
- Framework Four types of mobile services Enabler Platform owner controls many or most of the assets involved in mobile service provision, but leaves the customer relationship to third-party developers Integrator Closed approach where the platform owner controls service development and distribution Neutral platform owner does not control most of the assets necessary for the value proposition and on top of this does not have customer ownership. Broker The platform relies on other actors that control most of the assets for establishing the value proposition, but does integrate customer ownership.
Table: Mobile service platform typology
- City platform typology Smart city definition: “We believe a city to be smart when investments in human and social capital and traditional (transport) and modert (ICT) communication infrastructure fuels sustainable economic growth and high quality of life, with a wise management of natural resources, through participatory governance.”
Four types of city platforms: Enabler City providing open data and statistical information to interested developers. Integrator Closed approach where the city controls service development and distribution. Neutral City not taking any initiative to deploy mobile services: leaving the initiative to private projects Broker City operates a platform that hosts personal information on its users, but is nott involved in developing the services benefiting from it.
Conclusion We can clearly define platform roles that are being taken up by the cities in different parts of the world The different roles have their own merits and consequences that would need to be explored in greater detail in future research The applied topology can be used as an initial tool for city governments to consider their own role within the value network and the potential platform dynamics at play when they are involved in mobile service provision Future research will establish whether there are crucial gatekeeping platform roles at play in the creation and provision of mobile services in the context of the city A clearer definition of what control over assets and customers eans in the city context required
Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities Introduction Connecting everyday objects via existing network highly favorable Smart city is an application of the IoT UN projected 66% of the world population to be urban by 2050 75% of total energy is consumed by cities This consumption generate 80% of greenhouse gases Smart city is the ideal solution to urbanization challenges
Features of a smart city Smart city comprises of: Attributes - characteristics of a smart city Themes - the pillars of the smart city Infrastructure - provides the operational platform
Characteristics of a smart city Four main attributes Sustainability Quality of Life Urbanization Smartness
Pillars of a smart city Institutional infrastructure Governance Technocratic governance Physical infrastructure Natural resources Manufactured infrastructure Social infrastructure Intellectual capital Human capital QoL Economic infrastructure Smart economy
Smart city architecture Sensing layer Data collection Collecting data concidered the most important role but also the most challenging task Captures all types of data from all types of sensors and devices Transmission layer Carries data to upper layers Acts as the backbone of ant smart city architecture Convergence of various communication networks Consists of various types of wired, wireless, and satellite technologies Data management layer The brain of any smart city Performs a variety of data manipulating, organizing, analyzing, storing, and decision-making tasks. Maintains vitality of data Derived decisions are conveyed to the application layer to execute Application layer Mediates between urban citizens and data management layer Key services: Community development Grid distribution Smart transportation Weather forecasting Information sharing between applications a promising approach Composition of smart city Varies between cities and often synergies between areas Smart community Aspire to uplift citizen satisfaction and well-being Smart buildings, water and waste management Smart building connected with smart grid Green buildings and smart waste Smart hospitality Smart Transportation Already seeing this transformation Will be safer for both passengers and riders Congestion control Synergies with other smart applications No need to own car Other types, such as drones Smart healthcare Combined with transportation, analytics of blood samples Highly empirical field, better diagnosis Remote surgery Automatic surgery Smart energy and interconnectivity Smart green energy production Predicting future demand Enormously important to have all interfaces talking with eachother
Smart cities in the world City In Motion Index (CIMI), 77 indications, 10 categories. 181 cities with NYC London and Paris at the top. Very unevenly spread. London One million population growth over the last decade London data store, first open access to public data Congestion control, smart money, smart waste management Data collection, management and application layer Smart energy and smart healthcare San Francisco Greenest city in North America Smart buildings, extended transportation system, centralized waste Innovative waste management main application (zero landfill waste by 2020) Autonomous, shared electric vehicles Extensive data collection, with connected transport, pedestrian crossing and traffic signals. Santander City, Spain Part of SmartSantander project Extremely large framework for research expreiments on smart cities and IoT. Largest testbed for IoT applications The city employs more than 12,500 sensors Available parking, remaining volume of trash, pedestrian crossing, and more Has separate device layer compared to other architectures Challenges and opportunities Design and maintenance cost Isolated data - how should it be accessed, processed and personal lives protected? Fault tolerance Opportunities because of Green City Advances of big data processing Reflection How is this relevant to my task? The paper talks about E-commerce and e-business Smart building could be a part of my application, providing smart solutions to their housing. This way they can control their housing from afar, like heating up before guests arrive. This is also part of the smart hospitality component, but this is not mentioned in the article.
Standardization of enterprise architecture development for smart cities Introduction What are smart cities: Smart cities are innovative cities which use ICT to facilitate daily activities of the citizens to improve their QoL. Smart cities are dealing with complexity of ICT services Many EA frameworks introduced to manage complex information systems, processes and infrastructures EA framework for smart cities should consider specific concerns for stakeholders and improve their QoL. This framework contains two new layers
Context layer: To capture the smart city context information about strategies, priorities, and other critical aspects (e.g. stakeholders and their concerns) to deliver effective services to the citizens.
Service layer: To define appropriate goals, scope, etc. for the services with regard to the smart city requirements, concerns, and priorities.
ADM (Architectural Development Method) – A process for creating an enterprise architecture that is part of the TOGAF standard.
application architecture – The architecture of a specific application.
architect – One whose responsibility is the design of an architecture and the creation of an architectural description.
architecture – The fundamental organization of a system embodied in its components, their relationships to each other, and to the environment, and the principles guiding its design and evolution (from IEEE-1471-2000).
architectural artifact – A specific document, report, analysis, model, or other tangible that contributes to an architectural description.
architectural description – A collection of products (artifacts) to document an architecture.
architectural taxonomy – A methodology for organizing and categorizing architectural artifacts.
architectural framework – A skeletal structure that defines suggested architectural artifacts, describes how those artifacts are related to each other, and provides generic definitions for what those artifacts might look like.
architectural process – A defined series of actions directed to the goal of producing either an architecture or an architectural description.
architectural methodology – A generic term that can describe any structured approach to solving some or all of the problems related to architecture.
business architecture – An architecture that deals specifically with business processes and business flow.
business reference model (BRM) – A FEA term that gives a business view of the various functions of the federal government.
business services segment – A FEA term that refers to a segment that is foundational to most, if not all, political organizations, such as financial management.
capability – A collection of business functionality that works together to deliver some specific business value.
capability centric approach – An approach to enterprise architecture that focuses on analyzing the capabilities of an organization with the goal of maximizing the value that each returns.
CIO — Chief Information Officer, the executive in charge of information technology in a corporation.
CIO Council – A council consisting of CIO’s from each of the federal governmental agencies that coordinates work related to common interests.
Clinger/Cohen Act — See Information Technology Management Reform Act.
common object request broker architecture (CORBA) – A component-oriented system designed and evangelized by the OMG.
common systems architectures – A TOGAF term referring to an architecture that are common to many, but not all types of enterprises. In contrast to foundation architectures and industry architectures.
component reference model (CRM) – A FEA term that gives an IT view of systems that support business functionality.
data architecture – The architecture of the data (typically stored in databases) owned by the enterprise.
DCOM - A component-oriented system designed and evangelized by Microsoft.
enterprise architect – An architect who is who specializes in enterprise architectures.
enterprise architecture — An architecture in which the system in question is the whole enterprise, especially the business processes, technologies, and information systems of the enterprise.
enterprise service – A FEA term referring to a well-defined function that spans political boundaries, such as security management.
FEA – See Federal Enterprise Architecture.
FEAF — See Federal Enterprise Architectural Framework.
FEAPMO – The organization within the OMB that owns and administers the Federal Enterprise Architecture.
Federal Enterprise Architecture – An architectural description of the enterprise architecture of the U.S. federal government that includes various reference models, processes for creating organizational architectures that fit in with the federal enterprise architecture, and a methodology for measuring the success of an organization in using enterprise architectures.
Federal Enterprise Architectural Framework (FEAF) — An enterprise architectural framework used by the United States federal government to describe how the various governmental agencies and their IT systems are related to each other.
Federal Architecture Program EA Assessment Framework – A benchmark used by the OMB to measure the effectiveness of governmental bodies in using enterprise architecture.
foundation architecture – A term used by TOGAF to refer to the most generic of architectures that can be used by any IT organization. In contrast to common systems architectures.
GAO — See General Accountability Office.
Gartner – An IT research and advisory organization.
gateway — A transfer point of an autonomous system from which messages from the outside world are received or through which messages to the outside world are sent.
General Accountability Office — A branch of the United States Government that is responsible for monitoring the effectiveness of different organizations within the U.S. Government.
industry architecture – A TOGAF term that refers to a architecture that is common to most enterprises within an industry. In contrast to a common systems architecture and an organizational architecture.
Information Technology Management Reform Act — An act passed by the United States Congress in 1996 that requires all governmental organizations to use effective strategies and frameworks for developing and maintaining IT resources.
OMB (Office of Management and Budget) – Part of the Executive Office of the President of the United States which serves the function of presidential oversight on federal agencies.
organizational architecture – A TOGAF term that applies to an architecture that is specific to a particular organization. In contrast to an industry architecture.
performance reference model (PRM) – A FEA term that gives standard ways of describing terms related to measuring value.
perspective centric approach – An approach to enterprise architecture that focuses on aligning different organizational perspectives.
process centric approach – An approach to enterprise architecture that focuses on creating a well defined process for modeling the enterprise.
Return on Investment — A measure (in percent) of the business value of a project based on the increase in profit (either because of increased income or decreased expenses) divided by the cost of the project. For example, a project with a cost of