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The disjointness graph G = G(𝒮) of a set of segments 𝒮 in ${\mathbb{R}^d}$, $$d \ge 2$$, is a graph whose vertex set is 𝒮 and two vertices are connected by an edge if and only if the corresponding segments are disjoint. We prove that the chromatic number of G satisfies $\chi (G) \le {(\omega (G))^4} + {(\omega (G))^3}$, where ω(G) denotes the clique number of G. It follows that 𝒮 has Ω(n1/5) pairwise intersecting or pairwise disjoint elements. Stronger bounds are established for lines in space, instead of segments.
We show that computing ω(G) and χ(G) for disjointness graphs of lines in space are NP-hard tasks. However, we can design efficient algorithms to compute proper colourings of G in which the number of colours satisfies the above upper bounds. One cannot expect similar results for sets of continuous arcs, instead of segments, even in the plane. We construct families of arcs whose disjointness graphs are triangle-free (ω(G) = 2), but whose chromatic numbers are arbitrarily large.
This paper presents a robust adaptive impedance controller for electrically driven robots using polynomials of degree N as a universal approximator. According to the universal approximation theorem, polynomials of degree N can approximate uncertainties including un-modeled dynamics and external disturbances. This fact is completely discussed and proved in this paper. The polynomial coefficients are estimated based on the adaptive law calculated in the stability analysis. A performance evaluation has been carried out to verify satisfactory performance of the controller. Simulation results on a two degree of freedom manipulator have been presented to guarantee its successful implementation.
Policy-making in local public administrations is still largely based on intuition rather than being backed up by data and evidence. The goal of this work is to introduce the methodology and software tools for contributing toward transforming the existing intuition-based paradigm of policy-making into an evidence-driven approach enabled by heterogeneous sources of data already available in the city. More specifically, methods for data collection, efficient data storage, and data analysis are implemented to measure the economic activity, assess the environmental impact and evaluate the social consequences of certain policy decisions. Subsequently, the extracted pieces of evidence are used to inform, advise, monitor, evaluate, and revise the decisions made by policy planners. Our contribution in this work is on outlining and deploying an easily extendable system architecture to harmonize and analyze heterogeneous data sources in ways that are found to be useful for policy-makers. For evaluating this architecture, we examine the case of a controlled parking system in the city of Thessaloniki and try to optimize its operation by balancing effectively between economic growth, environmental protection, and citizen satisfaction.
Boolean functions are essential to systems for secure and reliable communication. This comprehensive survey of Boolean functions for cryptography and coding covers the whole domain and all important results, building on the author's influential articles with additional topics and recent results. A useful resource for researchers and graduate students, the book balances detailed discussions of properties and parameters with examples of various types of cryptographic attacks that motivate the consideration of these parameters. It provides all the necessary background on mathematics, cryptography, and coding, and an overview on recent applications, such as side channel attacks on smart cards, cloud computing through fully homomorphic encryption, and local pseudo-random generators. The result is a complete and accessible text on the state of the art in single and multiple output Boolean functions that illustrates the interaction between mathematics, computer science, and telecommunications.
This chapter is about managing expectations and describing the features of the Gartner hype cycle. It also explores an approach to the DIKW (Data – Information – Knowledge – Wisdom) pyramid and how to deliver early incremental value to the business in a strategic context.
The Trough of Disillusionment
We have previously talked about the issue of the ‘hype cycle’ when discussing the ability of the new CDO to shift between the tactical and the strategic. The hype cycle is a Gartner tool to represent the maturity, adoption and social application of specific technologies. It claims to provide a graphical and conceptual presentation of the maturity of emerging technologies through five phases: technology trigger, peak of inflated expectations, trough of disillusionment, slope of enlighten ment, plateau of productivity. It has been criticised, not least for not being a cycle:
The Gartner hype cycle has been criticised for a lack of evidence that it holds, and for not matching well with technological uptake in practice.
(Wikipedia, March 2020)
However, the idea can also help us to understand the challenges facing a new CDO, and to frame the first 100 days and beyond.
Currently, the CDO role is relatively new in many organisations, and, even if it is not, the CDO will arrive into an atmosphere of great expectation. There will be common sentiments that will greet you: ‘the business will be transformed into a data-driven business, an organisation capable of making better and more informed decisions based on data; data science will bring the business better insight into its customers and operations; the new CDO will bring big data’. The organisation's data risks, on the enterprise risk register, may even list the arrival of the new CDO as the mitigation.
There will be great expectations about the arrival of the CDO; there will also, in most cases, be a lot of goodwill and enthusiasm in the business for data success. One of the biggest threats to you – certainly in the first 24 months or first 1½ financial years – is the Trough of Disillusionment in the hype cycle.
We started the preface of the first edition of this book with a short anecdote to set the scene; since then, much has changed. The ecosystem of the CDO has evolved, there are more CDOs and more organisations are trying to get their data under control and to leverage its value. However, that initial anecdote still is very relevant, so here goes.
We were on a panel at a conference discussing how to harness value from data − we’ve changed the discussion topic slightly so as to not identify the conference, event or other participants; to protect the ‘notso-innocent’. This topic, or a closely related one, has been a regular feature of the panels and discussions we’ve been involved with. It seems everyone is trying to get to the heart of that question and find the answer. Data has been seen as such an inconsequential thing, that just seemed to be there, in the past; but there is a growing respect for data as a really fundamental asset − which is a great thing.
Everyone knows, because we’ve all been told many times recently, that data is the new oil, or perhaps the new soil, the new sun, the new water, we’ve even heard a comparison to bacon. The question that then leads out of this is the one we have been facing: if data is the new oil, how does an organisation get value out of it? It is all very well having struck oil, but if you don't know how to get it out of the ground, or how to refine it into useful products, or that it can be transformed and manufactured into valuable products or consumed to create energy – what use is the oil in the ground? To be frank we really hate data is the new oil, because data is data and the analogy only goes so far before it falls really short on highlighting the power of data.
On that panel we began by responding to some prepared questions. There were some great and experienced minds on the panel: leaders in their respective fields and all practitioners from the hard edge of industry, business and commerce.
This chapter poses a number of questions: are you an FCDO or an SCDO? CDOs come from a wide spectrum of skills and experience: where are you on that spectrum? What are your strengths and weaknesses? We discuss the importance of addressing these questions. The questions may be too simple, or perhaps the answers more complex than it might seem. There are several features that will determine what type of CDO you are.
What sort of CDO?
Looking at one aspect, which we have discussed already, are you an FCDO, SCDO or TCDO? Each of these is very different, regardless of their background, expertise or sector. The difference is very much around what type of person you are. In very simple terms, as an FCDO you will probably arrive in post with no existing team, reports or support. It may well be that you don't even have a desk because your role hasn't existed before. The FCDO isn't on the auto-invite for the many meetings and boards that they need to be on, so the role is often a lonely one for a while: the person in that role has to be resilient, able to think and motivate themselves alone, and to be very outgoing, to win the hearts and minds within the organisation. You would really struggle with this role as a shrinking violet. The SCDO and TCDO can perhaps be more low key, even though they will want to make their own mark; they will at least have a warm desk and a team to welcome them, and perhaps a budget. The organisation should already understand their value and the types of return on investment that they can bring.
CDOs come from many backgrounds and have a variety of skills. It is worth spending some time to consider what sort of CDO you are. What sort of CDO will you be, or wish to be? Or, if you are running a business, what sort of CDO do you want, or what sort do you wish to recruit? It is especially important to understand this, both for the recruiter and for the recruit; this will be make or break, both at interview and in post.
This chapter explores the idea that the CDO is different to the Chief Technology Officer (CTO) or Chief Information Officer (CIO) and discusses the relationship that the CDO might have with the Chief Executive Officer (CEO). The key role of the CDO and data ownership is examined. This chapter is aimed at the business stakeholders.
There are more C-Suite roles than there used to be. The longestablished roles of Chief Executive and Chief Information Officer now have to compete for room at the table with roles like the Chief Information Security Officer, Chief Operating Officer, Chief Finance Officer, Chief Customer Officer, Chief Digital Officer and, of course, the Chief Data Officer – it's getting a bit crowded around the table.
Key relationships
Relationship building is a key skill for the CDO. Working with the data means you, the CDO, are cutting across the silos in the organisation and therefore potentially messing around in everyone's backyard, so you had better be able to ask nicely before you do, or have some air cover for when an area feels pain for the greater good! While the CDO needs to form a working relationship with any other stakeholders in the company, not just the rest of the C-Suite, the one that causes the most concern is the relationship with CIO or CTO; it definitely generates the most questions at conferences. Of course these roles and their scope vary from organisation to organisation.
The difference between a CIO and CDO (apart from the words ‘information’ and ‘data’) is best described using the bucket-and-water analogy. The CIO is responsible for the bucket (the technology), ensuring that it is complete, without any holes in it, that the bucket is the right size, with just a little bit of spare room but not too much and it's all in a safe place. The CDO is responsible for the liquid (the data) you put in the bucket, ensuring that it is the right liquid, the right amount, and that it is not contaminated. The CDO is also responsible for what happens to the liquid; making it available when it's needed. In this analogy the CIO has a responsibility to make the water accessible to the CDO (the business).
This chapter suggests that all organisations hoard data. It goes on to explore why we hoard data, where we store this data and the nature of ‘dark data’. The chapter provides some suggestions for cutting through the hoarded data and the dark data and looks at the importance of counting the value of the data we do have.
The hoarding mentality
Have you ever watched those programmes on TV where a person is labelled a ‘hoarder’? There tend to be various interviews with friends and family who are worried about the person and then pictures showing the person's home, which is usually so full of stuff that it is not fit to live in. You then see the person themselves, who sometimes recognises the problem, but not to the same extent that their nearest and dearest do. Normally they have found a way to make their home work as far as they are concerned: there are paths around the piles of things, as long as you pull in your stomach and walk sideways, and the oven makes a much better cupboard than it did a cooking implement, so cold food works just fine. If you watch them, though, you can tell that deep down they know that this isn't how most people live, but are in denial about the amount of time they are sitting in discomfort and working around a situation which, to outside eyes, could be easily solved. Most of us have tendencies in this direction: those shoes, tools or drawers full of bits that you keep just in case. Every single one of us must have experienced that feeling when you suddenly need something that you threw away the day before, because you had been storing it for so long and had never needed it, and so resolve to be more patient with your storage needs next time.
However, compulsive hoarding (which is what these individuals suffer from):
… is a pattern of behaviour characterised by excessive acquisition and an inability or unwillingness to discard large quantities of objects that cover the living areas of the home and cause significant distress or impairment. Compulsive hoarders may be aware of their irrational behaviour, but the emotional attachment to the hoarded objects far exceeds the motive to discard the items.
(‘Compulsive hoarding’, Wikipedia, the free encyclopedia)
This chapter explains how data governance can help and not hinder the business; in fact, how data governance can drive innovation. The elements of good data governance are outlined, and how good data assurance can keep the data strategy and business on track.
Data governance and data protection
Data governance is one of the pillars of a data strategy and a large part of the CDO's task and responsibilities. Why are we singling out data governance in particular for its own chapter in this book, and not master data management, metadata or some other core deliverable in a data strategy?
The answer is twofold. First, it could be argued that data governance is the underpinning principle of any data capability: it is fundamental to the work of a CDO. Second, the introduction of GDPR in May 2018 brought data governance into sharp focus, and the role of the Data Protection Officer (DPO) within organisations is worth some examination in relation to the CDO; as the legislation has become more embedded, so the role has evolved and become more understood. So, the first reason for examining the CDO's role in data governance is the importance of the business outcomes that effective data governance provides and the second reason is regulatory pressures.
In fact, since the first edition of this book more countries are taking the regulation of data protection much more seriously. Various African nations have introduced (or are reviewing) amendments to their 2004 law on the protection of personal data which strengthen the rights of the individual with regard to their data. US states such as California, with ‘the California Consumer Privacy Act’, seek to establish an enforceable right of privacy. Canada has also reviewed and changed some of its privacy regulations, and the list goes on.
Not only have regulations been updated (and tightened) but they are also, in our opinion, being taken much more seriously. Equifax agreed to pay a fine of $575 million because not only did they fail to fix a critical vulnerability months after a patch had been issued, but they then failed to inform the public of the breach for weeks after it had been discovered.
To say the world has moved on a bit since the first edition of this book would be an understatement; the world of data has moved even faster and continues to do so, and that rate of forward movement seems to be accelerating. The leaders are leading from a greater distance and others are falling behind. Data is becoming the differentiator. It is probably more nuanced than that. Where organisations have embedded data deeply into the heart of their change, transformation and business processes then that has become the true differentiator in the markets and verticals. We still hope that this book has done what it aimed to do, which was to share our knowledge and the knowledge of the countless data professionals we work with in order to help you. We have enjoyed and been privileged to beg and borrow knowledge from our fellow data professionals, who have been most generous with their time and ideas, and we both know we have added massively to our own experience and learning through this process. There were also times that we both wondered why we thought this would be a good idea again, but thankfully they were relatively few and far between! On the contrary, we have found this a rewarding and stimulating exercise. We’ve listened a lot over the past two years, and it has been interesting and encouraging to note that there are now more, and an increasing number, of well-informed voices to listen to.
This excerpt from the first edition is as true now as it was then – data is still an exciting place to be and we feel even more strongly how lucky we are.
We strongly believe that data is the catalyst for innovation and transformation and that it will reshape the way that organisations are structured and how they operate. A successful organisation will be one that collects the right data, stores it well, makes it accessible to the business and uses it to gain insight and wisdom, enabling it to make accurate and powerful decisions. Furthermore, we believe that organis - ations need a Chief Data Officer, a specialist data professional, to deliver this data capability to drive the innovations and transformations that the organisation requires.
This chapter is mostly aimed at the CDO, to help you understand and appreciate the skills and characteristics that are required to be a CDO. However, it is also a useful chapter for organisations thinking about recruiting a CDO – what sort of skills should they be looking for? To that extent, this chapter is also useful for recruiters when trying to assess potential candidates. The chapter emphasises the necessity for the CDO to have ‘narrative powers’ and lists the seven secret ingredients of the CDO. It introduces for the first time in the book the concept of ‘first-generation CDO’ and ‘second-generation CDO’. The firstgeneration CDOs are those taking up roles in organisations which haven't previously had a senior function responsible for data and a data strategy, whereas the second-generation CDO builds upon the firm foundation created by the first-generation CDO and generates more value for the organisation. In this second edition we also introduce the concept of the ‘first-generation CDO – replayed’.
The CDO's role
The role of the CDO is evolving fast. In one type of organisation compliance and regulation may lie behind the creation of the role, whereas in another the CDO is there as a response to business model disruption and the need to drive innovation.
(Emanuela Aureli, Spencer Stuart)
Compared to most of the C-Suite colleagues, the CDO is faced with a set of unique problems. There are some similarities: the CDO is a subject specialist, and in that respect is similar to the Chief Finance Officer, Chief Investment Officer or Chief Risk Officer. The CDO also operates across the organisation and so has similarities with the Chief Operating Officer or Chief Accounting Officer. However, the CDO does have a unique set of challenges: primarily, the role is still being defined and, in the absence of certainty, there is an assumption that the role will solve all the problems the organisation is facing. The CDO in many organisations is a new role (the number of people in CDO roles doubled between 2013 to 2014, and probably doubled again in 2015 – Karl Greenberg, MediaPost 2015), while the other C-Suite executives have roles and responsibilities which the organisation recognises and understands.
This chapter examines the idea that there are two types of CDO; the first-generation CDO (FCDO) and the second-generation CDO (SCDO). We go on to discuss their roles and deliverables.
An evolving role
The CDO is an evolving role and, as such, there are different ‘flavours’ of CDO, who are still all about the data but maybe come at the problem from different directions. We find there are few things in life where ‘one size fits all’, so why should we assume that one CDO will solve all our problems? The simple answer is that they won’t, and while there are many different varieties (being the wonderful, multifaceted humans we are), currently they can be loosely categorised into two groups: firstand second-generation CDOs. Before we jump into the current CDOs, we look at where the role came from.
Every C-Suite role had come from somewhere, believe it or not the CFO wasn't a core component of the strategic team. The very first CDO was in 2002 for Capital One, with a slightly eclectic responsibility for IT, Supply Chain and Market Analyses – nothing about getting value from the data. The banking industry picked up on CDOs faster than any other industry, focusing them on the governance side of the role, but by then the uptake of CDOs had begun. Data from Forbes shows that by 2012 only 12% of Fortune 1000 companies had a CDO, but by 2018 this had grown to just under 70%, and the number continues to rise. Countries are now getting the idea. France was the first European country to have a CDO, in 2014, closely followed by the UK in 2015. In 2019 every state in the US was tasked with having a CDO of their very own, so it's fair to say that the role is more established. However, this hasn't stopped the evolution of the role and, as more people from varied backgrounds bring their experience to bear, the role will continue to evolve. As we discussed in Chapter 2, this evolution has even resulted in the FCDO Replayed. Perhaps this is even a re-evolution.
You know those dreams you have when you are a kid, before you realise that the moon isn't made of cheese and there is only so much your dad and superglue can fix? Well, for me one of those dreams was to be an author. Putting words down on paper has always felt more like a joy than a job (until you get to the editing process and please don't get me started on that). I have to be honest and say that The Chief Data Officer's Playbook isn't the kind of book that young me envisaged writing. However, the night we had our book launch was literally one of the proudest moments of my working life.
It all started at a data conference – where else? When Peter and I were talking at a conference about writing a book together I assumed that the suggestion would be one of those great ideas that fade in the light of the real world. Only this one didn’t, it became a persistent thought that would lead me and Peter down a path neither one of us would foresee. That book became The Chief Data Officer's Playbook, which was our summation of all the things a CDO needed to know, and it resonated with so many of our colleagues and future data leaders that we were humbled by the response to it. We realised that we had missed something. It was great that the first book was a data book for data leaders, but what about the other leaders? Hence we wrote our second book, Data Driven Business Transformation, to help spread the message. Then the world shifted so fast in the data space we felt compelled to update The Chief Data Officer's Playbook (the book you have in your hands, in case you were wondering) to make sure that it stayed relevant to the world around us.
Somewhere along the line we were asked for advice from people and companies that we really wanted to help, but with us both in full-time employment it was literally impossible to help everyone and still do a decent job for the people who were paying us, so we knew something had to change.