Building a More Resilient, Data-Driven Economy

Irving Wladawsky-Berger

Today we face two simultaneous disruptions: one is the COVID-19 pandemic and resulting economic shock, and the second is the rise of pervasive digital data, crypto systems, and artificial intelligence (AI).” T he two disruptions are highly interrelated. Similar questions are now being raised regarding data and AI. Who controls the vast amounts of data required to train deep learning algorithms and ensure that they do what we want them to do ? Data and AI: A new ecology.

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The Emerging Data Economy

Irving Wladawsky-Berger

The Economist’ s May 6 issue referred to data in its cover as the world’s most valuable resource. Similarly, data centers “power all kinds of online services and, increasingly, the real world as devices become more and more connected.”. Data has been closely intertwined with our digital technology revolution since the early days of the IT industry. But, data science should not only be framed in terms of the digital revolution of the past few decades.

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Data

Stephen Downes: Half an Hour

Responding to Cooperative Catalyst, Metrics and "Success" I think data is important (it's the only evidence we have!) but I think that people take a very narrow view of data, which is unfortunate. Instead of attacking the data - which leaves you with no ground to stand upon - it makes more sense to attack the simple-mindedness.

Data 160

Big, thick and rich (the data)

Dave Snowden

Now when you talk to people about mass distributed sense-making you often hit the Big Data argument. Give me a bright mathematician, technology tools and lots of data and I create meaning without effort. Tricia Wang, in a medium article that triggered this post argues for thick data to complement big data and the first of the two illustrations above is from that article. The post Big, thick and rich (the data) appeared first on Cognitive Edge.

Data 180

Data is the New Love

Doc Searls

Personal data, that is. I bring this up because a quarter million pages (so far) on the Web say it “data is the new oil.” ” That’s because a massive personal data extraction industry has grown up around the simple fact that our data is there for the taking. As a result, we’re at a stage of wanton data extraction that looks kind of like the oil industry did in 1920 or so: It’s a good metaphor, but for a horrible business.

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Traditional Data Analysis and Data Science

Irving Wladawsky-Berger

Among other questions, moderator Michael Hickins , - a senior editor at the Wall Street Journal and editor of its online CIO Journal , - asked the panel to discuss the difference between the business intelligence and analytics approaches of the past twenty years and the emerging discipline of data science. . In my opinion, data science should be viewed as a multidisciplinary evolution from business intelligence and analytics.

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Big Data Takes Center Stage

Irving Wladawsky-Berger

A few recent articles have expressed concerns that big data may be at the peak of inflated expectations in the so-called hype cycle for emerging technologies, and will soon start falling into the trough of disillusionment. So is big data. . The article is adapted from their book Big Data: A Revolution That Will Transform How We Live, Work, and Think published in March, 2013. Our new big data tools have the potential to usher an information-based scientific revolution.

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Towards a Trusted Framework for Identity and Data Sharing

Irving Wladawsky-Berger

As the economy and society move toward a world where interactions are primarily governed by digital data and transactions, our existing methods of managing identity and data security are proving inadequate. Large-scale fraud, identity theft and data breaches are becoming common, and a large fraction of the world’s population lacks the credentials needed to be part of the digital economy. Few institutions will let their critical data out of their premises.

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The Big Data Era Is Here

Irving Wladawsky-Berger

During the meeting, the TRB Executive Committee held a policy session on the impact of big data on transportation systems. Big data and related information-based disciplines, - e.g., data science , artificial intelligence , - are everywhere. Big data is part of both the digital revolution of the past few decades and the scientific revolution of the past few centuries. These devices generate massive amounts of data, with a lot more to come. Data Quality. “How

Data 180

Big Data, Science and the Humanities

Irving Wladawsky-Berger

In my opening statement I said that I strongly believe that digital technologies and the many data services they are enabling will make cities smarter and help transform them over time. Later, in my closing remarks , I pointed out that since the qualifier smart essentially means information-based or data-driven, the promise of smart cities is inexorably linked to the general promise of big data and data science , which some have felt are themselves being over-hyped.

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Cognitive Systems and Big-Data-driven Applications

Irving Wladawsky-Berger

The need for such systems is a result of the explosive growth of data all around us. Not only are we now able to collect huge amounts of real-time data about people, places and things, but far greater amounts can be derived from the original data through feature extraction and contextual analysis. players, - was that the very process of analyzing data increases the amount of data by orders of magnitude. . This is what data science is all about.

System 207

Data-Driven Decision Making: Promises and Limits

Irving Wladawsky-Berger

Given the explosive growth of big data over the past decade, it’s not surprising that data-driven decision making is one of the most promising applications in the emerging discipline of data science. . Equally succinctly, they view data science “as the connective tissue between data-processing technologies (including those for big data ) and data-driven decision making.”. Neither is good data-driven decision making.

Data 198

A Data Science Approach to Organizational Health

Irving Wladawsky-Berger

McKinsey adopted a more objective, facts-based, data-science-oriented approach to organizational health by developing an Organizational Health Index, comprised of 37 different management practices grouped into 9 different elements: Direction, Leadership, Culture and Climate, Accountability, Coordination and Control, Capabilities, Motivation, External orientation, and Innovation and Learning. . A 2013 Deloitte report, Success or Struggle?

Data 195

Becoming a Data-Driven Business: Challenges and Opportunities

Irving Wladawsky-Berger

A few weeks ago, McKinsey published The age of analytics: Competing in a data-driven world , a comprehensive report on the state of big data, and in particular, on the challenges and opportunities a company faces as it strives to become a data-driven business. Big data ,- including analytics , data science , artificial intelligence and related information-based technologies - are now everywhere. “Is Is big data all hype?,”

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The Competitive Value of Data: From Analytics to Machine Learning

Irving Wladawsky-Berger

A recent article by NY Times reporter Steve Lohr discussed the rising importance of data as a major competitive differentiator. The article noted that regulators, policy makers and academics in Europe and the US are increasingly concerned that the vast data assets of digital giants could become a competitive barrier to startups and innovation. In his NY Times article , Lohr cautions that standard antitrust arguments may not be so easy to make in this new era of data competition.

Learning to Apply Data Science to Business Problems

Irving Wladawsky-Berger

A-Lab’s objective is to teach students how to use data sets and analytics to address real-world business problems. Companies submit project proposals prior to the start of the class, including the business problem to be addressed and the data on which the project will be based. This is a particularly interesting project because economic data in emerging markets is often not as reliable as the data in more advanced markets.

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Open Data

George Siemens

One of the remarkable developments over the last three or four years is the opening of data by organizations such as OECD, UNESCO, World Bank, and city, state/province/national governments. Recent funding cutbacks to this movement in the US – see Death of Open Data? The benefit of open data derives from what it enables – in itself it has limited value.

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A Framework for the Safe Management of Digital Identities and Data

Irving Wladawsky-Berger

In a world that’s increasingly governed by digital transactions and data, our existing methods for managing security and privacy are proving inadequate. Data breaches, large-scale fraud, and identity theft are becoming more common. Data attributes are generally siloed within different private and public sector institutions, each using its data for its own purposes. The OPAL paradigm is based on several key principles, including: Move the algorithm to the data.

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Data, Data Everywhere

George Siemens

This article has been an open tab on my browser for a few months (tabs are just another way to store massive amounts of information that I’ll likely never get to): Data, Data Everywhere : All these examples tell the same story: that the world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly.

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Data Science - the Emergence of a New Discipline

Irving Wladawsky-Berger

Data Science is emerging as a hot new profession and academic discipline. Data Scientist: the Sexiest Job of the 21st Century is the title of a recent Harvard Business Review article. They note that demand for data scientists is racing ahead of supply. People with the necessary skills are scarce, primarily because the discipline is so new that there are no university programs offering data science degrees. . What is data science? ,

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Reflections on Big Data, Data Science and Related Subjects

Irving Wladawsky-Berger

CUSP’s research and educational programs are centered on urban informatics , - “the acquisition, integration, and analysis of data to understand and improve urban systems and quality of life.” Big Cities + Big Data and Bringing Urban Data to Life are prominently displayed in its website. Given the central role of big data with CUSP and with other initiatives I’m involved with, I’d like to step back and reflect on what this all means. What is data science? ,

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Are You a "Data Subject"?

Nine Shift

So, are you a 'data subject'? The European Union's new digital privacy law, the General Data Protection Regulation, doesn't just protect European residents or citizens. The law covers 'data subjects.' You are a data subject," writes Atossa Araxia Abrahamian in the NY Times. . A data subject is a person inside or OUTSIDE the European Union whose personal data is used by a controller or processor.

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How the personal data extraction industry ends

Doc Searls

The main takeaway for me, to both Elizabeth’s piece and Jon’s book, is making clear that Google and Facebook are at the heart of today’s personal data extraction industry, and that this industry defines (as well as supports) much of our lives online. Our data, and data about us, is the crude that Facebook and Google extract, refine and sell to advertisers. adtech advertising Business data Ideas infrastructure Internet Law marketing News Technology VRM

Reflections on the Education of Applied Data Scientists

Irving Wladawsky-Berger

About a year ago, an article in the Harvard Business Review called data scientists the sexiest job of the 21st century. Patil , succinctly defined data scientist as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data.”. For over ten years , we’ve been using the term big data to refer to the fast growing volumes and varieties of digital data being collected, much of it in real-time.

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Why Do We Need Data Science when We’ve Had Statistics for Centuries?

Irving Wladawsky-Berger

Data Science is emerging as as one of the hottest new professions and academic disciplines in these early years of the 21st century. A number of articles have noted that the demand for data scientists is racing ahead of supply. But, the situation is rapidly changing, as universities around the world have started to offer different kinds of graduate programs in data science. So, what is data science all about?

Data Science and the Changing Nature of Research and Innovation

Irving Wladawsky-Berger

Both “are moving toward a common language: advances in mathematics, information sciences, and computer engineering allow highly diverse kinds of data to be manipulated in digital form, and this capability will help unlock problems across scientific disciplines.” . Not surprisingly given our information-intensive economy, these common capabilities are very much like those we are beginning to associate with data science. Quite possibly, data science can be a catalyst for the.

Data 202

Data Viz

Adaptive Path

It ties together three things that are compelling: data viz, Wikipedia and human agreement. Be sure to read the full story about the data and what it represents.). Getting the data isn’t easy. Wikipedia’s model ensures that there is a direct data trace for the recommended action on an AfD thread. a way to track data (Um, “Wait a minute while I post my interim recommendation about this conversation to my iPhone App.” – NOT.). Data Visualization Visualizations

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Uber’s pending sale of your personal data

Doc Searls

Interesting legal hack there: you own your data, but you license it to them, on terms that grant you nothing and grant them everything. As I read that, they have sale on personal data pending until that time. Business data personal data Customer Commons freedom Lyft UberUber has new terms for you : User Provided Content.

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New MOOC: Data, Analytics, & Learning

George Siemens

This fall, together with colleagues, I’ll be offering an open course on edX: Data, Analytics, and Learning. From the description: In education, the use of data and analytics to improve learning is referred to as learning analytics. Software companies, researchers, educators, and university leaders recognize the value of data in improving not only teaching and learning, but the entire education sector. The era of data and analytics in learning is just beginning.

As Big Data and AI Take Hold, What Will It Take to Be an Effective Executive?

Irving Wladawsky-Berger

Big data , powerful analytics and AI are everywhere. First, much still needs to be done to create the proper data sets that would enable intelligent computers to assist in decision-making. Garbage in, garbage out applies as much to data analysis today as it has to computing in general since its early years. Analysis is essentially rational, quantitative, data-driven decision making and problem solving.

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look for disconfirming data

Harold Jarche

Kahane closed by noting that “almost everything I’ve learned is through the disciplined examination of my experience” as well as an approach of “looking for disconfirming data, as Charles Darwin did”. Adam Kahane hosted a webcast this week to discuss his new book, Collaborating with the Enemy. I thought his first book, Solving Tough Problems , was an excellent read so I attended. What follows are from my notes. The quotes are as I wrote them down and may not be Kahane’s exact words.

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Big Data at Google

Jay Cross

To see Big Data at work, look to Google, where number-crunching on a massive scale has changed hiring and management practices. All people decisions at Google are based on data and analytics,” according to Kathryn Dekas, a manager in Google’s “people analytics” team. Measurements and analytics rule at Google. Google’s conclusions have a bearing on where CLOs should be focusing their efforts.

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Owning our data

Harold Jarche

With the internet of everything (IoE), once everything is connected, where will our data reside? If things do not work, will we know what has happened to our data? Individual control over data may be a more robust way to to ensure some level of privacy. The Respect Network is an early example of this move, providing a secure network to share private data. Meanwhile, the IoE is seen by some active players in the field as a way to trade data for information.

Data 184

Latest Data on Telework

Nine Shift

Here's the latest data on the growth in working from home. Telework continues to be the "silent revolution" in the 21st Century. Regular telecommuting grew by 61% between 2005 and 2009. During the same period, home-based selfemployment grew by 1.7%. Based on current trends, with no growth acceleration, regular telecommuters will total 4.9 million by 2016, a 69% increase from the current level but well below other forecasts. ?

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structures and data

Harold Jarche

“Collecting data on human learning based on children’s behavior in school is like collecting data on killer whales based on their behavior at Sea World. ” Warm Data “can be defined as: Transcontextual information about the interrelationships that integrate a complex system.” Far from solving these dilemmas or resolving the conflicting patterns, Warm Data utilizes these characteristics as its most important resources of inquiry.”

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Organizing Big Data Initiatives: Lessons from the Internet

Irving Wladawsky-Berger

In a recent CIO Journal article, Is There a Leadership Vacuum for Big Data? , my fellow guest columnist Tom Davenport reflected on whether institutions should appoint a dedicated executive to oversee their company-wide big data and analytics initiatives, and if so, which C-level senior executives should such a position report to. About 80 percent of the participating companies said that they were already using big data and analytics to a greater or lesser extent.

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Positivism and Big Data

Stephen Downes: Half an Hour

She writes, data scientists use their quantitative measure, as positivists do, by putting a large number veneer over their research This misrepresents positivism, just as Nathan Jurgenson does in his original article. We can apply these principles to big data analytics, of course, and we can use the standard criticisms of positivism to do it: Underdetermination – this is the ‘problem of induction’ or the ‘problem of confirmation’. The same data will confirm any number of theories.

Data 166

Ideas, Experts and Data

Harold Jarche

Data Enslavement – by @ballantine70. Here are some observations and insights that were shared on social media this past fortnight. I call these Friday’s Finds. “ We don’t see something until we have the right metaphor to let us perceive it.” ” – Thomas Kuhn – via @tobiasmeyer. “ Humans require the difficult and messy social routing protocol of trust.” ” – Valdis Krebs @orgnet – via @voinonen.

Data 185

Follow the Data to Find the Money

John Hagel

If you want to know where’s the money, then follow the data and don’t get distracted by the technology. Sure, technology is a key enabler of data capture, aggregation, and analytics, but the providers of this technology will not capture the vast bulk of the value – it will be those who have access to this data and, most importantly, those who can creatively find ways to generate economic value from this data. There’s a growing meme that data is the new oil.

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The Data Bubble redux

Doc Searls

It gets worse: In between the Internet user and the advertiser, the Journal identified more than 100 middlemen — tracking companies, data brokers and advertising networks — competing to meet the growing demand for data on individual behavior and interests.The data on Ms. one of the new data exchanges. “It But that’s a different business than advertising — and it’s no less thick with data… just data that’s voluntarily shared with trusted limits to use by others.).

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Rethinking Personal Data

Irving Wladawsky-Berger

In 2010, the World Economic Forum (WEF), launched a project on Rethinking Personal Data. The project brought together experts from business, government, academia and end user privacy and rights groups to examine the challenges and opportunities involved in properly managing the explosive growth of personal data in the digital world. In January of 2011 they published their first report, - Personal Data: the Emergence of a New Asset Class. .

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#OEB14 - Does Data Corrupt Education

Stephen Downes: Half an Hour

This house believes that data is corrupting education For: Ellen Wagner - Data as the meme - It bothers me that I leave this trail of data everywhere we do - Data without context is really without value - data with context is information, and information is power, and power corrupts. data in the wrong hands might be misused - will this change what we do? Even in low-data environments, you''re already collecting some data. I depend on data.

A Framework for the Safe Management of Digital Identities and Data

Irving Wladawsky-Berger

In a world that’s increasingly governed by digital transactions and data, our existing methods for managing security and privacy are proving inadequate. Data breaches, large-scale fraud, and identity theft are becoming more common. Data attributes are generally siloed within different private and public sector institutions, each using its data for its own purposes. The OPAL paradigm is based on several key principles, including: Move the algorithm to the data.

Data 100