Data Science newsletter – August 24, 2021

Newsletter features journalism, research papers and tools/software for August 24, 2021

 

Pushing Health App Data to Doctors: A Burden or an Asset?

Undark magazine, Sarah Kwon


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Questions remain on how providers use app-based health data and whether success stories are the norm, or outliers.


UC San Diego Breaks Record with $1.54B in Research Funding

University of California-San Diego, UC San Diego News Center


from

During a year when much work around the world ground to a halt, researchers at the University of California San Diego were busier than ever working on ways to better understand the movement of SARS-CoV-2; using data science to help predict wildfire behavior; and assessing the risks of weather extremes such as flooding and sea level rise. This work was supported by a record-breaking year of research funding.

In fiscal year 2021 (July 1-June 30), UC San Diego earned $1.54 billion in sponsored research funding, a 6% increase over the previous year. This is the largest number ever for the university and marks the 12th consecutive year the campus has earned more than $1 billion in funding to support its extensive research enterprise.


Strength in Diversity

University of California-Santa Barbara, The UCSB Current


from

“This is a huge win for BioPACIFIC MIP,” Read de Alaniz said. “This award will broadly impact researchers underrepresented in STEM, mainly Hispanic or Latinx. NMHU plays a vital role in educating Hispanic students pursuing a college degree and through this partnership it will enable BioPACIFIC MIP to deliver on its promise to make biomaterial discovery resources available to a broad and diverse national user base.”

“We’re very excited,” said Gil Gallegos, principal investigator and director of the NMHU-led PREM. “The research is one part synthesis and analysis, and the other part is the design, which is going to be machine learning- and AI-informed. That’s the missing element that BioPACIFIC MIP has been looking for in their laboratories over the past few years.”

The joint effort “will focus on machine learning, materials synthesis, high-throughput automated chemistry/biosynthesis, and organic-inorganic materials applications.”


AT&T explores private 5G with University of Tennessee

Mobile World Live, Martha DeGrasse


from

AT&T began installing a private 5G network and testbed at the University of Tennessee’s Knoxville campus which it will use to research mmWave and multi-access edge computing (MEC).

Deployment is scheduled to be completed by the year-end, offering digital learning capabilities including AR-powered visits to places including nuclear power plants or the seabed. Students may also gain the ability to submit biometric signatures, enabling instructors to use machine learning to track time spent on course materials.

In a statement, AT&T explained the network will also provide fresh R&D opportunities. It plans to collaborate with engineers from the university to research the potential of 5G and MEC to create business value in industries including defence, public safety, healthcare, education, entertainment and banking.


Stanford University’s new approach to mitigate negative ethical and societal aspects of AI research

YouTube, The Alan Turing Institute


from

AI research is routinely criticized for its real and potential impacts on society, and we lack adequate institutional responses to this criticism and to the responsibility that it reflects. AI research often falls outside the purview of existing feedback mechanisms such as the Institutional Review Board (IRB), which are designed to evaluate harms to human subjects rather than harms to human society. In response, we have developed the Ethics and Society Review board (ESR), a feedback panel that works with researchers to mitigate negative ethical and societal aspects of AI research. The ESR’s main insight is to serve as a requirement for funding: researchers cannot receive grant funding from a major AI funding program at our university until the researchers complete the ESR process for the proposal. [video, 56:30]


Why Do Chief Data Officers Have Such Short Tenures?

Harvard Business Review; Tom Davenport, Randy Bean, and Josh King


from

Thirty years ago, a widely repeated joke was that CIO — the abbreviation for Chief Information Officer — really meant “career is over.” But as job tenures lengthened and the role became more institutionalized, the joke lost its relevance. Now, however, the most unstable C-suite job may be the Chief Data Officer, or CDO. Tenures are short, turnover is high, and as in the early days of the CIO role, many companies don’t seem to know exactly what they want from its incumbents.

But the CDO job doesn’t have to be so unstable. We believe there are ways that its value can be made more apparent, and for benefits to be delivered quickly enough to prolong job tenures. A clearer definition of the role and a focus on business rather than technology can also help. Conversations with the relatively few long-tenured CDOs have provided valuable insights for newer incumbents.


What will today’s data tell future historians?

BBC Future, Chris Baraniuk


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When John Randolph wrote his first book, about the lives of the Bakunin family in 19th-Century Russia, he had mountains of source material to work from.

“I read hundreds, probably thousands, of letters,” he recalls. “All of these messages were meticulously preserved and ordered in a family archive.”

The Bakunins narrated their lives and relationships in great depth in those letters, bequeathing fascinating details to future historians such as Randolph, director of the Russian, East European and Eurasian Center at the University of Illinois Urbana-Champaign.

But what if he had had an archive of social media posts and photographs to work with instead?

Inevitably, the form and content of surviving records shapes the perspective of anyone who seeks to explore the past. That raises an interesting question for our age: if digital media survive long enough to be studied by future historians (though there’s no guarantee that they will), how will that influence their judgements about us as people?


Engineering Dean Kyle Squires is appointed vice provost

Arizona State University, ASU News


from

For Squires, who has been the dean of the Fulton Schools since 2015, the connecting point for all of these efforts is the central role of discovery, translation and education in a rapidly changing, technologically evolving society. The university plays a key role, Squires said, in providing a portfolio of resources that can be called upon during a person’s career to establish expertise, to adapt to the needs of future work, and to provide value through lifelong learning. The New Economy Initiative is a case in point.

The initiative is a new multiyear program seed-funded by the state of Arizona that will accelerate the rate of faculty growth in the Fulton Schools of Engineering, among other outcomes. The foundation for the New Economy Initiative was built both within the Fulton Schools through its programs and people as well as through partnership with others across the university, especially ASU’s Academic Enterprise and Knowledge Enterprise. These entities working in partnership were able to increase faculty impacts, advance new programs, address critical infrastructure needs, enable cutting edge research and allow the free flow of ideas that refined the larger-scale themes reflected in the initiative.

“The New Economy Initiative, the new and reimagined schools we are launching, the ways we evolve (Fulton Schools of Engineering) and advance our faculty, programs and student engagement opportunities are all vitally important,” Squires said. “But what has also become clear over the past year are how all of these efforts can be expanded to regional and national hubs of excellence, providing unparalleled expertise in critically important areas, and at the scale for which ASU is known.”


The Need for Continuous Intelligence in Higher Ed

RTInsights, Salvatore Salamone


from

Institutes of higher education must deal with all the performance and security issues as major corporates, plus more that are unique to their environment.

There is great siloing. Like most businesses, a university might offer centralized IT services, but many departments go their own way buying, installing, and running systems and applications of their own. As a result, there often are many systems, each with its own management system. And the disparate systems all generate their own telemetrics, logs, and other data needed to fix problems and spot problems in the making product.

Universities are typically more open than businesses. There is less centralized control over what IT equipment, applications, and services can be used. And there is extensive collaboration with outsiders in most research environments. While a business might limit access to a system, application, service, or dataset, it is quite common for much more shared access to these things in an academic setting.

All of these factors make it much harder to manage systems, resolve problems, and reduce problems.


China adopts national privacy law

iapp, Jedidiah Bracy


from

The top legislative body in the People’s Republic of China voted Friday to adopt a new national privacy law. The Standing Committee of the National People’s Congress passed the Personal Information Protection Law at a meeting in Beijing, according to the nation’s state-operated Xinhua News Agency.

The sweeping law will take effect Nov. 1. With the move, the PRC joins three of the world’s top four economies with an omnibus privacy law, leaving the U.S. as the only nation in the top four without one.


PennMed’s to debut new Pavilion facility in November

The Philadelphia Inquirer, Zoe Rosenberg


from

After five years of construction, Penn Medicine will debut The Pavilion, a mammoth new care facility in University City that Penn officials said includes advanced and adaptable features and amenities to better tackle education and research as well as patient treatment.

The Pavilion, to open Nov. 1, will house the Hospital of the University of Pennsylvania’s oncology, neuroscience, and cardiovascular care units. At 1.5 million square feet, the $1.6 billion structure is larger than the Comcast Center (which it beats out by some 100,000 square feet) and spans the length of two football fields between Health Sciences Drive and 33rd Street.


How Big Data Carried Graph Theory Into New Dimensions

Quanta Magazine, Stephen Ormes


from

Graph theory isn’t enough.

The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them) — has been an invaluable way to model real-world phenomena since at least the 18th century. But a few decades ago, the emergence of giant data sets forced researchers to expand their toolboxes and, at the same time, gave them sprawling sandboxes in which to apply new mathematical insights. Since then, said Josh Grochow, a computer scientist at the University of Colorado, Boulder, there’s been an exciting period of rapid growth as researchers have developed new kinds of network models that can find complex structures and signals in the noise of big data.

Grochow is among a growing chorus of researchers who point out that when it comes to finding connections in big data, graph theory has its limits. A graph represents every relationship as a dyad, or pairwise interaction. However, many complex systems can’t be represented by binary connections alone. Recent progress in the field shows how to move forward.


As Artificial Intelligence Expands, So Do Legal Protections

Bloomberg Law, David Rabinowitz


from

It is useful to look at what the law, particularly copyright law, already says about ownership and use of AI rather than trying to forecast what the law will say about the works of autonomous automatons.

Trade Secrets

Before commenting on copyright protection, note that anything that gives a business an advantage over competitors can be protected as a trade secret. This includes all aspects of AI.

The catch is that the information must be kept secret and is not protected against discovery or use by others if they learn the information without discovering it unfairly by breaching the secrecy. Reverse engineering, for example, is permitted. Getting the secret from an unfaithful employee is not permitted. Secrecy can be maintained while allowing users to use a device or service that contains the secret either by agreement or by security measures.

Algorithms

The U.S. Court of Appeals for the Eighth Circuit has held that an algorithm—for making a diagnosis or determination based on research, for example—embodied in documents can be copyrightable. However, it is doubtful that the underlying method, as separate from the specific words of the documents embodying the method, is copyrightable.


A Famous Honesty Researcher Is Retracting A Study Over Fake Data

BuzzFeed News, Stephanie M. Lee


from

According to the 2012 paper, when people signed an honesty declaration at the beginning of a form, rather than the end, they were less likely to lie. A seemingly cheap and effective method to fight fraud, it was adopted by at least one insurance company, tested by government agencies around the world, and taught to corporate executives. It made a splash among academics, who cited it in their own research more than 400 times.

The paper also bolstered the reputations of two of its authors — Max Bazerman, a professor of business administration at Harvard Business School, and Dan Ariely, a psychologist and behavioral economist at Duke University — as leaders in the study of decision-making, irrationality, and unethical behavior. Ariely, a frequent TED Talk speaker and a Wall Street Journal advice columnist, cited the study in lectures and in his New York Times bestseller The (Honest) Truth About Dishonesty: How We Lie to Everyone — Especially Ourselves.

Years later, he and his coauthors found that follow-up experiments did not show the same reduction in dishonest behavior. But more recently, a group of outside sleuths scrutinized the original paper’s underlying data and stumbled upon a bigger problem: One of its main experiments was faked “beyond any shadow of a doubt,” three academics wrote in a post on their blog, Data Colada, on Tuesday.


Naming rights: What universities gain and lose when they name places after people

Columbia Missourian, Owen Krucoff


from

When the building now known as Mizzou Arena opened in 2004, Paige Laurie was a recent graduate of the University of Southern California and an heir to one of the largest fortunes in the country. She was also the namesake of MU’s new basketball facility.

Paige Sports Arena, as it was known when the Missouri men defeated Central Missouri in an exhibition game Nov. 4, 2004, had been paid for in part by a $25 million donation from Laurie’s parents, Bill and Nancy Laurie, the niece and nephew-in-law of Walmart founder Sam Walton. The Lauries, both Missouri natives who had raised their daughter in Columbia, used the leverage from their donation to name the building after Paige, who had never had any formal ties to MU. It was a questionable decision, but one that didn’t seem too controversial — for about a month or so.

That November, Paige Laurie was accused of paying a former classmate to do her schoolwork at USC. Laurie later surrendered her diploma, and MU was forced to change the name of the arena rather than have it continue to be named after a known cheater.


Carrie Chapman Catt’s legacy is controversial at Iowa State University

Ames Tribune, Isabelle Rosario


from

More than 25 years after Iowa State University officially christened Carrie Chapman Catt Hall — and the swift controversy that followed — a committee is once again considering whether to change the building’s name.

This time, Iowa State is paying consulting firm History Associates Inc. an estimated $33,140 to “gather and organize factual evidence”, university spokesperson Brian Meyer said. In the fall, a committee will outline the timeline for making a recommendation to President Wendy Wintersteen on whether to rename the building.

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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.

 


Tools & Resources



Friends Don’t Let Friends Use Stoplight Color Schemes

Evergreen Data


from

Friends don’t let friends use stoplight color schemes. This is the tiny hill I am willing to die on. So Friend, let’s talk about why this has got to stop. There are three solid reasons, each of which, on its own, is more than enough to get the red-yellow-green scheme uprooted.

1: It is not color-blind friendly.

The most common form of color-blindness is red-green. Which means that when we use the stoplight colors to communicate that red means “bad” and green means “good,” people who are red-green color-blind literally can’t tell if you are talking about the worst stuff or the best stuff.


People-centered data, with Jer Thorp

Substack, Slow Build newsletter, Nancy Scola


from

The Canada-raised, Brooklyn-based Thorp has long gotten attention for turning data sets into striking works of art, like plotting connections in the Times’ archives, mapping the world’s travel patterns via “just landed” tweets, and perhaps most powerfully, building the tool behind the placement of names on Manhattan’s 9/11 Memorial.

Thorp says he benefited early on from not knowing the rules. With a background in generative art, not charts and graphs, Thorp was free to jump from data set to data set, treating them as fodder for visualizations that tested the boundaries of the form.


Create a heatmap from the logs of your activity tracker

Towards Data Science, Leo van der Meulen


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I have 7 years’ worth of recorded walking activity on my computer. Over all these years these have been collected with several devices and apps, from stand-alone GPS-receiver, through SportsTracker to Garmin. Luckily, all of them have in common that the recorded route is available in GPX-format. Obtaining these files might not be as simple tough.

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