Half of the ‘euphoric’ wealth gained in tax cut rally fizzled out in 7 days
Data showed the domestic equity market gave up half the gains that it had amassed.
Hacker buys old Tesla parts on eBay, finds them full of user data
Data can be retrieved even after owners perform a factory reset, researcher says.
Lockdown messaging 'slightly too successful' with Britons scared to leave home once lifted, expert says
Data shows Britons are fearful of relaxing social restrictions as Prime Minister Boris Johnson readies to publish 'road map' for easing lockdown
Online searches for 'how to cut a mullet' surge amid coronavirus lockdown
Data compiled by online comparison site lays bare how much Britons are missing regular pampering during coronavirus lockdown
Data science drives new maps to predict the growth of cities over next century
A new global simulation model offers the first long-term look at how urbanization -- the growth of cities and towns -- will unfold in the coming decades. The research team projects the total amount of urban areas on Earth can grow anywhere from 1.8 to 5.9-fold by 2100, building approximately 618,000 square miles.
Light, sound, action: Extending the life of acoustic waves on microchips
Data centres and digital information processors are reaching their capacity limits and producing heat. Foundational work here on optical-acoustic microchips opens door to low-heat, low-energy, fast internet.
Statistics Canada says it is probing leak of April jobs data half an hour before official release
Data leaks of this magnitude are virtually unheard of in Canada
Data Filters in PMC and PubMed
Looking for journal articles with associated data sets? New search filters in PMC and PubMed aim to increase the discoverability of articles with associated data information.
In PMC, users can now search on or append searches with filters to discover articles with specific types of associated data, i.e., to find
- articles with associated supplementary material, use “has suppdata”[filter];
- articles that include a data availability or data accessibility statement, use “has data avail”[filter]; or
- articles that include data citation(s), use “has data citations”[filter]
Alternatively, users can run a search on “has associated data”[filter] to find all articles with any type of data section described above.
In PubMed, users can now search on or append searches with data[filter] to find articles with related data links in either the Secondary Source ID field or the LinkOut – Other Literature Resources field (both located below the abstract). These data links may be to records in other NLM databases (e.g., GenBank) or external data repositories (e.g., figshare, Dryad).
The provision and availability of associated datasets still varies widely from article to article, but it is our hope that this small step helps improve the discoverability of this material and supports wider community efforts to advance science in new directions.
Evidence Builds Linking Anticoagulation to COVID-19 Survival
Data from a large US cohort suggest systemic anticoagulation may confer a survival benefit in hospitalized patients without a spike in bleeding events.
Data and the artificial intelligence gold rush: Who will win? -- by Ozzeir Khan
The exponential growth of data and artificial intelligence is creating a tug-of-war between data for profit and data for the common good. In this struggle, it is fundamental that we protect our basic human data rights.
Data on climate change an effective weapon in fighting India’s coastal erosion -- by Rajesh Yadav
Effective and planned shoreline management would trigger activities for tourism, and support development of ocean and beach landscape, conserve biodiversity along with coastal people’s livelihood.
Datasec Solutions
Datasec Solutions Pty Ltd (Datasec or the Company) is an IT security company based in Melbourne, Australia.
Data, analytics and humans: The insight equation
Jim Harris shows how data, analytics and humans work together to form the "insight equation."
The post Data, analytics and humans: The insight equation appeared first on The Data Roundtable.
Data-driven to business insights
Data-driven businesses use technology as an insight platform to empower nontechnical users.
The post Data-driven to business insights appeared first on The Data Roundtable.
Data-driven is better: Lessons from handicapping the ponies
Data-driven is a buzzword again. It feels new and shiny but has been around for years. Yet, people still ask what it means to be data-driven. If you wonder why it’s important to be data-driven, you might ask your bookie. Yes, I said your bookie. In thinking about when I [...]
The post Data-driven is better: Lessons from handicapping the ponies appeared first on Government Data Connection.
The IoT and Data Sharing are Reinventing Loyalty
Data, collaboration, and the IoT are reframing loyalty for a new age
MEDIA ADVISORY: Public Health Makes Changes to Daily COVID-19 Reporting Format
Data Dashboard to be Updated During Noon Hour Starting Monday Smyrna, DE (April 19, 2020) – Starting Monday, April 20, 2020, the Delaware Division of Public Health (DPH) will begin providing its daily updates on COVID-19 statistics on the de.gov/coronavirus website during the noon hour. Data will reflect the most current information available as of […]
In The News
Datask will be its proprietary consumer-based targeted marketing and insights platform.
Data Breach – 95,000 Delawareans Impacted
June 26, 2019 DOVER, DE – The Delaware Department of Insurance recently received notice of a data security breach suffered by Dominion National, an insurer and administrator of dental and vision benefits. On April 24, 2019, through its investigation of an internal alert, Dominion National discovered that servers containing enrollment data, demographic details, and personal […]
Data: Student Achievement in the Era of Accountability - Education Week
The Education Week Research Center looks at student scores on the National Assessment of Educational Progress from 2003 to 2015, a period overlapping with the No Child Left Behind Act.
Data Reveal Deep Inequities in Schools
New data tools allow users to see how public schools fall short when it comes to providing all students the resources they need to meet their highest potential.
Data: How Reading Is Really Being Taught
New survey data from Education Week show that most K-2 teachers and education professors are using instructional methods that run counter to the cognitive science.
Data Privacy
Teachers can feel pressured to use education technology products without knowing how to protect their own and their students' privacy, according to a new online survey by privacy advocacy groups.
Data Doesn't Have to Be a Dirty Word
Every teacher wants his/her students to be successful and chances are, each teacher is doing so much already with the information he or she has to make that happen. As team leaders, we want to help our teachers leverage the information they have to create the most targeted and effective instruction
Data Security and Privacy
Many state and local education agency websites aren't disclosing the presence of third-party tracking services, which can use information about users' browsing.
Data-Based Decisionmaking
State structures can make the difference in whether local education research partnerships are effective, according to a new report by the Data Quality Campaign.
Data Reveal Deep Inequities in Schools
New data tools allow users to see how public schools fall short when it comes to providing all students the resources they need to meet their highest potential.
Data contradicts Harvard professor's assertions about homeschooling
Denver Newsroom, May 7, 2020 / 05:29 pm (CNA).- A Notre Dame sociologist is using data to challenge a Harvard Law professor’s assertions that homeschooling is “dangerous”, and detrimental to society.
The controversy stems from a recent paper by professor Elizabeth Bartholet in which she calls for a presumptive ban on homeschooling in the United States.
Bartholet, as quoted in a Harvard Magazine piece based on her paper, points to unspecified “surveys of homeschoolers” to assert that “up to 90 percent” of homeschooling families are “driven by conservative Christian beliefs, and seek to remove their children from mainstream culture.”
“Some” homeschooling parents are “‘extreme religious ideologues’ who question science and promote female subservience and white supremacy,” she writes.
David Sikkink, associate professor in the Department of Sociology at the University of Notre Dame, analyzed surveys of homeschooling families— including a 2016 government survey— and found that these families are not overwhelmingly Christian nor religious, and are not as universally closed-off to the outside world as Bartholet asserts.
In the analysis Sikkink conducted, just 16% of homeschooling parents said they were homeschooling primarily for religious reasons. The number one reason homeschooling parents cited was a concern about school environment, such as safety, drugs, or negative peer pressure.
Eleven percent of parents reported homeschooling because their child has special needs.
While approximately half of the homeschooling parents surveyed mentioned religion as a factor in their decision to homeschool, Sikkink notes that the parents who cited religion as a reason were, on the whole, more highly educated than those parents who did not.
In terms of Bartholet’s assertion that some homeschooling parents “believe that women should be totally subservient to men and educated in ways that promote such subservience,” Sikkink’s analysis did not find evidence that religious households oppose higher education for girls.
Among the homeschooling families in the survey who use a religious curriculum, there was no difference in their self-reported educational expectations— i.e., what education level they expected their children to reach— for their male children vs. their female children.
Several past studies have shown that homeschool students typically outperform their public and private school counterparts on things like standardized tests and college performance. A 2016 study from the National Council on Measurement in Education showed that, when adjusted for demographic factors, homeschool students were on par academically with their demographically-similar peers.
Moreover, the data Sikkink analyzed suggests that after family background and demographic controls are accounted for, about 64% of homeschoolers “completely agree” that they have much in life to be thankful for, compared to 53% of public schoolers.
On feelings of helplessness, or lack or goals or direction in life, homeschoolers do not substantially differ from their public school counterparts, the analysis suggests.
In the Arizona Law Review, Bartholet argues that while homeschool children may perform as well as their peers on standardized tests or in college, they are also often isolated from their peers and denied experiences and exposures that would make them more productive citizens.
Bartholet claims in her article that “a very large proportion of homeschooling parents are ideologically committed to isolating their children from the majority culture and indoctrinating them in views and values that are in serious conflict with that culture.”
“Isolated families,” she asserts, “constitute a significant part of the homeschooling world.”
In contrast, Sikkink’s analysis found that among the schooling groups surveyed, homeschooling families had the highest level of “community involvement” of all school sectors.
“Community involvement” activities included attending sporting events, attending concerts, going to the zoo or aquarium, going to a museum, going to a library, visiting a bookstore, or attending an event sponsored by a community, religious, or ethnic group.
Homeschooling graduates are almost identical to their public school counterparts in likelihood to vote in federal and local elections, Sikkink found.
Furthermore, the total number of volunteer and community service hours for homeschooling graduates is very similar to or slightly higher than public school graduates, the analysis found.
Bartholet asserts that some homeschoolers “engage in homeschooling to promote racist ideologies and avoid racial intermingling.”
In contrast: “The reality is that about 41% of homeschooled children are racial and ethnic minorities,” Sikkink writes.
“When asked about four closest friends, about 37% of young adult homeschoolers...mention someone of a different race or ethnicity—exactly the same as public schoolers.”
This diversity also extends to schooling practices— increasingly, Sikkink says, homeschooling adopts new forms, including “hybrids” that combine the benefits of home and institutional schooling.
“About 57 percent of homeschoolers are using some form of instruction outside the family,” Sikkink told CNA in an email.
“That includes using tutors, private or public schools, colleges or universities, or homeschooling coops. That percentage would be higher if we included those who reported obtaining curriculum from formal institutions, such as public schools.”
Moreover, about a third of homeschooling parents obtain their curriculum or books from a public school or school district.
“Altogether, 46% of homeschoolers have some pedagogical relationship with public schools,” Sikkink asserts.
Bartholet argues that homeschooling puts children at risk of abuse by their parents, while if children were in public schools, they would be among teachers who are mandatory reporters of any suspected abuse that may be taking place.
“The issue is, do we think that parents should have 24/7, essentially authoritarian control over their children from ages zero to 18? I think that’s dangerous,” Bartholet asserts in the Harvard Magazine piece.
“I think it’s always dangerous to put powerful people in charge of the powerless, and to give the powerful ones total authority.”
Sikkink says Bartholet’s image of a child confined to the home “24/7...from ages zero to 18” is not consistent with the data.
“When we look at the use of homeschooling for each year of the child's upbringing, we only find a small percentage that report that the child was homeschooled for all their years of schooling,” Sikkink told CNA in an email.
Many of these students are part-time public schoolers— about 25% of homeschoolers receive some instruction in public schools during their school-age careers, he wrote.
Homeschooling regulations vary widely by state. Sikkink told CNA he hopes future studies will examine the effects of state-level variation in regulation on homeschooling quality.
“The question of schooling oversight remains, of course, but it would be short-sighted not to keep homeschooling and other creative schooling options in the mix, including the hybrid models that cross sector boundaries,” Sikkink concludes.
Subsequent to the publication of this story, Sikkink told CNA he had revised his assessment of the percentage of homeschoolers using instruction outside the family, from 64% to 57%. The story has been updated to reflect that assessment.
Data gaps exist on COVID-19 cases in Indigenous communities, says research fellow
The number of cases of COVID-19 in First Nations reserves continues to rise this week, with 161 confirmed positive cases reported as of May 5.
Data, technology and policy coordination
Keynote speech by Mr Agustín Carstens, General Manager of the BIS, at the 55th SEACEN Governors' Conference and High-level Seminar on "Data and technology: embracing innovation", Singapore, 14 November 2019.
Data Denoising and Post-Denoising Corrections in Single Cell RNA Sequencing
Divyansh Agarwal, Jingshu Wang, Nancy R. Zhang.
Source: Statistical Science, Volume 35, Number 1, 112--128.
Abstract:
Single cell sequencing technologies are transforming biomedical research. However, due to the inherent nature of the data, single cell RNA sequencing analysis poses new computational and statistical challenges. We begin with a survey of a selection of topics in this field, with a gentle introduction to the biology and a more detailed exploration of the technical noise. We consider in detail the problem of single cell data denoising, sometimes referred to as “imputation” in the relevant literature. We discuss why this is not a typical statistical imputation problem, and review current approaches to this problem. We then explore why the use of denoised values in downstream analyses invites novel statistical insights, and how denoising uncertainty should be accounted for to yield valid statistical inference. The utilization of denoised or imputed matrices in statistical inference is not unique to single cell genomics, and arises in many other fields. We describe the challenges in this type of analysis, discuss some preliminary solutions, and highlight unresolved issues.
data warehouse
A large store of data for analysis. Organizations use data warehouses (and smaller 'data marts') to help them analyze historic transaction data to detect useful patterns and trends. First of all the data is transferred into the data warehouse using a process called extracting, transforming and loading (ETL). Then it is organized and stored in the data warehouse in ways that optimize it for high-performance analysis. The transfer to a separate data warehouse system, which is usually performed as a regular batch job every night or at some other interval, insulates the live transaction systems from any side-effects of the analysis, but at the cost of not having the very latest data included in the analysis.
metadata
Data about data. In common usage as a generic term, metadata stores data about the structure, context and meaning of raw data, and computers use it to help organize and interpret data, turning it into meaningful information. The WorldWide Web has driven usage of metadata to new levels, as the tags used in HTML and XML are a form of metadata, although the meaning they convey is often limited because the metadata means different things to different people.
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization. (arXiv:2005.00061v2 [stat.ML] UPDATED)
Data-space inversion (DSI) and related procedures represent a family of methods applicable for data assimilation in subsurface flow settings. These methods differ from model-based techniques in that they provide only posterior predictions for quantities (time series) of interest, not posterior models with calibrated parameters. DSI methods require a large number of flow simulations to first be performed on prior geological realizations. Given observed data, posterior predictions can then be generated directly. DSI operates in a Bayesian setting and provides posterior samples of the data vector. In this work we develop and evaluate a new approach for data parameterization in DSI. Parameterization reduces the number of variables to determine in the inversion, and it maintains the physical character of the data variables. The new parameterization uses a recurrent autoencoder (RAE) for dimension reduction, and a long-short-term memory (LSTM) network to represent flow-rate time series. The RAE-based parameterization is combined with an ensemble smoother with multiple data assimilation (ESMDA) for posterior generation. Results are presented for two- and three-phase flow in a 2D channelized system and a 3D multi-Gaussian model. The RAE procedure, along with existing DSI treatments, are assessed through comparison to reference rejection sampling (RS) results. The new DSI methodology is shown to consistently outperform existing approaches, in terms of statistical agreement with RS results. The method is also shown to accurately capture derived quantities, which are computed from variables considered directly in DSI. This requires correlation and covariance between variables to be properly captured, and accuracy in these relationships is demonstrated. The RAE-based parameterization developed here is clearly useful in DSI, and it may also find application in other subsurface flow problems.
Data confidentiality: A review of methods for statistical disclosure limitation and methods for assessing privacy
Gregory J. Matthews, Ofer Harel
Source: Statist. Surv., Volume 5, 1--29.
Abstract:
There is an ever increasing demand from researchers for access to useful microdata files. However, there are also growing concerns regarding the privacy of the individuals contained in the microdata. Ideally, microdata could be released in such a way that a balance between usefulness of the data and privacy is struck. This paper presents a review of proposed methods of statistical disclosure control and techniques for assessing the privacy of such methods under different definitions of disclosure.
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Data Driven Respiratory Gating Outperforms Device-Based Gating for Clinical FDG PET/CT
A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm to an external, device-based system for oncological [18F]-FDG PET/CT imaging. Methods: 144 whole-body [18F]-FDG PET/CT examinations were acquired using a Discovery D690 or D710 PET/CT scanner (GE Healthcare), with a respiratory gating waveform recorded by an external, device based respiratory gating system. In each examination, two of the bed positions covering the liver and lung bases were acquired with duration of 6 minutes. Quiescent period gating retaining ~50% of coincidences was then able to produce images with an effective duration of 3 minutes for these two bed positions, matching the other bed positions. For each exam, 4 reconstructions were performed and compared: data driven gating (DDG-retro), external device-based gating (RPM Gated), no gating but using only the first 3 minutes of data (Ungated Matched), and no gating retaining all coincidences (Ungated Full). Lesions in the images were quantified and image quality was scored by a radiologist, blinded to the method of data processing. Results: The use of DDG-retro was found to increase SUVmax and to decrease the threshold-defined lesion volume in comparison to each of the other reconstruction options. Compared to RPM-gated, DDG-retro gave an average increase in SUVmax of 0.66 ± 0.1 g/mL (n=87, p<0.0005). Although results from the blinded image evaluation were most commonly equivalent, DDG-retro was preferred over RPM gated in 13% of exams while the opposite occurred in just 2% of exams. This was a significant preference for DDG-retro (p=0.008, n=121). Liver lesions were identified in 23 exams. Considering this subset of data, DDG-retro was ranked superior to Ungated Full in 6/23 (26%) of cases. Gated reconstruction using the external device failed in 16% of exams, while DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, the data driven respiratory gating technique provided superior performance as compared to the external device-based system. For the majority of exams the performance was equivalent, but data driven respiratory gating had superior performance in 13% of exams, leading to a significant preference overall.
Data-driven motion detection and event-by-event correction for brain PET: Comparison with Vicra
Head motion degrades image quality and causes erroneous parameter estimates in tracer kinetic modeling in brain PET studies. Existing motion correction methods include frame-based image-registration (FIR) and correction using real-time hardware-based motion tracking (HMT) information. However, FIR cannot correct for motion within one predefined scan period while HMT is not readily available in the clinic since it typically requires attaching a tracking device to the patient. In this study, we propose a motion correction framework with a data-driven algorithm, i.e., using the PET raw data itself, to address these limitations. Methods: We propose a data-driven algorithm, Centroid of Distribution (COD), to detect head motion. In COD, the central coordinates of the line of response (LOR) of all events are averaged over 1-sec intervals to generate a COD trace. A point-to-point change in the COD trace in one direction that exceeded a user-defined threshold was defined as a time point of head motion, which was followed by manually adding additional motion time points. All the frames defined by such time points were reconstructed without attenuation correction and rigidly registered to a reference frame. The resulting transformation matrices were then used to perform the final motion compensated reconstruction. We applied the new COD framework to 23 human dynamic datasets, all containing large head motions, with 18F-FDG (N = 13) and 11C-UCB-J (N = 10), and compared its performance with FIR and with HMT using the Vicra, which can be considered as the "gold standard". Results: The COD method yielded 1.0±3.2% (mean ± standard deviation across all subjects and 12 grey matter regions) SUV difference for 18F-FDG (3.7±5.4% for 11C-UCB-J) compared to HMT while no motion correction (NMC) and FIR yielded -15.7±12.2% (-20.5±15.8%) and -4.7±6.9% (-6.2±11.0%), respectively. For 18F-FDG dynamic studies, COD yielded differences of 3.6±10.9% in Ki value as compared to HMT, while NMC and FIR yielded -18.0±39.2% and -2.6±19.8%, respectively. For 11C-UCB-J, COD yielded 3.7±5.2% differences in VT compared to HMT, while NMC and FIR yielded -20.0±12.5% and -5.3±9.4%, respectively. Conclusion: The proposed COD-based data-driven motion correction method outperformed FIR and achieved comparable or even better performance as compared to the Vicra HMT method in both static and dynamic studies.
Data from 2 space lasers comprehensively estimate polar ice loss and sea level rise
(American Association for the Advancement of Science) Ice sheet losses from Greenland and Antarctica have outpaced snow accumulation and contributed approximately 14 millimeters to sea level rise over 16 years (2003 to 2019), a new analysis of data from NASA's laser-shooting satellites has revealed.
Governance and Discovery
Data Governance sounds like a candidate for the most boring topic in technology: something dreamed up by middle-managers to add friction to data scientists’ lives. The funny thing about governance, though, is that it’s closely related to data discovery. And data discovery is neither dull nor additional friction; it’s an exciting process that enables great […]
Fin24.com | Datatec sees increased demand for its remote access computing
Datatec tells shareholders that the rapidly spreading coronavirus outbreak has reached every region where the group operates.
Data Science on AWS
If you use data to make critical business decisions, this book is for you. Whether you’re a data analyst, research scientist, data engineer, ML engineer, data scientist, application developer, or systems developer, this guide helps you broaden your understanding of the modern data science stack, create your own machine learning pipelines, and deploy them to applications at production scale.