Back Talk - Looking Backwards O'Donnell, Jim
Against the grain (Charleston, S.C.),
12/2022, Volume:
34, Issue:
6
Journal Article
Peer reviewed
O'Donnell discusses his early days of using the internet. He states that one day in 1990, his colleague Rick Hamilton from the Bryn Mawr College Greek Department had an idea of publishing a new book ...review journal in classics and he suggested to send the journal via email. Back then, only a few people had emails. But he stuck with his email idea and Hamilton humored him. Their first issue with a dozen reviews (stooged up from academic friends they asked to write about something they had just been reading) was available in print and went out by email as well on November 26, 1990.
In his email Reynolds convinced me that these partnership models have morphed into “gig economies” where employees have little influence on policy and service delivery.2 This change is now ...undermining the foundational principles that once made the NHS a beacon of collaborative healthcare. The homogenisation of policies at a national level fails to account for the nuanced health needs of diverse communities. Royal College of Physicians: Commentary 2019; 4: 20 - 2. https://edwardhreynolds.co.uk/wp-content/uploads/2022/09/National-Health-Service-or-National-Health-Business-1.pdf.
THE DARK SIDE OF PUBLISHING Butler, Declan
Nature (London),
03/2013, Volume:
495, Issue:
7442
Journal Article
Peer reviewed
Open access
According to Beall, whose list now includes more than 300 publishers, collectively issuing thousands of journals, the problem is getting worse. In one e-mail that Beall received and shared with ...Nature, a dental researcher wrote that she had submitted a paper to an open-access journal after she "was won over by the logos of affiliated databases on the home page and seemingly prestigious editorial board".
Full text
Available for:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in ...biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs.
To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence.
A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method.
The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models.
A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The objective of the study was to analyze researchers’ compliance with their data availability statement (DAS) from manuscripts published in open-access journals with the mandatory DAS.
We analyzed ...all articles from 333 open-access journals published during January 2019 by BioMed Central. We categorized types of the DAS. We surveyed corresponding authors who wrote in the DAS that they would share the data. Consent to participate in the study was sought for all included manuscripts. After accessing raw data sets, we checked whether data were available in a way that enabled reanalysis.
Of 3556 analyzed articles, 3416 contained the DAS. The most frequent DAS category (42%) indicated that the data sets are available on reasonable request. Among 1792 manuscripts in which the DAS indicated that authors are willing to share their data, 1669 (93%) authors either did not respond or declined to share their data with us. Among 254 (14%) of 1792 authors who responded to our query for data sharing, only 123 (6.8%) provided the requested data.
Even when authors indicate in their manuscript that they will share data upon request, the compliance rate is the same as for authors who do not provide the DAS, suggesting that the DAS may not be sufficient to ensure data sharing.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Email is one of the most common and widely used forms of communication today, but the specificities of the format make it particularly difficult to manage. As a born digital object, email raises both ...the problems of digital preservation in general and issues specific to electronic mail and correspondence. Its long-term preservation in (public) collections is a novelty in Hungary, but even at international level it is a relatively underdeveloped field. There is an urgent need to elaborate a detailed methodology, as there is already much collection content to be processed, and in the future the so-called LAM (Libraries, Archives, Museums) sector will be increasingly involved in such tasks. The article describes efforts that, among other things, ensure that current endeavours to preserve emails are not competing solutions, but elements of an interoperable toolkit. The authors examine the problems and their applications to email as a born digital object and the specific difficulties that arise beyond these, and they also outline the ways in which preservation can be achieved.
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. While numerous techniques have been developed ...in past years for spotting outliers and anomalies in unstructured collections of multi-dimensional points, with graph data becoming ubiquitous, techniques for structured
graph
data have been of focus recently. As objects in graphs have long-range correlations, a suite of novel technology has been developed for anomaly detection in graph data. This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods for anomaly detection in data represented as graphs. As a key contribution, we give a general framework for the algorithms categorized under various settings: unsupervised versus (semi-)supervised approaches, for static versus dynamic graphs, for attributed versus plain graphs. We highlight the effectiveness, scalability, generality, and robustness aspects of the methods. What is more, we stress the importance of anomaly
attribution
and highlight the major techniques that facilitate digging out the root cause, or the ‘why’, of the detected anomalies for further analysis and sense-making. Finally, we present several real-world applications of graph-based anomaly detection in diverse domains, including financial, auction, computer traffic, and social networks. We conclude our survey with a discussion on open theoretical and practical challenges in the field.
Full text
Available for:
CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
PDF
