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ISO27000 and Information Security
This extensive glossary of information security and related terms is not a technical glossary: it is designed to help a manager, or someone new to the subject, identify the meaning of a particular term.
eBook
Words and power : computers, language, and U.S. Cold War values
\"When viewed through a political lens, the act of defining terms in natural language arguably transforms knowledge into values. This unique volume explores how corporate, military, academic, and professional values shaped efforts to define computer terminology and establish an information engineering profession as a precursor to what would become computer science. As the Cold War heated up, U.S. federal agencies increasingly funded university researchers and labs to develop technologies, like the computer, that would ensure that the U.S. maintained economic prosperity and military dominance over the Soviet Union. At the same time, private corporations saw opportunities for partnering with university labs and military agencies to generate profits as they strengthened their business positions in civilian sectors. They needed a common vocabulary and principles of streamlined communication to underpin the technology development that would ensure national prosperity and military dominance. investigates how language standardization contributed to the professionalization of computer science as separate from mathematics, electrical engineering, and physics examines traditions of language standardization in earlier eras of rapid technology development around electricity and radio highlights the importance of the analogy of \"the computer is like a human\" to early explanations of computer design and logic traces design and development of electronic computers within political and economic contexts foregrounds the importance of human relationships in decisions about computer design This in-depth humanistic study argues for the importance of natural language in shaping what people come to think of as possible and impossible relationships between computers and humans. The work is a key reference in the history of technology and serves as a source textbook on the human-level history of computing. In addition, it addresses those with interests in sociolinguistic questions around technology studies, as well as technology development at the nexus of politics, business, and human relations.\"--Back cover.
Book
Translating Computer Abbreviations from English into Spanish: Main Types and Problems
Abstract
Many computer terms have entered the Spanish language in recent years. Some of them are widely adopted without any previous modification. The number of English computer abbreviations used in Spanish is constantly increasing. Some of them are well-established, e.g. RAM, ROM, PC, but others have appeared very recently, e.g. WWW, ISP, IRC, HTML. This paper is intended to classify the different types of English abbreviations most commonly used in computer terminology and to identify the most important problems for their translation into Spanish as well as provide some solutions for it.
Journal Article
Metaphor-based metaheuristics, a call for action: the elephant in the room
Taking inspiration from natural behaviors to devise new optimization algorithms has played an important role in the history of the field of metaheuristics (Sörensen et al. 2017). Unfortunately, in the last two decades we have been witnessing a new trend by which dozens of metaphor-based metaheuristics based on the most diverse possible set of natural, artificial, social, and sometimes even supernatural phenomena and behaviors are proposed, without a clear motivation beyond the desire of their authors to publish their papers.
Journal Article
Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration
Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).
Journal Article
A Closer Look at Classification Evaluation Metrics and a Critical Reflection of Common Evaluation Practice
Classification systems are evaluated in a countless number of papers. However, we
find that evaluation practice is often nebulous. Frequently, metrics are
selected without arguments, and blurry terminology invites misconceptions. For
instance, many works use so-called ‘macro’ metrics to rank systems
(e.g., ‘macro F1’) but do not clearly specify what they would
expect from such a ‘macro’ metric. This is problematic, since
picking a metric can affect research findings and thus any clarity in the
process should be maximized. Starting from the intuitive concepts of
and
, we perform an
analysis of common evaluation metrics. The analysis helps us understand the
metrics’ underlying properties, and how they align with expectations as
found expressed in papers. Then we reflect on the practical situation in the
field, and survey evaluation practice in recent shared tasks. We find that
metric selection is often not supported with convincing arguments, an issue that
can make a system ranking seem arbitrary. Our work aims at providing overview
and guidance for more informed and transparent metric selection, fostering
meaningful evaluation.
Journal Article
Automatic jargon identifier for scientists engaging with the public and science communication educators
Scientists are required to communicate science and research not only to other experts in the field, but also to scientists and experts from other fields, as well as to the public and policymakers. One fundamental suggestion when communicating with non-experts is to avoid professional jargon. However, because they are trained to speak with highly specialized language, avoiding jargon is difficult for scientists, and there is no standard to guide scientists in adjusting their messages. In this research project, we present the development and validation of the data produced by an up-to-date, scientist-friendly program for identifying jargon in popular written texts, based on a corpus of over 90 million words published in the BBC site during the years 2012-2015. The validation of results by the jargon identifier, the De-jargonizer, involved three mini studies: (1) comparison and correlation with existing frequency word lists in the literature; (2) a comparison with previous research on spoken language jargon use in TED transcripts of non-science lectures, TED transcripts of science lectures and transcripts of academic science lectures; and (3) a test of 5,000 pairs of published research abstracts and lay reader summaries describing the same article from the journals PLOS Computational Biology and PLOS Genetics. Validation procedures showed that the data classification of the De-jargonizer significantly correlates with existing frequency word lists, replicates similar jargon differences in previous studies on scientific versus general lectures, and identifies significant differences in jargon use between abstracts and lay summaries. As expected, more jargon was found in the academic abstracts than lay summaries; however, the percentage of jargon in the lay summaries exceeded the amount recommended for the public to understand the text. Thus, the De-jargonizer can help scientists identify problematic jargon when communicating science to non-experts, and be implemented by science communication instructors when evaluating the effectiveness and jargon use of participants in science communication workshops and programs.
Journal Article
Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility
The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk‐informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk‐based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick‐start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.
Journal Article
A benchmark and comprehensive survey on knowledge graph entity alignment via representation learning
In the last few years, the interest in knowledge bases has grown exponentially in both the research community and the industry due to their essential role in AI applications. Entity alignment is an important task for enriching knowledge bases. This paper provides a comprehensive tutorial-type survey on representative entity alignment techniques that use the new approach of representation learning. We present a framework for capturing the key characteristics of these techniques, propose a benchmark addressing the limitation of existing benchmark datasets, and conduct extensive experiments using our benchmark. The framework gives a clear picture of how various techniques work. The experiments yield important results about the empirical performance of the techniques and how various factors affect the performance. One important observation not stressed by previous work is that techniques making good use of attribute triples and relation predicates as features stand out as winners. We are also the first to investigate the question of how to perform entity alignments on large-scale knowledge graphs such as the full Wikidata and Freebase (in Experiment 5).
Journal Article