Talk:Data science - Knowledge

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does not mention the term "data science" at all. Rather it says he defined "e-Science" and "data-driven science". These specifically refer to the use of big data in academic research Science, as in, using big data technologies for astronomy, chemistry, biology etc. The vast bulk of self-described "Data Scientists" today do not work in academic science. They use the "science" in "data science" to mean a particularly methodology they employ, as in "philosophy of science", rather than to refer to the set of academic sciences such as astronomy and biology. They work in commercial fields like search engine and social network prediction rather than in "Science". So maybe we should split this into two articles, one about the current commercial profession of Data Science, as conceived by most self-describing Data Scientists, and a second one about data-driven science or "e-science" as conceived by Grey and others? They are not the same subject, maybe that's a reason why the article has been so confused and people are arguing over it?

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concepts with the mush that waffles about the continental ones). The "fourth paradigm of science" -- reminds me of the old 1990s maxim "whenever you hear 'new paradigm', put away your wallet" ! So can we find and describe some serious definitions of Data Science as a field to replace this mess of advertising and hype ? I have made a start with '"Data Science" has been defined as "the passive reuse of data collected for other purposes" in contrast to both "real science" in which the experimenter causes some of the data to occur and can thus make causal inferences' as defined in (Fox 2018, chapter 1), what do we think to this ?

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model random variations in the "speed of time"? For example, in modelling growth in adolescence, not all people experience the typical burst of growth at the same age; this can be modelled through time warping, and randomness in a Lie Algebra becomes a core concept. Time warping is one the topics in studying randomness that statistician are tackling now. Different branches of mathematics model different aspects, so one need to be very careful discarding one because "it is not important".

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methods puts emphasis on domain-specific knowledge? I never though the concepts of localisation (mean, median) and dispersion (quantiles, standard deviation) were specific to a particular domain - and you can't get more "traditional" in statistics than those. Not to mention many other (richer) models in modern statistics that can be applied to many fields (Bayesian learning, stochastic processes, etc etc). In short: this sentence is utterly rubbish!

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agains is a branch of mathematics and heavily used in statistics; "statistical learning" a method in statistics; "machine learning" is a subfield of computer science, again appearing on its own. If one wanted to write a structured sentence like this, one should use terms with the _same_ level of generality and scope! Someone needs to edit to fewer covering all relevant areas (If it was me I would put only "mathematics"!)

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Findings must be presented. To translate, say, "implications of trending tidal effects as measured, resulting from anomalies presented by random variance in the mean distance between the Earth and Moon" into people-speak requires a communication skill set that is essential. If decision makers do not "get it," the story big data is trying to tell could go ignored.

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overlapping regions arise out of the combination of their individual elements is not obvious, certainly not to an average, non-specialist reader. It may make seem like a great visual prop to you, but I think it is useless as a stand-alone image, which makes sense if it has been lifted out of a talk without any of the surrounding discussion.

2860:. I cannot quickly find a copy of this online. This paper could contribute to a Knowledge article about "data scientists", or there could be a data scientist section in this article. With data science being a career field, this topic too has heavy media coverage on degrees, particular skill sets, and working conditions. 2908:“Computer and information research scientists invent and design new approaches to computing technology and find innovative uses for existing technology.” "Explore fundamental issues in computing and develop theories and models to address those issues." "Help scientists and engineers solve complex computing problems." 2135:

The lead is somewhat chatty and editorialized; parts are intended to persuade rather than to inform. I think more authoritative sourcing would help establish what disciplines are subsumed within the field. The "buzzword" discussion is poorly cited and may not belong in the lead at all. Sentences like

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Well, everybody knows that Data Science is "full of rubbish", because it is a hype. So anything but advertising language doesn't describe this subject... That is an open secret, but it will take some years for the dust to settle and usable definitions to emerge. It's not our task to add another vague

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On this topic, the description “interdisciplinary field about processes and systems to extract knowledge or insights from data” is full of vague, advertising-style language, and could easily be used to describe a number of other topics, such as applied statistics or digital ethnography. If anyone can

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section both on the history of the term, the buzzword bingo, and the criticism (actually, almost the entire article is about this dilemma. No need to rewrite the wheel; in particular not based on a single just-published, non-reviewed book, by an author with no reputation in data science. (And your IP

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and copied the Jim Gray paradigm over there. Added further references to the modern professional definition of DS from Forbes and Udacity. We need some more up to date scholarly references then to reflect the modern community's usage -- Fox is from 2018 and happens to be what I'm currently reading,

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Gray was one of the best database researchers in the world but he didn't talk about data science in the currently popular sense of the word. (He died in 2007, one year before the modern sense was invented by Facebook and LinkedIn people). The opinion article in Science magazine citied here about him

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It is like writing in the biology page, a link to mammals, the kangaroo, ants, social insects, birds, dogs and Snoopy. This may see extreme, but this is what is happening in the overview. It is not a matter of readability. By the way, funny you mention Lie Algebra; did you know that it can be used to

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I don't see the need to have terms of the same level of generality. Clearly, not every branch of computer science is equally important (e.g. theoretical computer science). Computer science in general is important, and data mining in particular is more important, so it is worth emphasizing. Similarly,

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News has a number of interesting articles that show how statistics departments are anxious of becoming obsolete now, and therefore are rebranding themselves to data science. While computer science doesn't seem to care - they still have big data, deep learning, etc. as hypes that are uncontested, and

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No, I don't think it is "overly negative". Without doubt, the entire "DS" is a big bubble right now, and it still lacks a proper definition beyond "statistics, only renamed and with more CS". The article lede shouldn't be all "we are the most sexy unicorns"; and everybody doing data science only now

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Knowledge articles are a good indicator of the credibility of research fields in general. If Knowledge can't write a clear definition of what something is then it's probably a bullshit concept in the first place. (Compare, for example, Knowledge's beautiful and clear articles on analytic philosophy

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This book just came out and it has a Wikimedia compatible license. Data science can be lots of things, and I think much of this book talks about data science. Most of the explicit mentions of the term "data science" are in the context of teaching data science, both in university and citizen science

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I deleted the sentence on "many advocacy efforts". The reference was for the ASA that renamed a division to include the new name of DS, and as part of that charter, said it was advocating that statistics should be at the center of DS. The way it was written up in this article sounded like multiple

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I have removed a comment inserted at the opening line stating that "Data Science is a buzz word" with an incendiary, non-neutral blog post from an applied statistics website as its source. Looking back at the history I noticed that the same person keeps posting this comment after it repeatedly gets

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Knowledge has a challenge separating articles about academic and professional fields with the concept of careers in those fields. For example, nursing versus being a nurse. The challenge is that a large amount of media in these fields which users either want to read or want to share relates to the

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Glad we are on the same page on what Data Science is. I just want to point, out, the meta description of Nazism is not “the defense of Aryan purity;” it is defined as “ideology and practice associated with the 20th-century German Nazi party and state.” I am just saying we do not necessarily define

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The first sentence "Data science employs techniques and theories drawn from many fields ... " is full of terms grabbed on many articles, not well structured and with different levels of generality. For example, statistics is a branch of mathematics; "probability models" links to probability, which

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My edits have been a sincere attempt to improve the quality of the entry. I am not trying to protect "data science" from criticism, let alone serve my own personal interests by doing so. So please don't use a disagreement over content as a pretext for an unsubstantiated personal attack. I'll stop

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to ensure that statistics is truly at the center of data science education, research, and practice.”' and thus does show there are advocacy efforts surrounding this term. In particular, statisticians try to present themselves as the center of data science, and so do machine learners, and business

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Again, in same section we have this jewell "It emphasizes the use of general methods such as machine learning that apply without changes to multiple domains. This approach differs from traditional statistics with its emphasis on domain-specific knowledge and solutions." I am in shock! Statistical

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The venn diagram, as it is, is ridiculous. It has no context and has almost zero meaning without explnation. It should either be discussed in the text, at least to explain what is meant by the terms - "hacking skills" and "danger zone" seem to be the glaring examples- or removed. Exactly how the

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how about a talk page vote then -- how many people think that this "Data Science" page should be about (1) Data Science qua the 2010s Silicon Valley profession in the sense of Facebook and LinkedIn's job titles; or (2) Data-driven science as defined by Jim Gray's fourth paradigm for the academic

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Hi, first time chiming in. A colleague was reviewing the data science disciplines graphic with me and we agreed that proficiency in oral/written communications should get equal playing time with the other disciplines. At some point after analysis and visualization, the story needs to be told.

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Seems pretty clear that data science draws heavily from statistics, but isn't the same as it, similar to the field of actuarial science. Whatever criticism you have of DS could also be applied to AS when it was first established. (Regarding Terry Speed video, tl;dw). The lede in general is

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As a rule of thumb on a overhyped topic like this: if the authors are widely known professors, such books are probably good. These four seem a reasonable start (and do we need that many more?). But there are also plenty of self-appointed "experts" on this matter that fail this test...

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institutions, too, so how does it get us any further? (Were did you read about this? I cannot even find a mention of it). Are you sure its not about purely academic careers? Data science is just a lot of buzzword bingo and rebranding. We should wait for an actual accepted definition.

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This seems to be a free and open journal (CC-By-4.0) and is about data science. It published its first issue today. Some of the articles are social enough to present basic defining information about data science to the general public. This might be useful for this Knowledge article.

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I propose that risk should be mitigated within the team. Utilizing an external marketing resource compounds the risk factor, at the very least, by adding one more possible point of failure. How is the "translation" angle currently handled by working teams? Is it within or without?

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This sounds nothing like what a data scientist does and more describes someone who works with and studies the theory of computation. In fact, the BLS page for Mathematicians and Statisticians is actually much more akin to the actual responsibilities of data scientists:

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Domain Specific Interests begins by recapitulating a definition of data science, which is unnecessary so late in the article. "Data science requires a versatile skill-set" is an unverified claim that doesn't contribute much information about the article subject.

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There is actually a lot of controversy about whether data science is distinct from statistics. The "Statistics = Data Science?" lecture cited in the article is clear evidence of that. It can be seen as old wine in new bottles. See this article in Forbes, too:

2062:“A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization.” — Anjul Bhambhri, Vice President of Big Data Products, IBM 2879:

I'm not sure whether I would Data Science even to be a "professional field". On one hand, it claims to be science (i.e., academic), and on the other hand there is no such professional body or even a definition. And the whitepaper is about reports from

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This thread has to refer to the specific names of mathematical/statistical theory that data scientists use. Otherwise we're talking about English professors as data scientists, and philosophy professors as analyzing data on the human condition.

1770:. I do not see a reason to rewrite it yet again to make Mr. Fox "passive data reuse" opinion dominant. Fact is that opinions and definitions disagree. And in a few years we may need to add "data science bubble" to this article, so what? 2283:

analysts, and essentially everybody else that uses data, unfortunately... Everybody see themselves as "the" archetype of "sexy" data science and tries to push their point of view on what is data science, and that everybody else is not.

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Can we get rid of the "Further Reading" section? It's not adding anything to the article, and because the topic of Data Science is so broad, readers would be better off just searching for appropriate books on Amazon.

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come up with a better description than “A field of study involving the use of computers to perform statistics,” then by all means, do so, but from this article, this is what I have gathered the field is about.

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It had seemed the point of the sentence was advocacy for DS, not for a particular view of DS. I see you apparently didn't have criticism of my other points, namely that the lede is overly negative and not

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ideas on the terms of those who espouse them, for the good reason that editors, regardless of claims to neutrality, have a responsibility to the audience to make sense of the content for the audience.

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fields of science and mathematics evolve over time. It is not surprising in the least that the field of statistics has evolved to address digital data sets and digital processing of data.

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A computer and information research scientist is not the same thing as a data scientist in the context as shown on the BLS website. A look at the responsibilities page makes this clear:

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This has some excellent coverage of social issues which I have not seen elsewhere. They have weird access barriers on their website but I think anyone can download the PDF to read at

1652:. Perhaps we should redirect "data-driven science over there, move the text on Gray to it, then use the present page for Data Science as the modern profession ? What do people think ? 1227:. The project works to allow users to contribute quality articles and media files to the encyclopedia and track their progress as they are developed. To participate, please visit the 3327: 3290: 3417: 3342: 3073: 563: 501: 1970:

Sorry, I have no idea what you are trying to say. There is nothing wrong with the image that I can see. Could you provide specific criticism other than "absolutely awful"?

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The truth is the BLS does not have a dedicated page for this occupation, but the page for Computer & Information Research Scientists should definitely not be cited.

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job opportunities of a certain time and place, which is not general interest to everyone in the way that a general presentation of the field subject matter would be.

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At a glance all these seem like fine sources to include. I agree that I expect there is plenty of criticism and that we should plan to include it in the narrative.

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is a Turing Award winner, whose notable opinion of a "fourth paradigm" is found in independently written books. It shouldn't just be removed to promote your book.

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The O'Reilly reference for "diluted beyond influence" is actually very positive on the field of DS, but some negative wording from the article was cherry-picked.

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on the opinion of Wiki editors. So if you can find widely accepted, less vague-advertising definitions of data science (how about "the sexiest job"?) in some

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is a newly released book which I thought could be used to develop this article. It is open access with a Wikimedia compatible license so I copied it here.

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Is the section structure right for this article? The "History" section definitely belongs; I think specific conferences are trivial to a wide audience.

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Similarly, the BLS actually groups employment statistics for this occupation along with other mathematical science occupations, not computer science:

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In wikipedia you describe the controversy, you don't engage in it. Say something like "some people refer to it as a buzzword" and include the link.

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research sciences ; or (3) make it as a page which says the term is contentious and has been defined by a big list of people in different ways ?

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I am trying to determine what sources give a general overview of the topic. I hardly know where to begin, but I am looking at these to start.

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by Drew Conway, which for me conveys best what Data Science is. There is the issue of checking copyright (it can be found with copyright to

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Prior to 8/11/2022the definition was too general. You could call English PhD, an analyst of text data, and therefore a data scientist

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settings, to prepare people for careers. This just came out and I am just reviewing this, but I wanted to share it here now.

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removed by other contributors. I recommend that the article is locked from unmoderated edits and that the vandal is banned.

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This article is or was the subject of a Wiki Education Foundation-supported course assignment. Further details are available

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editing this page for a while -- hopefully you and others will arrive at a consensus as to what should be there. Peace out.

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Nate Silver is exactly right in saying that there is no difference between "data science" and the field of statistics.

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Many people want to know the career marketplace for this field. I think this article lays out popular thought on this.

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I'm moving this quote here that an IP placed in the lead. We might be able to use it (or not) but it needs a source:

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related articles on Knowledge. If you would like to participate, please visit the project page, where you can join

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Any misbegotten attempts to draw a distinction between the two terms, such as this article, is doomed to failure.

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Most of the rest of the article does not seem to cover a topic, either, so it will probably also be deleted.

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restored both the professional version of DS and also the Jim Gray forth paradigm text. Also added redirect to

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I think some critical thoughts like that should be included, not just the hype. There were some, until

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until a consensus is reached, and readers of this page are welcome to contribute to the discussion.

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Agreed. A Knowledge entry isn't a good place for reading lists on such a broad and amorphous topic.

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Additionaly, it always helps when a presentation has a strong narrative structure, don’t you think?

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The lead is fine and defines the topic quite well. I'm afraid I do not understand your criticism.

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on Knowledge. If you would like to participate, please visit the project page, where you can join

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on Knowledge. If you would like to participate, please visit the project page, where you can join

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on Knowledge. If you would like to participate, please visit the project page, where you can join

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on Knowledge. If you would like to participate, please visit the project page, where you can join

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This article was the subject of a Wiki Education Foundation-supported course assignment, between

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The introduction is supposed to be general, while the rest of the article can go into specifics.

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Clinical Data Science: I'm skeptical that a word can be "coined" and widely adopted in ~5 months

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This article was the subject of a Wiki Education Foundation-supported course assignment, between

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This article was the subject of a Wiki Education Foundation-supported course assignment, between

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This article was the subject of a Wiki Education Foundation-supported course assignment, between

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http://theconversation.com/statistics-and-data-science-degrees-overhyped-or-the-real-deal-102958

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http://www.forbes.com/sites/gilpress/2013/08/19/data-science-whats-the-half-life-of-a-buzzword/

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is not the answer (instead, everybody should have better basic knowledge in statistics, e.g.,

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If I can find any sentences with "content" that apply to the "topic" I will leave them alone.

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We already have (1) 'Sexiest Job of the 21st Century' and (2) '"fourth paradigm" of science'

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Many of these efforts (and all the money invested in expensive consultants) seem to fail:

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I think you should move this to the bottom as a new section as nobody will see it here. ♫

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DATA MATTERS : ethics, data, and international research collaboration in a changing world

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Research Areas: How can we verify that this list is exhaustive and each item significant?

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I have restored the old version, although I do not like the wording "To its discredit".

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to use that book). Sorry, I don't think we can find a consensus on using your rewrite.

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Requested articles/Applied arts and sciences/Computer science, computing, and Internet

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The Alfred P. Sloan Foundation in October 2019 published an interesting white paper,

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The article confounds information with knowledge. See for example this reference

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most parts of mathematics research are only marginally relevant to data science

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Another critical opinion mentioning a Gartner number of 85% failure rate:

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Empirically-based approach to understanding the structure of data science

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in terms of usefulness to humanity. And that image is absolutely awful.

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Knowledge:Redirects for discussion/Log/2021 April 30#Hadelin De Ponteves

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is a broken link, perhaps this material can be accessed elsewhere?

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Knowledge:Redirects for discussion/Log/2024 February 8 § Data duck

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Careers of Data Scientists: Report from 13 Academic Institutions

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Jeffrey M. Stanton (20 May 2012). "Introduction to Data science"

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Data Science, Big Data and Statistics - Can We All Live Together

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https://commons.wikimedia.org/File:Data_Science_Venn_Diagram.png

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by an editor with a conflict of interest has now been answered.

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The data science venn diagram is now available at WikiCommons:

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Wiki Education assignment: DATS 6450 - Ethics for Data Science

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Computer & Information Research Scientist ≠ Data Scientist

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Wikibooks already has an image in use, so I added it instead.

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In contrast to Mr. Fox and his just-out specialized book, Mr.

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Find pictures for the biographies of computer scientists (see

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Wiki Education assignment: Introduction to Digital Humanities

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description / "definition", but instead we should work with

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is a data science software platform for the development of

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http://www.infogineering.net/data-information-knowledge.htm

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for a good description of the difference between the two.

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The fourth paradigm : data-intensive scientific discovery

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Data Science (The MIT Press Essential Knowledge series)

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In the "Platforms" section, please add the following:

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Knowledge level-5 vital articles in Physical sciences

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It is misleading and dishonest to pretend otherwise.

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A discussion is taking place to address the redirect

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Wiki Education Foundation-supported course assignment

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Wiki Education Foundation-supported course assignment

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Wiki Education Foundation-supported course assignment

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Wiki Education Foundation-supported course assignment

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to determine whether its use and function meets the

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This article was accepted on 4 May 2012 by reviewer

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Should "Communicator" Be Added To Discipline Chart?

944:This article has not yet received a rating on the 507:Computer science articles needing expert attention 2472:; Tansley, Stewart; Tolle, Kristin, eds. (2009). 2428:Journal of Computational and Graphical Statistics 2018:So I will probably delete most if not all of it. 2496:(First edition. ed.). Sebastopol, CA: O'Reilly. 2426:(19 December 2017). "50 Years of Data Science". 739:, a project which is currently considered to be 33:for general discussion of the article's subject. 2713:"Statistics Losing Ground to Computer Science" 2198:. I'm thinking of adding a criticism section. 647:WikiProject Computer science/Unreferenced BLPs 3328:Knowledge vital articles in Physical sciences 2920:https://www.bls.gov/oes/current/oes152098.htm 174: 8: 2447:Kelleher, John D.; Tierney, Brendan (2018). 2112:YES! There is a study to support your claim 1116:, which collaborates on articles related to 3418:C-Class physics articles of High-importance 3343:C-Class vital articles in Physical sciences 2260:groups were trying to hype up DS as a name. 1237:Knowledge:WikiProject Articles for creation 564:Computer science articles without infoboxes 502:Computer science articles needing attention 2926: 1799: 1240:Template:WikiProject Articles for creation 1221:This article was reviewed by member(s) of 1185: 1062: 957: 859: 770: 699: 468:Here are some tasks awaiting attention: 442: 357: 227: 3373:High-importance Computer science articles 2166:Vandalism / "Data Science is a buzz word" 1484:Template:Dashboard.wikiedu.org assignment 1419:Template:Dashboard.wikiedu.org assignment 1370:Template:Dashboard.wikiedu.org assignment 1313:Template:Dashboard.wikiedu.org assignment 1920:), and the fact that it's from a blog. 1482:Above undated message substituted from 1417:Above undated message substituted from 1368:Above undated message substituted from 1311:Above undated message substituted from 1187: 1064: 959: 861: 772: 701: 359: 229: 188: 3099:2405:201:5C09:5102:9D8C:35AA:43A3:F943 2492:Schutt, Rachel; O'Neil, Cathy (2013). 2278:Well, the reference does contain '... 1672:but can we provide some more as well ? 409:Knowledge:WikiProject Computer science 3403:Unknown-priority mathematics articles 3378:WikiProject Computer science articles 3196:2601:200:C000:1A0:88E0:B50A:C99D:52BB 2414:Likely good general reference sources 412:Template:WikiProject Computer science 7: 3190:It is still the field of statistics. 1172:This article is within the field of 1110:This article is within the scope of 1005:This article is within the scope of 904:This article is within the scope of 802:This article is within the scope of 735:This article is within the scope of 389:This article is within the scope of 266:This article is within the scope of 3448:AfC submissions by date/04 May 2012 3388:High-importance Statistics articles 2695:"Data Science Consulting Is A SCAM" 2014:The lede does not define the topic. 23:for discussing improvements to the 3433:Systems articles in systems theory 3353:High-importance Computing articles 3223: 3219: 1451: 1447: 1402: 1398: 1345: 1341: 583:Timeline of computing 2020–present 14: 3368:C-Class Computer science articles 3358:Computing articles needing images 1224:WikiProject Articles for creation 924:Knowledge:WikiProject Mathematics 609:Computing articles needing images 3428:High-importance Systems articles 3413:High-importance physics articles 3323:Knowledge level-5 vital articles 3269: 3226:. Further details are available 3213: 3063: 3056:"Hadelin De Ponteves" listed at 2996: 1454:. Further details are available 1441: 1405:. Further details are available 1392: 1348:. Further details are available 1335: 1294: 1214: 1200: 1189: 1097: 1087: 1066: 992: 982: 961: 927:Template:WikiProject Mathematics 891: 881: 863: 822:Knowledge:WikiProject Statistics 795: 774: 728: 703: 459: 382: 361: 336:An editor has requested that an 259: 245: 231: 198: 189: 45:Click here to start a new topic. 3393:WikiProject Statistics articles 3294:until a consensus is reached. 3072:. The discussion will occur at 1648:there is already an article on 1150:This article has been rated as 1045:This article has been rated as 842:This article has been rated as 825:Template:WikiProject Statistics 751:Knowledge:WikiProject Databases 429:This article has been rated as 314:This article has been rated as 294:Knowledge:WikiProject Computing 3333:C-Class level-5 vital articles 2823:https://hdsr.mitpress.mit.edu/ 2597:Gift, Noah (4 February 2019). 2107:15:25, 12 September 2013 (UTC) 1882:then everybody will be happy. 1696:indicates that you may have a 754:Template:WikiProject Databases 297:Template:WikiProject Computing 218:It is of interest to multiple 1: 3242:— Assignment last updated by 3107:05:08, 19 November 2021 (UTC) 3034:02:21, 17 February 2021 (UTC) 2968:Data Journeys in the Sciences 2962:Data Journeys in the Sciences 2952:Data Journeys in the Sciences 2765:10:44, 23 February 2019 (UTC) 2744:19:26, 19 February 2019 (UTC) 2726:17:32, 19 February 2019 (UTC) 2687:16:56, 19 February 2019 (UTC) 2659:02:16, 20 February 2019 (UTC) 2624:15:37, 19 February 2019 (UTC) 2440:10.1080/10618600.2017.1384734 2408:19:28, 10 November 2017 (UTC) 2393:01:50, 10 November 2017 (UTC) 2308:20:26, 29 November 2018 (UTC) 2228:10:31, 17 February 2016 (UTC) 2161:22:55, 24 February 2014 (UTC) 2125:10:23, 17 February 2016 (UTC) 2008:19:04, 7 September 2014 (UTC) 1614:Jim Gray (computer scientist) 1578:10:58, 17 February 2016 (UTC) 1560:05:50, 24 February 2016 (UTC) 1541:13:35, 19 February 2016 (UTC) 1517:10:58, 17 February 2016 (UTC) 1130:Knowledge:WikiProject Systems 1025:Knowledge:WikiProject Physics 1019:and see a list of open tasks. 918:and see a list of open tasks. 816:and see a list of open tasks. 663:Tag all relevant articles in 403:and see a list of open tasks. 288:and see a list of open tasks. 42:Put new text under old text. 3438:WikiProject Systems articles 3398:C-Class mathematics articles 3304:22:54, 8 February 2024 (UTC) 3252:01:09, 1 November 2022 (UTC) 2895:22:02, 22 October 2019 (UTC) 2874:15:06, 22 October 2019 (UTC) 2559:. NATIONAL ACADEMIES PRESS. 2549:National Academy of Sciences 2373:03:27, 22 January 2015 (UTC) 2327:10:33, 2 December 2018 (UTC) 1870:That description supposedly 1496:19:49, 17 January 2022 (UTC) 1431:19:49, 17 January 2022 (UTC) 1382:19:49, 17 January 2022 (UTC) 1325:19:49, 17 January 2022 (UTC) 1133:Template:WikiProject Systems 1028:Template:WikiProject Physics 672:WikiProject Computer science 448:WikiProject Computer science 392:WikiProject Computer science 3458:Implemented requested edits 3383:C-Class Statistics articles 3204:20:41, 22 August 2022 (UTC) 3165:00:01, 12 August 2022 (UTC) 3132:23:34, 11 August 2022 (UTC) 2816:Harvard Data Science Review 2693:Piyanka Jain (2019-01-29). 2591:14:53, 7 January 2019 (UTC) 2280:highlights advocacy efforts 1951:This seems even worse than 1945:05:58, 4 January 2013 (UTC) 603:List of computer scientists 50:New to Knowledge? Welcome! 3474: 3348:C-Class Computing articles 3088:17:34, 30 April 2021 (UTC) 3050:12:36, 17 March 2021 (UTC) 2543:06:50, 26 April 2018 (UTC) 2523:21:27, 25 April 2018 (UTC) 1839:12:54, 21 April 2019 (UTC) 1818:07:14, 13 April 2019 (UTC) 1156:project's importance scale 1051:project's importance scale 435:project's importance scale 320:project's importance scale 2945:03:27, 14 June 2020 (UTC) 2709:they just move on. E.g., 2293:12:41, 16 June 2018 (UTC) 2274:22:00, 13 June 2018 (UTC) 2218:refers to the same issue 2214:This talk by Terry Speed 2208:01:33, 28 June 2014 (UTC) 1930:12:24, 26 July 2012 (UTC) 1780:19:46, 5 April 2018 (UTC) 1710:18:16, 4 April 2018 (UTC) 1626:21:12, 3 April 2018 (UTC) 1602:09:22, 2 April 2018 (UTC) 1502:Overview, full of rubbish 1260: 1209: 1171: 1149: 1082: 1044: 977: 943: 876: 841: 790: 723: 665:Category:Computer science 441: 428: 415:Computer science articles 377: 335: 313: 254: 226: 80:Be welcoming to newcomers 3453:Accepted AfC submissions 3423:C-Class Systems articles 3408:C-Class physics articles 3282:redirects for discussion 3264:Redirects for discussion 3058:Redirects for discussion 2984:21:11, 2 July 2020 (UTC) 2843:16:06, 3 July 2019 (UTC) 2810:15:23, 16 May 2019 (UTC) 2491: 2242:04:29, 26 May 2018 (UTC) 2187:16:20, 24 May 2014 (UTC) 2075:09:46, 12 May 2013 (UTC) 1917:Zero intelligence agents 1858:16:46, 01 May 2019 (UTC) 946:project's priority scale 667:and sub-categories with 2673:Harvard Business Review 2640:removed them recently: 2049:07:27, 4 May 2013 (UTC) 2034:01:46, 3 May 2013 (UTC) 1980:07:26, 4 May 2013 (UTC) 1965:01:43, 3 May 2013 (UTC) 1892:22:27, 2 May 2019 (UTC) 1691:There is a lengthy and 907:WikiProject Mathematics 3363:All Computing articles 3318:C-Class vital articles 2964: 2792: 2786:The State of Open Data 2776:The State of Open Data 2478:. Microsoft Research. 2359:http://jsresearch.net/ 1257: 1168: 1105:Systems science portal 805:WikiProject Statistics 628:Computer science stubs 332: 282:information technology 75:avoid personal attacks 3230:. Student editor(s): 3022:business intelligence 2960: 2784: 2551:just published this: 1906:I would like to add 1829:as much as possible. 1458:. Student editor(s): 1409:. Student editor(s): 1352:. Student editor(s): 1303:. Student editor(s): 1256: 1234:Articles for creation 1231:for more information. 1197:Articles for creation 1167: 737:WikiProject Databases 331: 269:WikiProject Computing 205:level-5 vital article 100:Neutral point of view 3443:C-Class AfC articles 930:mathematics articles 446:Things you can help 105:No original research 3286:redirect guidelines 3280:has been listed at 3070:Hadelin De Ponteves 2788:, a 2019 book from 2575:their download page 1113:WikiProject Systems 1008:WikiProject Physics 828:Statistics articles 3228:on the course page 2965: 2793: 2494:Doing data science 2247:negatively toned: 1874:based on sources, 1768:various references 1462:. Peer reviewers: 1456:on the course page 1407:on the course page 1350:on the course page 1301:on the course page 1258: 1169: 899:Mathematics portal 757:Databases articles 333: 300:Computing articles 214:content assessment 86:dispute resolution 47: 3011: 3010: 2947: 2931:comment added by 2565:978-0-309-48247-9 2177:comment added by 1998:comment added by 1908:this Venn diagram 1820: 1804:comment added by 1287: 1286: 1283: 1282: 1279: 1278: 1184: 1183: 1180: 1179: 1061: 1060: 1057: 1056: 956: 955: 952: 951: 858: 857: 854: 853: 769: 768: 765: 764: 698: 697: 694: 693: 690: 689: 686: 685: 356: 355: 352: 351: 183: 182: 66:Assume good faith 43: 3465: 3279: 3273: 3254: 3236:article contribs 3225: 3224:16 December 2022 3221: 3217: 3160: 3153: 3146: 3140: 3067: 3026:Sam at Megaputer 3000: 2999: 2993: 2981: 2976: 2871: 2866: 2840: 2835: 2807: 2802: 2754: 2741: 2736: 2716: 2711:Norman Matloff. 2702: 2677: 2644: 2635: 2621: 2616: 2606: 2588: 2583: 2569: 2533: 2520: 2515: 2506: 2488: 2465: 2443: 2189: 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article 3170: 3166: 3162: 3161: 3154: 3152: 3151: 3145: 3136: 3135: 3134: 3133: 3129: 3125: 3124:68.134.243.51 3116: 3111: 3109: 3108: 3104: 3100: 3092: 3090: 3089: 3086: 3085: 3084: 3075: 3071: 3066: 3059: 3055: 3051: 3047: 3043: 3039: 3038: 3035: 3031: 3027: 3023: 3019: 3016: 3015: 3014: 3006: 3002: 2995: 2994: 2988: 2986: 2985: 2982: 2977: 2975: 2969: 2963: 2959: 2953: 2950: 2948: 2946: 2942: 2938: 2934: 2930: 2923: 2921: 2916: 2913: 2909: 2906: 2900: 2896: 2892: 2888: 2883: 2878: 2877: 2876: 2875: 2872: 2867: 2865: 2859: 2854: 2847: 2845: 2844: 2841: 2836: 2834: 2824: 2821: 2820: 2817: 2814: 2812: 2811: 2808: 2803: 2801: 2791: 2790:African Minds 2787: 2783: 2777: 2774: 2766: 2762: 2758: 2752: 2747: 2746: 2745: 2742: 2737: 2735: 2729: 2728: 2727: 2723: 2719: 2714: 2707: 2704: 2700: 2696: 2690: 2688: 2684: 2680: 2675: 2674: 2669: 2664: 2660: 2656: 2652: 2647: 2646: 2643: 2639: 2633: 2628: 2627: 2626: 2625: 2622: 2617: 2615: 2604: 2600: 2595: 2594: 2593: 2592: 2589: 2584: 2582: 2576: 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