I've written a technical book using Bookdown, which is hosted on GitHub and is open access. As an academic, I'd like people to be able to cite the book, and normally that would be done with an ISBN and DOI. However, I'm not sure what is the best way to get hold of these.
Could anyone tell me the best way to go about this? I am not looking for any royalties, and the book will likely be updated every now and then, so I don't see much point in using a self-publishing service like Amazon, or going through a classical publisher like Springer, CRC, etc.
My ideal end scenario would be just to have the book open access online, but so that it can be cited (I mean properly cited, ideally with ISBN and/or DOI). Any ideas?
p.s. apologies if Stack Overflow is not the place for asking this, not sure where else to ask.
Getting a ISBN costs money, and I do not think it will work well for free online only books. However, getting a DOI is free and easy either by publishing the book as a pre-print on arxiv without peer review, or using zenodo. You can even automatically generate new DOIs for newer versions with GitHub actions.
Related
R offers a breadth and depth in statistical computing beyond what is available in commercial
closed source products. Yet R remains, primarily, a programming language for the highly
skilled statistician, and out of the reach of many. --- The R Journal Vol. ½, December 2009
Note: Name changed from Interactive R Language Online Learning Platform: CloudStat School
As stated, R is the best tool and is the lingua franca of statistics. But many people, especially my students found difficulties to use R.
I wish to make an interactive R Learning Platform, called CloudStat School.
The best way to learn R programming is doing while learning.
In CloudStat School, you will see a console box at your top left hand side, while the lesson notes at your top right. Bottom is the output box. Anything you “Run” in console box will be shown as a result in the output box.
So, while learning the notes, you can “run” the R examples immediately without open another windows, software or tabs. You can do it in a page.
I did make a simple working prototype:
Lesson 1: Overview of R Language & CloudStat School
The prototype is simply integrating R Web that hosted in Pôle Bioinformatique Lyonnais in iframe.
If many of you think that this idea great, I would start making a better version.
This is my current simple idea, hope to get some feedback from you.
Thanks a lot.
It would probably be much more resource intensive and require more effort to create, but check this out: I found Code Academy to be a fun way to tinker with JavaScript. Unfortunately the site is (so far) only for a single language and a closed-source, venture-backed startup.
The main problem is that Rweb (as I am learning right now) does execute everything in batch, so this interpreted line-by-line approach used in CA probably cannot be done with it. If you were to create a similar app to CA for R, you'd have to open an R session for every user, hence the resource intensiveness disadvantage stated above. Hope this can be overcome, maybe someone will have an idea.
Hope you find this useful, at least as an inspiration for your endeavors. I wish you the best of luck.
A couple of pointers that might help: Eloquent Javascript and CodingBat.
Eloquent Javascript is an "interactive Hyperbook" where the students can edit and try out the examples right there in HTML as they are learning Javascript. Might be worth a look to get ideas for CloudStat.
In CodingBat, Stanford professor Nick Parlante's has been doing (for Java and Python) exactly what you are attempting to do for R learners. Especially relevant is the Authoring Page.
The success of your CloudStat School will be in getting crowdsourced contributions. To that end, my suggestion is for you to create 4-5 really good exercises with levels and hints, and then to focus on the 'meta' aspect of directing others to create the R exercises for you. Provide instructions for creating hints, tests, code, and tags. You could even consider assigning the task of 'creating new exercises' as a midterm/endterm projects to your R students for extra credit.
Hope that helps and good luck.
Commonly, there are two method of R Learning, one is step-by-step, like what CloudStat School is doing, as well as other R Language books and websites. This is good especially for those (newbie) learn R without specific purpose.
Another one is learn through problems. When you face specific problems, need specific functions, you are forced to learn it. Instead of "start from zero", the better way is learning through examples. This work even for experienced R users.
Since we want to make the best Interactive R Language Online Learning Platform, we need to add as many analysis examples/study cases here. If you need to get some ideas to make a statistical analysis with R, there is a place you will visit first. :)
I'm about to start my honours project at uni on OpenCL and how it can be used to improve modern game development. I know there is a couple of books out now/soon about learning opencl but I was wondering if anyone knows any good papers on opencl.
I've been looking but can't seem to find any. Part of my project requires a literary review and contrast so any help on this would be appreciated.
I'll not point you directly to any papers, instead I'll give you a few hints on where to look for them.
Google scholar, One of the best places on the web to search for papers on any subject. Searching for "opencl game development" turned up a few interesting results right on the first page; for sure there are other valuable results in the following pages.
IEEE Explore; IEEE is one of the de facto establishments on all thing computer and electronics; their journals and conferences have many publications on OpenCL in particular and parallel processing in general. IEEE Explore is their search engine, although usually all articles are also referenced in Google Scholar (but may be easier to find using IEEE explore).
ACM Digital Libray; ACM is a large and important institution like IEEE, but with even bigger focus on computing. You will find many papers on OpenCL there.
Google, Yahoo, Bing, etc; sometimes when everything else fails, using normal search engines can go a long way. You may find information about ongoing projects, important game developers blog posts, etc. All of these can be valid references if there aren't more (be sure to search really well before concluding there aren't more).
You should favor articles published in scientific journals over: a) papers or extended abstracts published in conference proceedings; b) corporate articles, not peer-reviewed, usually found in the respective corporation websites; c) articles published in general scientific knowledge magazines (e.g. Scientific American, etc.).
Sometimes you may not be given access to certain papers, which you will be requested to purchase. Usually, universities have subscriptions to many journals or such, as such you may have better luck trying to download the PDFs when accessing the web inside your institution. If you have no luck, sometimes the authors put "preview/unfinished" copies of the articles in their websites (sometimes they even put the dubiously legal published copy). As a last resort, you can always contact the authors directly, they'll most likely send you the article by email (it's of their own interest).
Finally, to learn OpenCL, I found that a mixture of reference manual, quick reference card and looking at examples from Intel, AMD, Nvidia and IBM SDK's goes a long way. No doubt a book will help, though I can't recommend you any, because I didn't read any.
This probably isn't the answer you wanted, but believe me, it's the answer you need to do a good work.
Good luck!
My teammates and I have a very challenging new project to do, and we are supposed to submit it next week. We don't have a single clue about how to do it, and really need help. We are undergraduate students, new to Information Retrieval and AI, and really need your ideas.
The project is roughly:
When an expert is cited in a document,
find an expert with an opposing
opinion & find out what he/she says
about that topic.
We are free to use any programming language, but we are not concerned with the programming. We would like help to get us started. Please give us a rough idea on how to design such a system and how to retrieve information on the internet. How should we get his opinion, then find an opposite opinion?
Simple: use Amazon's Mechanical Turk.
Without that (or an equivalent) you're in trouble. If there are no further constraints on the problem then you will need a full-blown AI, the kind that doesn't yet exist. If there are severe restraints then you might have a chance of doing this in a week. If the expert can be in any field (medicine, politics, history, fashion, science, comic books, etc.) then there will be no single, well-organized repository of essays. You'll have to use Google to find Dr. X's opinion. Once you find Dr. X's writing (and let's pray it's text, not audio) you'll have to do some kind of natural language processing to get the thrust of it, even if you're lucky enough to find a descriptive title ("Digital Photography Is Absolutely Great"). Then you have to figure out it's opposite. What's the opposite of "Neil Gaiman draws on folklore for his story ideas"? Figuring out what opinion you're looking for will be a serious problem. After that, things actually get easier: you can google for the subject and use the same magic tools to find the one you're looking for.
So what do have a chance of solving? A search for opinions that someone else has already organised into "pro" and "con". Some online political forums are organised that way. Wikipedia cites opposing views in a special section in some of its articles. Science journals print letters of rebuttal. Look around, you might find a site even more cut-and-dried. Choose a small enough arena and you'll have a tractible problem.
EDIT: Damn, Ben Dunlap beat me to all my major points in a comment. Sigh
Sounds like an NLP problem to me. As for the information about documents and cites, http://citeseerx.ist.psu.edu should be a good starting point.
For each paper, there are several citations which refer to the paper. At the very minimum, you have to scan the abstract of the paper and that of the citations and run your own algorithm to figure if any citation is of the opposing opinion. Maybe your professor can give you hints on some approximate heuristic, but as far as I know it is a really hard problem.
I would be watching this thread for more interesting approaches.
Automatically submit a Google search request similar to "expert_name sucks", "expert_name wrong", or something like that. Find the first result that has "PhD" with a document link in the same sentence and return the link.
I think you might be blowing this up a little too big... as an undergraduate project, I would approach it a little more small scale.
Unless your specification says you must use actual internet resources, you would be better off creating your own database of custom short documents. Add metadata to each document stating the points they make about certain topics.
Next, I would create a list of citations which link to each document and add some metadata representing that experts stance on the topic. When someone reads a document, I would augment the list of citations with lists of links to documents which have alternative views on that topic.
Basically it would consist of these tables:
Document (id, data)
DocumentPoints (documentId, topic, stance)
Citation (documentId, topic, stance)
And when someone loads up a document, the citations are pulled up as well. For each citation, you search DocumentPoints for the same topics with different stances. The most difficult part of this project would be creating the 5 or 6 documents you need to have data in your database. After that the solution is trivial.
On a side note, most of these other answers are telling you to use some existing solution... don't do that unless the assignment tells you to. You'll be much better off understanding the problem and various ways to solve it (this is definitely not the only/best one) if you work through the entire problem yourself. When the teacher asks you to do something not supported by whatever product you chose to implement your solution on, you wouldn't be able to fix it. If you had just written it yourself, you could just as easily implement to the new spec as well.
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Closed 11 years ago.
In my work experience, most fresh out of school programmers are set right to creating reports for 6-12 months or so. While I see the benefit of doing something non-crucial, it seems to really discourage them.
So my question is, should organizations allow newbies to work with someone experienced right off the bat, obviously doing non-critical phases of a project, do get a real feel for what their career choice has in stock, or throw them on reports out of the gate?
Ah, there really is nothing like exploiting interns for remedial jobs...
Seriously though, you get back what you put in. Forcing them to do a thoughtless, thankless job for a long period of time is a quick way to build up a useless team member.
Perhaps they should be looking for a job at different companies? Maybe they shouldn't settle?
I was once a fresh-grad, and I have never been asked to work on a report. I had a programming check-in within the first 5 days of my job.
Maybe I am confused about the question. We are talking about folks who apply for programming positions and are sent to doing "reports" related job?!
I didn't start in "reports". I started on a conversion -- just get stuff to run on the new platform. Relatively safe, minor programming changes.
Then I did some new development for a while.
Then another conversion.
Then -- 2 years into my career -- no longer a complete n00b -- I wound up in "Reports". They wanted something like a dozen dumb-as-dirt accounting reports. Each was a "pull from the general ledger", "do some quick math" and "write a columnar report". [It was 1980, that's how stuff was done.]
I couldn't stand to do copy-and-paste programming. So I wrote a thing that extracted from the ledger into an array of values. It used a flexible notation for doing calculations on values in that array, then it wrote out the results of the calculations.
It could add, subtract, multiply and divide. You could use multiple operations on a series of "cells" to compute wonderfully complex things. To a limit.
I had invented the spreadsheet, built as a COBOL batch program. Seriously. That's what putting someone on reports can lead to. A single program that produced the dozen dumb-as-dirt financial reports. And a large number of additional reports, too.
Bonus. It was built in an Agile, incremental fashion. The first version did a half-dozen of the really easy reports. The next one did two or three more.
I don't think "reports" is a bad gig. What's bad is forcing people to copy and paste yet another dumb-as-dirt report program from a cookie-cutter template.
I believe it to be beneficial. It's what happened to me long ago and it provided me an opportunity to learn the database schema, the domain, and how the data is being used.
But, if they were hired as a Software Engineer they shouldn't be a report writer indefinitely. Programmer/Analyst however...
It's beneficial to the company in the short run, because then you can get useful work out of new graduates. It's harmful to everyone in the long run, because creating reports isn't really that hard, so the newbies don't learn much from doing it.
That being said, 6-12 months is a really long time to stick anybody on doing reports (unless they enjoy it, which most people don't). Maybe a shorter time period would be better training for a new employee.
I've worked in shops that threw a lot at the new hires where the results were mixed and I've worked at shops where they did pointless monkey-business exercises such as writing reports that nobody would read, attending 'process' meetings and open-ended tasks like "read a book about C++" or "learn something about this technology or that one. Both of these approaches were a waste of effort and time.
At my shop, if you are the new guy you aren't going to get left to your own devices to figure out X or to create busy work for yourself. Typically, we'll run you through our products so you are familiar with them as a user, then we'll talk through whatever task it is we need you to do, do the "I'm right over here, tell me if you need assistance" thing and then check up on them during the morning "what are you working on?" meeting. The goal at my shop is to get a developer up to speed as quickly as possible without skipping over the important stuff.
I think the key to successfully developing the new employee, particularly one who may be right out of school is to challenge them, provide them with interesting tasking that will make them not dread coming to work. If you get them interested in the work, you get an employee who becomes valuable. There are some tasks that just aren't interesting, and we all do them at my place. For me, I dread getting anywhere near MS Word to write formal documentation, but that comes with the territory sometimes. The 'new guy' needs to realize it won't always be code slinging or new development. Sometimes it is maintenance coding - much of the time it is. Sometimes it is 'turn the crank' type work. Sometimes it is report writing.
A good manager or senior developer will mentor the new hire. If a shop doesn't do that, I'd probably not want to work there myself.
They should be pair programming (or spectator programming) with different people from their department for a few weeks. Then they get to know all the people, the structure, the code and useful tips.
Reports are a wonderful introduction.
They tend to have very specific specifications, unlike many other projects. They're a good "stand alone" task. They also give the developer a good introduction to the domain model, which they must use to actually get the data out for the report.
Finally, they're (typically) reasonably simple with some reporting framework doing most of the heavy lifting for them. So they need to focus on learning the tools of the trade, deployment, and the data model.
They're a nice gradual introduction to the larger domain and application.
I've never been put on a non-important job as a safety function. Even when I didn't know exactly what I was doing I got put on important projects people wanted yesterday, and then paired with someone who had specific development he/she wanted to offload onto the new-hire.
It works pretty well that way.
If you put a college grad on report-writing duty for a long time, he's going to bail on you. Bad management and a waste of money...
I have two contrasting experiences with Crystal Reports in two different companies:
With my first employer (fresh out of University), our Crystal Reports expert was leaving, so I was asked to take over the role. No actual training was provided, so I had to learn everything on-the-job, with no support from either the Vendor or the Employer. Although my position description was as an IT Developer, I eventually spent 100% of my time working on Crystal Reports. It was an unproductive experience for me, and a waste of manpower and resources.
My current employer asked me to assist another Developer in creating and maintaining their Crystal Reports setup. Because they provided adequate training, and I was mentored in the role, I gained knowledge on multiple systems and databases. I even a little experience at administrating and maintaining SQL Server. And I also got the chance to interact with many different clients in the company, as many different sections of the company needed these reports.
So my answer to the original question is that it really depends on the organization, rather than the central concept. If your employer is intending to use it as a way of familiarizing new employees with multiple systems, then I think it's a great idea. If it's just a short-term way of foisting a thankless (and rotten) job on a hapless new employee, then I think it's a waste of manpower and resources.
The good thing about reports is that they are not updating information so there's no chance that any data will be lost.
Depending on what the tools are for reporting too. When I did reporting, I learned tons about SQL, and stored procedures. Of course that is probably not the norm for reporting.
It depends on the report, and it depends on the job. Many reports are anything but trivial, and excellent SQL skills are needed to create a performant and properly maintainable back-end. If your newbies are good with SQL, let them cut their teeth on the queries. It will be a good way for them to learn the schema of your database.
However, if "putting them on reports" is just a euphamism for them trying in vain for hours without direction or inspiration to format a table in Crystal reports 25 (or whatever the current version is), well, I think you probably already know my answer to that question...
Are there any real world applications written in the Clean programming language? Either open source or proprietary.
This is not a direct answer, but when I checked last time (and I find the language very interesting) I didn't find anything ready for real-world.
The idealist in myself always wants to try out new languagages, very hot on my list (apart from the aforementioned very cool Clean Language) is currently (random order) IO, Fan and Scala...
But in the meantime I then get my pragmatism out and check the Tiobe Index. I know you can discuss it, but still: It tells me what I will be able to use in a year from now and what I possibly won't be able to use...
No pun intended!
I am using Clean together with the iTasks library to build websites quite easy around workflows.
But I guess another problem with Clean is the lack of documentation and examples: "the Clean book" is from quite a few years back, and a lot of new features don't get documented except for the papers they publish.
http://clean.cs.ru.nl/Projects page doesn't look promising :) It looks like just another research project with no real-world use to date.
As one of my professors at college has been involved in the creation of Clean, it was no shock he'd created a real world application. The rostering-program of our university was created entirely in Clean.
The Clean IDE and the Clean compiler are written in Clean. (http://wiki.clean.cs.ru.nl/Download_Clean)
Cloogle, a search engine for Clean libraries, syntax, etc. (like Hoogle for Haskell) is written in Clean. Its source is on Radboud University's GitLab instance (web frontend; engine).