But real academic publications should have a DOI - it's an identifier which is supposed to make it easier for people to find and cite paper. You know how books have a unique ISBN? It's like that.

I couldn't find a way to publish this via my university, which was a little disappointing. And I didn't have the time or energy to rewrite it for submission to a journal. Then a couple of people suggest that I submit it to arXiv.

arXiv is a free distribution service and an open-access archive for 2,243,321 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

So I registered for an account using my uni email address and selected a suitable topic. I picked Computer Science / Human Computer Interaction - which felt the closest to what I'd written about.

The process was simple enough. Fill in a form then upload a PDF. Then the interminable wait for moderation. It only took two-week.

And, then, it was published!

And, with publication comes a persistent DOI - 10.48550/arXiv.2304.10542.

Now all I need to do is wait and watch my h-index grow 🤓

The main point, I agree with. Citing a whole paper is a lossy process. Saying "Smith, J (1963) Practical Time Travel, Gallifrey Press" is basically fine but it doesn't tell you where in the publication the bit is you're citing.

Xiao & Ballou contend that the answer is to add a page number to every citation. I think that's a simple solution - but almost always the wrong way to solve the problem.

Firstly, page numbers aren't stable. If you've got the large-print version of a paper, it will have a different page numbers than the regular print edition. Paperbacks and hardbacks have different numbers. The paper copy might be formatted differently from the digital copy.

Secondly, most modern documents simply don't have pages. Anything published as HTML / ePub won't have a page number. Page numbers are a skeuomorph in those contexts.

Finally, even if there is a stable page number - is that precise enough? A page may have several hundred words in multiple sections. Page numbers aren't granular.

I've ranted before about I consider Quoting Page Numbers from eBooks is Considered Harmful.

So what's the solution?

URl fragments!

A properly formatted document should be accessible by sub-section. For example:

example.com/papers/time-travel.html#2.3.9-Eye-of-Harmony

That takes us to the paper we want, and straight to the anchor heading we're discussing. This also works with the obsolete PDF format.

Now, not all papers have the correct markup to do this. That's OK! We can cheat using Text Fragments. That allows us to link to the first instance of a specific string of text in a document. For example:

example.com/papers/time-travel.html#:~:text=Reverse the polarity of the neutron flow

I genuinely think both of those solutions make more sense than hoping that your reader has a copy of a paper in exactly the same format as you do.

One of the things I found most frustrating during my MSc was how... old fashioned academia was. PDFs with two column layouts, unreadable fonts, paywalled knowledge trapped in moribund formats. Let's try to drag it into the late 20th Century, eh?

At the time, all the FOAF relationships were defined in terms of positive sentiment. There wasn't (and still isn't) a FOAF representation for "divorced" or "estranged" or "fired by". I thought this was a failing. I understand why we all might want to play nice on the Internet. But sometimes it is useful to know about "negative" relationships.

For example, I want to organise a seating plan for my wedding - it's helpful to know that Alice and Bill divorced and can't be on the same table, Carol doesn't talk to David. Bill is in a relationship with David and wants to keep it secret. Ellen would like to know Alice better. That sort of thing.

More modern versions of FOAF have properties like enemyOf and wouldLikeToKnow. Which I think makes a great deal of sense.

And so we come to Academic Citations.

Using Google Scholar (or any other knowledge graph) I can find just about any academic paper. More importantly, it lets me see every paper which references that paper.

Great! I can see if something has been cited lots of times, or very few times. That gives me a weak signal about its "importance".

But it tells me nothing about the sentiment of those citations.

Suppose I've just read (Smith, 2015) and I want to know whether the consensus is that the paper is a work of genius or absolute horseshit. What are my options? I can find all the citations of it, then manually read each one to determine whether the author thinks Smith is off their rocker or not.

Wikidata has support for this. The Cites Work property can have roles like "objection" and "endorsement"

This means, in theory, someone could build a knowledge graph which says "Smith's argument rests on Jones' paper, but Xi's paper and Zhang's paper both object to Jones. Hook disagrees with Zhang's analysis, but these 500 papers disagree with Hook."

Why is this important

One problem that modern social media has is that its algorithms have no knowledge of sentiment. Whether you share a cute kitten video to make your friends smile or share a hateful message by a bigot in order to whip up a frenzy against them - the algorithm sees the same signal; +1.

This means the outrage economy grows quickly. All "shares" are seen as positive sentiment. The algorithm sees lots of shares, interprets that a positive signal, and then further promotes the content - or similar content. There is very little way that a social network can filter content by "agrees with" or "disagrees with".

Things like Facebook attempt to map sentiment with a series of emoji.

In theory, you could tell Facebook not to show you posts which have more than 10% of anger reactions. Or only show you posts with positive sentiment. I say "in theory" because Facebook profits off your rage, so has no interest in helping you moderate your emotions.

Popping back to academia for a moment. I recently read a paper that I disagreed with. I wanted to know if I was alone in my objection. This is currently no way for me to find all the citations which also disagree with the paper.

Why this will never happen

The first thing that stops this is that it is a lot of extra work for a human to perform. With hundreds of citations per paper, it would be a massive burden to categorise every single paper mentioned in passing. Most academics can't even be bothered to write alt-text for their images, so any extra labour is likely to be resisted.

The second problem is that sentiment is hard! Can it be boiled down to just "agrees with" and "disagrees with"? What about "Agrees with methodology but not conclusion" or "Disagrees with some definitions but supports others"? There are hundreds of different sentiments. Even just positive and negative probably need degrees of strength associated with them.

In the glorious future where DEEP AI and MACHINE CLEVERNESS rules, it might be possible for a computer to read an academic paper and determine whether it concurs with the papers referenced therein.

Perhaps we need an army of (paid?) dogsbodies to manually go through every paper ever published and assess the sentiment behind each citation?

But, for now, we have to make do with weak signals and uncertain sentiment.

Recently, someone let me know that they'd found one of GitHub repos in a paper they'd read. It hadn't even occurred to me to search for those!

So, shove your GitHub URl into Google Scholar - https://scholar.google.com/scholar?q=github.com/edent - and you'll see if any repos have made it into academia.

Have you spotted any of your code in interesting places? Let me know in the comments ☺

Leigh Dodds

@ldodds

Discovered that someone built a tool for making SPARQL more usable by building on my sparql-doc tool:

Paper: ceur-ws.org/Vol-2721/paper…

Terence Eden is on Mastodon

@edent

Well worth searching your GitHub URL with Google Scholar.
E.g. scholar.google.com/scholar?q=gith…
Great way to find out if your code has made it into any academic publications. pic.x.com/fpysrjhws6

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Simon Willison

@simonw

Thanks to this tip I just found out Datasette gets a mention in this academic paper! "What Else Is New? Open Data Users Need to Know What’s Changed" computer.org/csdl/magazine/…

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🕊

@sephr

Replying to @edent@edent Woah I got 8 pages of results. Completely unexpected!

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Daniel Schildt

@autiomaa

Google Scholar search results scholar.google.com/scholar?hl=en&… found one academic reference to my list of companies that use GitHub. github.com/d2s/companies/…

Documentation can be useful in research & learning.

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Pratyush Mittal

@faltoo

Wow! Screener.in has been cited in at least 21 papers: scholar.google.com/scholar?start=…

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I'm not a big fan of it. First, I'll explain how to opt-out your websites. Then I'll explain why I don't like the service.

Block Their Robot

TurnItIn scans the web and records everything on your website. It then uses that to tell Universities whether a student has plagiarised from you. While I don't condone cheating, I haven't given TurnItIn permission to store my content and profit from it.

Their website gives you details on how to prevent your site being slurped up in the first place.

It's as simple as adding the following to robots.txt:

User-agent: TurnitinBot
Disallow: /  

That should stop TurnItIn from crawling your site in future. But how do you remove all the content they've stored?

Remove your website

I fundamentally disagree that a private company should be able to profit from my works by storing and selling access to it. I wrote to their legal department, and got this in response:

In order to delete content from our database, please provide proof that the content you are requesting to remove belongs to you. Acceptable proof would be:

• A confirmation from an instructor at the university that the work is yours
• A confirmation from the admin at the university that the work is yours
• Draft papers, proof of communication with the university, proof of upload

Please also reconfirm the URL of the content that needs to be deleted.

I emailed them to correct their misunderstanding. My blog is not an academic work (LOL!) and was not written for a University. After a couple of weeks - and several further emails from me to escalate - I got this back:

We have encountered an issue when trying to remove your content. The problem is that the website has been around for some time and was initially crawled by our old crawler. Please rest assured that we take the request to remove your content seriously, and our legal and content teams are already currently working on populating a complete crawl set from our old indexed content. Once this tool is created, we will be able to fully unindex your website, including any links crawled by our old crawler.

A little later, they updated me with this:

Just to further add, our crawler engineers have stated that they’ve unindexed and deleted all of your pages that they are aware of, until we have the ability to perform a granular search on our database for the older indexed links. If you find any other content still indexed, please let us know, and we will remove it.

Testing

I submitted a draft paper which had a selection of paragraphs drawn from my blog posts. Essentially trying to see if they'd accuse me of plagiarising myself. It came back saying that it detected plagiarism and then displayed the full contents of my blog post.

The left shows the paragraph I uploaded. The right shows the full text of my original blog post.

There were over 60 URLs of mine that TurnItIn said it had records for:

After 5 months of complaining to TurnItIn, I discovered that they cannot remove content which was stored prior to 2015. So I've submitted DMCA complaints to their hosting company and registrar.

OK, but why?

There are a couple of arguments, that I have. Firstly, I have rights over my blog posts. There are Fair Dealing exceptions to UK copyright law but I don't think TurnItIn can take advantage of any of them.

Regarding copyright of my essays, here's what TurnItIn say:

Students who submit papers to Turnitin retain the copyright to the work they created. A copy of submitted papers is retained in a Turnitin database archive to be compared with future submissions—a practice that helps protect and strengthen copyright ownership.

I mean... Yes. I haven't assigned my copyright to them. I just don't think they have the right to store and profit from my essays in perpetuity.

TurnItIn are a bit defensive about the subject of copyright, arguing:

A U.S. District Court judge ruled that archiving student papers to assess the originality of newly-submitted papers constitutes a fair use under the U.S. Copyright Act, provides “a substantial public benefit" and helps protect the papers from being exploited by others.

The summary judgment was unanimously affirmed by a U.S. Court of Appeals.

TurnItIn

My argument is "Fuck You. I don't want you to hoover up my content and then sell it without my permission."

Frankly, TurnItIn can either pay me for my content, or remove it. They sell my content to universities - so they obviously think it has value. I'd like to be compensated for it.

If TurnItIn were a not-for-profit, or a community resource, I'd have some sympathy with them using the web to detect academic misconduct. But, as it is, I don't derive any benefit from them reselling access to my content. So they can get in the bin.

I'm sympathetic to the argument that having students steal my content as pass it off as their own is damaging to me. But I've no evidence to suggest that's a problem. It isn't like TurnItIn sends me an alert whenever it detects plagiarism.

So, I'm opting out. And I hope this guide is useful if you also want to do so.

As part of a data analytics class, I'm learning about "database sharding". That is, the process of splitting data between multiple machines. But where does the term come from?

Wikipedia - the source of all truth - says:

In a database context, most recognize the term "shard" is most likely derived from either one of two sources: Computer Corporation of America's "A System for Highly Available Replicated Data"

It lists the reference as "Sarin, DeWitt & Rosenburg, Overview of SHARD: A System for Highly Available Replicated Data, Technical Report CCA-88-01, Computer Corporation of America, May 1988"

It is a heavily cited paper. But it doesn't seem to exist!

I've contacted the authors of this, and other papers, but they've not been able to supply me with a copy of the paper.

As far as I can tell, it was originally an internal company report to the Computer Corporation of America. Their new owners didn't respond to a request for archival material.

Perhaps I can't find it because the authors' names are misspelled?

This 1989 thesis from MIT spells the name as "Rosenberg" - with an e, not a u. (Thanks to Suzy Hamilton for helping me find that paper.]

But can we trust this source? Probably; it was written by one Ronni Lynne Rosenberg - and I assume she can spell her own name correctly! I've updated the Wikipedia citation.

But now I'm stumped. Everyone refers to this ur-paper, but I can't find it anywhere. I've checked all the sources I have access to. And even some of those despicable sites which share academic PDFs for free. None of them have it.

This leads me to conclude one of three possibilities:

1. It exists, but I'm too stupid to find it
2. People are citing things which they haven't read
3. I have fundamentally misunderstood how academia works

What do you reckon?

2021-06-30 UPDATE! The inimitable Dr Laura James has found a clue! The British Library holds a copy of "TECHNICAL REPORT- COMPUTER CORPORATION OF AMERICA CCA".

I've requested an interlibrary loan from my university to see if it contains this mythical document.

2021-07-13 Update! Sadly, it's a bust. I got a lovely and detailed email from the British Library. In it, they say:

I have asked my colleague in Boston Spa, in Yorkshire to check the shelves and our holdings for this catalogue record:

Title: TECHNICAL REPORT- COMPUTER CORPORATION OF AMERICA CCA.

Holdings Notes: Document Supply 8715.133000 81/05, 1981-

Shelfmark(s): Document Supply 8715.133000

Sadly it is rather misleading and the dash -, implies that we have CCA-81/05 onwards but in fact we just have that particular technical report and no others. I will ask our data quality team to correct the record for future enquirers.

The quest continues!

One paper had this popular quote in it (emphasis added):

As with many rapidly emerging concepts, Big Data has been variously defined and operationalized, ranging from trite proclamations that Big Data consists of data-sets too large to fit in an Excel spreadsheet or be stored on a single machine (Strom, 2012)

Kitchin, Rob Big Data, new epistemologies and paradigm shifts (2014) SAGE Publications. Big Data & Society. Page: 205395171452848. DOI: https://doi.org/10.1177/2053951714528481

I keep seeing that damned Excel quote. But who originally said it? The "Big Data" paper above references "Strom". Well, here's what Strom has to say for themselves:

Big Data is everywhere. As Bit.ly‘s chief scientist Hilary Mason likes to say: “Big Data usually refers to a dataset that is too big to fit into your available memory, or too big to store on your own hard drive, or too big to fit into an Excel spreadsheet.”

Big Data Makes Things Better - Slashdot.org August 3rd 2012

Aha! It's a blogpost from Slashdot. And Strom is quoting someone else - Hilary Mason. I've seen Mason being quoted saying this before. Here's the earliest Tweet I could find attributing Mason - from April 2013:

Atypic

@ATYPIC

"People think big data is too big to fit in Excel" not really says @hmason #boomconf

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But I couldn't find the original quote. I want to be able to cite who originally said it, and where & when they said it. Not a second-hand transcription.

Googling around, I found this definition of Big Data from July 2013:

“Big Data” is “it doesn’t fit in Excel”

Stéphane Hamel – één van inmiddels meer dan 30 definities van Big Data!.

Data Science – de toekomst van webanalisten?

Interesting! That's Stéphane Hamel - not Hilary Mason. Searching for Hamel's name, lead me to this 2017 article

The simplest definition of “Big Data” is “it doesn’t fit in Excel”

Stephane Hamel comment 8/2012 Big Data – What It Means For The Digital Analyst.

Definitions of Big Data

The "What it means for the digital analyst" page has since disappeared - but is available in the Wayback Machine. Here's the quote in full:

I have joked that the simplest definition of "Big Data" is "it doesn't fit in Excel" - and when you think of it, it's true for most people who wonder how to make the shift from a traditional approach to a Big Data one. Shifting away from Excel forces the analyst to change his approach, view the data differently, and explore new solutions.

And that's a whole lot of fun to do! :)

August 2nd, 2012

There's also a Slideshow from March 2013 in which Hamel uses the phrase:

A bit more digging and I found this document from July 2012:

How Big is Big Data (2013) Columbia University. DOI: https://doi.org/10.7916/d82v2qkb

The @SHamelCP Twitter account doesn't exist any more. And while some of its Tweets are in the Internet Archive, that one is missing. But there are contemporary Tweets which suggest that it was Tweeted at about that time:

Back in 2012, the Retweet function didn't exist, hence the slightly weird syntax. Here's a link to a bunch of people quote tweeting it in July 2012.

The reason @SHamelCP doesn't exist is because at some point it was renamed to @SHamel67. Which means, the original Tweet exists! And here it is:

(Archive link from original)

I reckon that's the earliest directly citable Tweet of the phrase. But there is some evidence of it being used earlier. Here's a report from the BigDataWeek Community meetup in London:

The panel started off with Edd asking, So what is big data? The answers ranged from correct but slightly silly:

   lots of 0s and 1s

to

   too big to fit in x (where x is your usual tool - excel, SQL, memory etc) - Hilary

”Big data, ready or not” 25th April 2012

Here's the video - with the quote at ~15 minutes 30 seconds in:

And, slightly earlier:

“Big Data usually refers to a data set that is too big to fit into your available memory, or too big to store on your own hard drive, or too big to fit into an Excel spreadsheet,” says Mason

Hilary Mason Wants To Get You Started With Big Data 26th December 2011

(Although possibly originally published in September 2011)

Prior to that, things start getting a little fuzzy. In April 2011, Mike Driscoll wrote a blog post about a presentation he gave with Hilary Mason and Joe Adler:

1. Choose The Right-Sized Tool

Or, as I like to say, you don’t need a chainsaw to cut butter.

If you’ve got 600 lines of CSV data that you need to work with on a one-time basis, paste it into Excel or Emacs and just do it

...

When you’re data gets very large, so big it can’t fit reasonably on your laptop (in 2010, that’s north of a terabyte), then you’re in Hadoop, parallelized database , or overpriced Big Iron territory.

The seven secrets of successful data scientists 19th April 2011

So the proto-phrase seems to have appeared between April 2011 and April 2012. By July 2012 it had become much more pithy. And from there became endlessly quotable.

Before April 2011, it was always expressed much more fuzzily. A McKinsey report from May 2011 says:

In some cases, decisions will not necessarily be automated but augmented by analyzing huge, entire datasets using big data techniques and technologies rather than just smaller samples that individuals with spreadsheets can handle and understand.

Big data: The next frontier for innovation, competition, and productivity

And, even further back, here's what RedMonk's Stephen O'Grady had to say back in 2009:

Excel has been used on big data for years, it’s true. But not directly on big data. With a row limit of around 65,000, it certainly can’t be used as a direct window into data warehouses or marts

What’s After Excel? Big Data and the Future of Spreadsheets 19th November 2009

Please don't think I'm picking on any of the people mentioned in this blog post - I've seen the quote attributed to a dozen other people, and to none. It is a catchy little slogan with huge memetic potential. I think it has now now become a standard truism.

But this was a great reminder to me that is always worth following the trail of a quote to see where it leads.

Update!

Thanks to Pete Skomoroch for alerting me to this earlier usage, from March 2009.

jake hofman

@jakehofman

be weary of somone who tells you they're familiar with "big data" and then sends an excel speadsheet.

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Pete Skomoroch

@peteskomoroch

@jakehofman was pondering a blog post on that, often people contact me about "big data" where big = slightly larger than can fit in excel :)

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Pete recollects that people were using this phrase in 2007 — but I've yet to find evidence of it. If you have, please stick a note in the comments.

A friend of mine recommended an obscure book, published a couple of years ago. The blurb made it look right up my alley, so I tried to buy it. I only read eBooks, but I couldn't find it anywhere for sale in the UK. Amazon had a listing for a paper copy, but it was permanently out of stock.

In desperation, I went straight to the publisher. They would ship a dead-tree book across the Atlantic to me. With shipping costing even more than the book.

I found someone on Twitter who was posting highlighted screenshots of the book, so I Tweeted him and the publisher to find out where to get a copy. He graciously offered to send me a PDF.

At which point, the publisher waded in - furious at the situation.

How dare you give this away for free? We're a small publisher and we have to sell books to stay in business!

Fair enough. So I asked them where I could buy an eBook version. Their response was disappointing.

It's only available on Proquest and Ebsco. Sorry!

Both of those are academic databases, available on subscription only, with no public pricing available.

So, let's be clear. You don't want people giving it away, but you won't actually sell me a copy?

What do you want me to do? Not read your book?

I took the emailed PDF. I'm not particularly proud of that. The book is good, and I'm enjoying learning from it. I just wish I could have paid for it.