SpringerImages is a growing collection of scientific images that spans the scientific, technical and medical fields, including high-quality clinical images from images.MD. The continually updated collection – currently over 1.5 million images – gathers photos, graphs, histograms, figures, and tables, and is available to libraries and their patrons via a searchable online database. The SpringerImages interface enables users to search faster, more broadly and more accurately, through captions, keywords, context and more, even jumping from the image to the source article. Users can create personalized image “sets,” and can easily export images for use in their own presentations or lectures.

The service offers a range of potentially innovative features.

Being able to search, organise and download high quality images as PDF from a large corpus of books and journals might represent a breakthrough in the dissemination and reuse of non-textual content from the scientific literature. Usage factors related to images may provide additional metrics of scientific impact for authors and journal editors. From the end user’s point of view, the collaborative annotation functionality is an interesting addition, although it may not be obvious to convince users to massively start tagging and annotating images. Last but not least, a prominent button allows users to bookmark images via CiteULike (a Springer partner) in the same way as references (images available from SpringerImages will be the displayed as thumbnails from the correspondent article page). It is worth reporting details on the access conditions, as the full availability of the service (in particular access to full-resolution images) is tied to Springer’s institutional subscriptions. The set of freely accessible images is–helas–a tiny portion of the complete database.

Anyone can create an account and search the free and Open Access images indexed by SpringerImages. Access to the complete collection is available via subscription to libraries, research institutions and individuals. Images obtained from SpringerImages can be used for almost all noncommercial purposes, including integration into presentations and PDF documents.

• plot the sky above your head tonight at 3am
• look up your genome for occurrences of a specific sequence
• compare current unemployment rates for countries you would like to move to
• display the taxonomic tree of your favourite bug
• spell boredom in Morse
• disclose the Answer to Life, the Universe, and Everything
• you can even check your body mass! (am I really 3kg away from my ideal weight?)

Depending on your field of expertise, Alpha is likely to provide a powerful combination of computational tools and relevant data sources to calculate virtually anything you might want to know about the universe.

Apart from technical use, though, I am curious to understand whether and how people will start using Alpha as a productivity tool and integrate it in their daily workflow.

Granted, the title of this post may be overstated, as I am sure there are better ways to use Alpha to work less and live happy. Here’s my take of the 10 best productivity tips I was able to find out, please prove me wrong with better examples and I will add them to the list below.

1. Word count for humans

How often have you tried to figure out how many pages or words make 7,000 characters? Alpha can help you out, even if you speak German.

2. Convert any character

Type a character (e.g. ∞) and quickly look up its corresponding Unicode, HTML, TeX or Mathematica representation. You can obviously do a reverse lookup as well.

3. Look up URL information

You can display a nice summary of information on site ownership (from WHOIS), popularity (from Alexa) and HTML structure for any given URL.

4. Find English words matching a specific pattern

No more tip-of-the-tongue frustrations! OK, I have to think of an actual use for this one but I am sure that the poets among us will appreciate.

5. Calculate time differences

Ever wondered how much hours are left before light comes through your friend’s window in Tokyo?

6. What’s in a word

Definitions, synonyms, antonyms, word frequency, pronunciation (AmE only though…), hy–phen–a–tion patterns for any word in the English language. I even discovered that “hack” and “adulteress” are neighbours in a synonym network.

7. Where am I?

Check your current network name and IP address.

8. Tame nutritional values

If you desperately need to know how much iron is in your spinach salad or how many calories your breakfast is worth, Alpha has answers for you.

9. Convert currency

Enjoy watching how your purchasing power in Europe kept falling indefinitely over the last months, before showing some timid sign of recovery.

10. Estimate download times

Stay zen when you know that it will take slightly more than one day to download those 90GB with your 7.5Mb/s broadband connection.

Even more ideas

There are plenty of tools and Web services to do most of the above searches, but it’s nice to be able to query anything from a single search field. I obviously can’t wait for the day when the full power of Alpha will be unleashed via its API so as to be mashed with external data sources and applications, or integrated as a clever QuickSilver plugin to put the world’s knowledge at the tip of your fingers. Unfortunately it will take some time before this happens.

In the meantime, if you are looking for inspiration, you can browse the Wolfram Alpha community page: it’s a goldmine of ideas (and a good source of information on some ridiculous flaws and limitations in Alpha).

Maybe writing a blog post is too time consuming, and the barrier of entry is too high. An easy solution is microblogging: services like twitter let you share a tiny bit of something interesting you found (with a link), and anyone following you will receive it.

The thing with microblogging is that it doesn’t take much effort to share. Many people (including me) thought it was silly at first, but now it’s mainstream.

Since twitter provides real-time search you can find what people talk about right now. If you want to monitor a special topic, chances are someone came up with a unique way of identify the topic. A spontaneous way of organizing information outside the ‘follows’ structure emerged: the hashtag. These are terms that start with #, example: #iranelection. We have set up #AcaProd for academicproductivity. If you have an idea, or read something outstanding that you would like to share with us, just tweet about it and add #AcaProd somewhere in the 140 characters. Your tweet then is easily found by anyone interested in the topic. We will display all tweets in our front page too.

I found myself sharing a lot of interesting stuff over twitter, and much more often than through a blog, so I have a good feeling about this.

Of course, you should keep sending ideas/suggestions/complaints using our email, blog@academicproductivity.com

Aug 2008 – SCHOLARLY USE OF THE WORLD WIDE WEB – Research Front Map – ScienceWatch.com

This is a citation network that shows highly cited papers on WWW. Diameter relates to citation: the two bigger circles are the paper that proposed the Hirsch index, and King’s paper on the scientific impact of nations. Clicking on the circles provides details on the papers.

There are many other fronts:

• Fast Breaking papers. These papers comprise the top 1% of papers in each field and each year
• Top Topics selects the Research Fronts with the largest absolute increase in size in each of the 22 major fields covered by Essential Science Indicators

Worth keeping an eye on.

Moving to more modern OSs (I’m running windows server 2008 64-bit), it simply didn’t work anymore. Plus it never worked well with Firefox or thunderbird. Anyway, I’ve found a much better replacement: Comfort type. It was hard to find, because reading the site, it’s not clear that it can do this kind of job. Looks like this feature is just one more for the author… which is quite impressive since it costs $20, half of what intellicomplete costed.

The main advantages over intellicomplete are:

• Multi-language support. This is killer, you can switch quickly with a shortcut, and as it learns it places words in different dictionaries
• It works on More OSs and applications.
• It also gives typewriter-like auditive feedback, which somehow makes me write more. Subconsciously, my body knows that if you don’t get the typing sound, you must be doing something passive. It’s also helpful to let people on the phone with you know when you are typing (so they don’t think an intimidating silence just started)
• It detects caret on more applications. Not very well on Tunderbird/Frefox, but better than anything else I’ve tried

The problems I can see right now are:

• It doesn’t complete with tab; only numbers, or enter. Enter can be a bit of a pain. This doesn’t bother me much because my tab finger was getting too much work anyway.
• Sometimes is not as fast as I’d like. When it completes a word, you can see it going back and retype what you wanted.
• Sometimes it hangs, but resetting it works.

What is interesting about this application is that it replaces quite a few others. For me, it replaces: Keepass (or any Password Manager) because it has encryption, and Autohotkey (for some basic templates).

Important: it doesn’t work with java applications. Could be a deal breaker. It even works when I use skype.

Most reference managers graft themselves to word or to openOffice. For example, Mendeley, and zotero both use internal reference functionality in word. In doing so, they use features that are available only on those editors. I think this is a big error for at least 3 reasons:

1. I draft my papers on a text editor or oneNote. This has a lot of advantages for me. But I would not be able to use say Mendeley or Zotero on oneNote; and I do want to keep references on my notetaking tool. Using a text editor has a lot of nice advantages over a word processor too, if you know how to use it.
2. It’s a lot faster to massage your reference the way you like it. It takes several clicks on zotero to get an Author (year, p. XX) reference. In endNote, it’d be a few keystrokes.
3. There are bottlenecks in our digital lives that are plain text. For example, emails, forum posts, and google docs are cases of writing that may need reference management but are ill-served by most current offerings. I want to copy-paste chunks of scientific writing and still carry my references; there’s life outside word processors, and quite a lot of it!

So what reference managers work ok on plain text. Well, here is the surprise: as far as I know, only bibTeX and endnote. This is surprising because they are the oldest. One would have thought that newcomers would have taken advantage of what these older tools learned.

Lurking in the Zotero forums, I saw people asking for support of this exact feature. But it seems that it’s never going to happen. It would take a lot of reengineering, and all users that are happy with the current solution (and have amassed a large body of authored docs) would complain.

so, where does this leave me? I need to either comply and write everything in word to take advantage of Mendeley and Zotero, or stick to oneNote, but use endNote references. Of course I could also do everything on a text editor and use bibTeX, but right now, it’s more trouble than it’s worth.

Does anyone know a good solution for my setting?

My starting point for this post was simple; I wanted to know how my productivity has changed (hopefully improved) since I first started my DPhil. From keeping a research journal, I know that some days are more productive than others and it would very helpful if I could understand when those fits and starts occur, to spot co-occuring events and thereby learn when to say “Forget work, I’m going for a run.”

In other words, I wanted to plot my productivity cycle over time. It might look something like this:

But the obvious problem with this exercise is how to measure productivity. It’s a subject that’s been tackled indirectly on this site before but going through the old posts, I haven’t yet find any attempts at a general theory – and related measures – of productivity. So drawing on the collected wisdom of previous AP.com posts, here’s a rough sketch of such a theory.

What is productivity?

Most simply, productivity is a question of efficiency: what outputs can be produced for a given amount of inputs? If you were working in a factory, measuring productivity is therefore fairly straight-forward: widgets per hour might be a nice personal productivity measure. But in an academic context, these inputs and outputs are not so easily defined.

This dilemma is briefly introduced in a discussion of productivity for programmers, where Gil Gordon suggests that when we say productivity, we really mean effectiveness. In other words, unlike a factory worker, our outputs can be multi-faceted and might be judged by their:

• Quantity (how much gets done)
• Quality (how well it gets done)
• Timeliness (when it gets done)
• Multiple priorities (how many things can be done at once)

Nevertheless the basic efficiency model is a good template for our model. So if P = productivity, O = output and I = input, we can write the basic definition:

Defining outputs

There are many different kinds of academic output. Papers, citations, funding received, teaching feedback, and promotions are just some of the ways in which we can measure our success, either directly or indirectly.

But as Jose pointed out previously, these outputs are all trying to attract a scarce resource, namely attention, and success in attracting attention results in prestige. So we might say that, for a given class of task t, output could be measured as:

where p_t is the prestige associated with task t and n_t is the number of those tasks completed in a given time period.

Measuring prestige varies with the task. For journal papers, citations seems like a sensible measure but for other tasks, this may involve a lot of guesswork. If your university has guidelines on promotion, they can be useful in identify how much of your professional success is expected to come from teaching, research and so on. But most likely you will need to use a technique like Analytic Hierarchy Process to unify your prestige measures.

Defining inputs

If you follow the game of cricket, you are probably familiar with the Duckworth-Lewis method. In an English summer, it often happens that one team has finished batting and their opponents have just started trying to catch the target score when it begins to rain. Rather than call off the whole game, the DL method is used to adjust the target score to account for a reduced amount of playing time. To do this, Messrs. Duckworth and Lewis developed their model using the concept of resources.

With productivity inputs, we can do something similar. The amount and quality of work that we can achieve depends on the resources available to us. But instead of wickets and overs in cricket, academic input resources might include time, money, lab access, the attention and effort we can devote to a task and so on.

Again, some of these inputs are more easily measured than others but if we want to generalize our model, we need some sort of conceptual common currency like we had with prestige on the output side. An economist might attempt to convert everything to money: how much would I have to spend to acquire this piece of data? But to link with our earlier discussion of prestige, I think a more useful framework is to convert everything to a common attention unit: let’s call it the Atnu for short (AU is already taken).

1 Atnu can be defined as the amount of attention necessary for a reference task, such as reading a journal article. It’s a rather arbitrary unit, but it’s intended to acknowledge that an hour of hard concentration is not the same as an hour spent doing miscellaneous administrative tasks like sorting through emails. It also has the advantage that you can define the Atnu as it makes sense to you and your work; if you spend time in a lab, performing an assay might be the base unit. My only suggestion would be that it is the defined as the most attention-consuming task. That way, the most difficult part of your day will correspond with actual hours.

So for task t, we can say that the total input is the total amount of attention hours spent on the job.

where a_t is the Atnu value for task t and h_t is the actual number of hours spent working at that level.

Final notes

Putting it all together then, productivity is the amount of prestige we earn for each attention-hour we invest.

It is a very simple model but from the form of this equation, we can already draw a few practical conclusions (even if they just confirm what we intuitively knew already):

• Productivity is maximized by concentrating on those activities that earn you the most prestige for the least effort. Conveniently the form of the equation is linear so that, assuming not all of the variables are unknowns, you could apply linear programming techniques to come with fancy “optimal” productivity strategies.
• Since the number of hours in a day is fixed, and we can arguably only give our full attention to a fraction of these hours, we should try to improve productivity by reducing either the number of hours or the amount of attention that a task requires. Some strategies let you do both things at once. For example, co-authoring a paper means you can delegate some of the work to someone else; you only need to invest a reduced amount of attention-hours to manage the project but you’ll receive similar amounts of prestige. Case in point: the world’s best connected mathematician.
• For those tasks that you have to do yourself, use your time wisely. This means balancing the levels of attention required by different tasks so you don’t burn out and focusing on those that earn the most prestige. This is why so much of what we write about here is concerned with time management, especially those tools that help us finish necessary but unrewarding administrata. See this post in particular.

What about actually implementing the model?

• Fitting the model to data and standardizing the coefficients for a large population will be difficult. As covered in this interview with Dan Navarro, there are “some big individual differences” in how people work; we shouldn’t put too much hope on one model holding for everyone.
• The interview also touches on another related issue: uncertainty. A strict optimization strategy is probably impossible because you don’t know the prestige associated with a task a priori. As Dan says, “it’s striking the right balance between exploration [of new ideas] and exploitation [of existing work]“.
• A related implementation issue is the problem of timing when collecting productivity data. This is two-fold: 1) when does the prestige arrive relative to the task being completed and 2) what is the temporal resolution of the feedback? One task may yield many different types of “prestige”: a small immediate personal satisfaction for completing a paper, a medium term recognition as it is published in a journal and cited, and maybe 50 years later receiving the Nobel Prize for your work. More from the archives on this here.
• I’ve said nothing about the psychology of productivity. It seems to me there should be feedback and “versus expectation” terms in all of this. Our earlier posts on learning theory and managing large projects (1,2,3,4,5) discuss the need to set clear goals, evaluate your performance against targets, and to learn from these experiences, changing your habits for next time. Such evaluations are key to maintaining your motivation and productivity.
• I’ve also said nothing about the physiology of productivity. What is the role of diet, daylight hours and half a dozen other factors?

So there you go. My two cents on what all of this productivity stuff really boils down to. I’m curious to see what you the readers think. Is this a crazy idea? Should we be trying to model productivity in such a formal way? Does anyone have the appetite for a community effort to gather some data and test the theory out?

Some people have chosen a wiki for their scientific homepage (Dario posted a tutorial in How to run an invisible wiki). I have considered it myself, although I’m more inclined to use a wordpress blog (post on how to set it up to maximize google scholar’s chance of getting your pubs coming soon!). One of the advantages of a blog over a wiki is that one can use a very good WYSIWYYG tool, windows live writer. Unfortunately only for windows. Now, this advantage is gone: one could reasonably set up and update without having to ftp files around or use crappy editors that come built-in with most wikis.

EndNote maker’s lawsuit over open-source Zotero dismissed – Ars Technica