Thursday, 30 March 2017

This is the night


This is the night

Later the weight of wood, the darkened sky,

those who will see strange things, those who deride him.

We do not see Jesus enthroned on high.

The picture's clustered soldiers almost hide him.


Blindfold, he singles out no captor's fist.

The childhood-nasty blares from the horn

deafen Jesus. Worn, he does not resist.

This is the night. We must pray for dawn.


'This is the night' is my response to Albrecht Dürer's print The mocking of Christ.  It's my contribution to the '26 prints' project organised jointly by the writers' group 26 Characters and the Eames Fine Art Gallery. The Dürer and my poem are on display in the gallery, along with 25 other prints and 25 other writers' responses to them, until 16 April, and all the works are reproduced in the exhibition guide.

Sunday, 19 March 2017

Thing 21: Managing citations

The post behind this assignment sends us to Zotero, ORCID, and Google Scholar.

Zotero

This round of 23things has taken me further with Zotero than I've been before. In my 2010 post, I wrote that I had attempted to use Zotero a couple of years previously, but been deterred by the facts that "I had to download Zotero machine by machine, and could use it only with Firefox".  For this '23 research things' assignment, done on my home laptop, I've succeeded in embarking on a Zotero library via Chrome, and ventured an in-text citation in Open Office Writer.  By the time you read this, I may have seen how I get on using my workplace computer's Firefox and MS Word.

I expect that my two principal uses of Zotero will be these: 

(i) to keep track of material used in Alumni Festival presentations, as in my abortive experiment of 2008 

(ii) to help any library users in their own explorations of referencing software.

ORCID

I have set up an ORCID account for myself in the same spirit as Librarian at heart, who signed up for ORCID even "while I may not be publishing papers any time soon", and with similar motivation (cf. (ii) above): "it’s useful to know how ORCID works as the University is trying to persuade everyone to get one, and it’s good to be able to offer advice based on experience when people ask".  And, like ResearchGate, Academi.edu, LinkedIn and some less serious sites, ORCID will be a way of tracking down visitors, donors, and other library users we might lose sight of.

Google Scholar

I have set up a Google Scholar account for myself, again with no prospect of papers any time soon.  I don't intend making it public.  I was glad to find that Google Scholar offered one publication of mine (amongst those by several other people with similar names) for inclusion in my citations list, a gratifying discovery even though the number of its citations stands at zero. 

Monday, 13 March 2017

Thing 20: Presenting data

I must admit I've never had a favourite chart of choice, nor can I immediately recall a data presentation either bad or good enough to stick in my memory.  But I have tried out one of the data visualisation tools mentioned in Georgina's post. I went for easel.ly, the one that had been used by the other participants, following their praise for its ease of use.  It took me a certain amount of trial and error to use it, especially as I didn't see a 'Help' page.  However, I hope you agree I have succeeded in making a Venn diagram of data from my blog post of January 2011, on poetry competitions.

The data concerns my poetic output from 1977 to 2011, as recorded in the card index I've kept since 1994.  Of a total 218 indexed poems, I counted 95 that had been specially written for competitions, 67 that had been published, and 25 that had been both written for competitions and published. Making the Venn diagram required some revisiting of 'O'-level maths, to determine whether the radii of the smaller circles should measure against the large circle in the ratios 95/218 and 67/218, or in ratios of the squares of 95/218 and 67/218, or in the ratios of the square roots of 95/218 and 67/218.  But I think I got there.

I have not used Microsoft Excel's SmartArt facility, but I suppose I had better try it some day, if I'm going to make a habit of Venn diagrams.
.

Monday, 20 February 2017

Thing 19: Text and data mining

I've seen Georgina's post on this topic.  Its most important advice is likely to be this:

"If you wish to use TDM in your work, we highly recommend that you ensure you are doing so legally and that you contact likeminded folk such as the team at ContentMine to ask for advice."

Will do.  My own post, like those of other participants, has to be short for want of experience.  I have not had occasion to use data-mining in my own work, but I now know that any research query that sounds as though data mining would help towards the answer is a matter for ContentMine.

Meanwhile, I suppose I get a frisson of what data mining is like when I dabble in Google Books' Ngram Viewer.  This enables the user to search vast numbers of books for the occurrence of phrases.  By it I have satisfied my idle curiosity as to the frequency of use of the locution "And Oh!" (it seems to have peaked in 1842 and then slowly declined), and the relative frequency of the phrases "railway station" and "train station" (the latter overtook the former in 1994, and peaked in 2000; they now seem to be rapidly converging again).  But I am not an expert user of this site, and I increased my knowledge of it around 150% in the past hour, revisiting it for this post.

Monday, 13 February 2017

Thing 18: Research data management (RDM)

This is where I hit the '23 research things' hard stuff.  Research data management is an area where I have clearly more to learn than things like Twitter.  I draw comfort from other participants' blogs, in which similar confessions are made.

I'd better start by copying out those four types of data that Georgina names in the post under that link above:

- Observational – so data captured in real-time that is usually irreplaceable and can include anything from survey data to images of someone’s brain. 

- Experimental – this can be data from lab work which can be reproducible such as gene sequences. 

- Simulation – this can be data generated from test models where the models themselves are sometimes more important than the results, such as climate or economic models. 

- Derived or compiled data – this is data that is reproducible and can include 3D models, text and data mining, and compiled databases.

A waterfall of consciousness notes that data management begins with "personal diaries, work e-mails, holiday snapshots and, even, home videos".  Emboldened by that, let me tell how I have managed data at such a level.

Personal diaries.  Mine go back, in an unbroken series, to 1 January 1969.  I keep them all together, in a reasonably consistent compromise between size and chronological order, and I usually have no difficulty finding a particular year.  I say "usually" because my latest search of them failed.  The unfound years are presumably buried on my desk somewhere, and maybe it's time for a spring-clean.

Work emails.  For these I have many folders.  When I answer an email, I incorporate the incoming email into my reply, save that thread, and delete the incoming email.  This works, though not as well as it used to, by reason of the sheer volume of email to deal with.

Word documents and spreadsheets.  In the days when my Word documents were mostly letters, naming them was an easy matter of applying the date, written yymmdd, plus a sequential number for letters written on that date, and the file type extension ("17021201.doc").  An adaptation of that applies to things that fit into a regular sequence ("170212minutes.doc").  But I'm a bit indecisive with other files, leaving the form of the date and the relative position of date and content liable to variation ("170212members.xls", "Events Feb 2017.doc").  I need to get a grip.

Money statements.  Domestic money statements I've got more or less under control.  They're still on paper, for the most part, and I shred them after set intervals (three months for those relating to food and cash withdrawals, two years for those relating to utilities, six years for all others).  Bank statements and similar I keep in separate files for each account; bills &c from other organisations I keep in an A/Z sequence by organisation, and within each organisation in reverse chronological order.  All this is a consequence of reading Taming the paper tiger at home by Barbara Hemphill, which I'll have read ca 2002.

Poetic output.  This I keep track of using a card-index system I devised in 1994.  The card fronts show poem title, number of lines, and year of composition; the backs show where I've submitted the poem and when, and the outcome of the submission.  While a poem's being considered by an editor or competition adjudicator, I flag the card with a yellow sticker. If an unpublished poem is between submissions, I flag the card with a blue sticker.  If I'm lucky enough to have the poem published, or placed in a competition, I mark the card front with a diagonal red line and the place of this success.  And all this information is necessary.  Poetry competitions often have rules about number of lines, and about the ineligibility of poems that have been already published.

So all the above attempts at data management are creaking, and the paper-based ones will have to be replaced with electronic equivalents sooner or later.  The poetry card index might be worth replacing with a database -- something I've had some training in, but never actually made.  An alternative might be to mark the information among the properties of the file, but I can see two disadvantages to that: the risk of information loss between file versions, and the amount of digging that would need to be done in order to get at the information.

Further research needed.  What a thing for Love Your Data Week!

Monday, 6 February 2017

Thing 17: Survey tools (ii)

An update on what I posted on 8 January.

I said then I'd created a survey, using Google Forms, on the subject of superhero powers.  It has drawn a single response, which is obviously not an adequate statistical sample.  100% of respondents named telekinesis as the superpower they hadn't got, and television as the source of their hearing about it; they were disappointed not to have this power, had aspired to it, and, for the story behind their aspiration, gave the following statement:

"Moving equipment would be a gesture away! Computers would be instantly fixed because I willed it to happen."

Let us press on to Georgina's recommended application, Qualtrics.  This is now live for me, and I've had a go at creating a survey using it. It's a spoof, I admit, and neither an illuminating survey nor particularly funny, but had me exploring large areas of Qualtrics that I shall be able to evaluate properly as I use them, or not, in creating surveys in earnest for the Haddon. They will be no worse for this dash of prior Qualtrics experience.

Sunday, 8 January 2017

Thing 17: Survey tools (i)

This post is an interim progress report.  I have, as Georgina bids us, applied for a Qualtrics account; I have made a survey using Google Forms while waiting for Qualtrics to arrive, and tweeted links to said survey.  Later, I will do a 'Thing 17: Survey tools (ii)' post, reporting on how I find Qualtrics and what answers, if any, my Google Forms survey has drawn.

The survey takes its cue from the 2017 Libraries at Cambridge conference. Registrants at the conference were invited to indicate what their superhero powers were, and a few did.  But the conference included much -- a panel discussion and a well-received keynote address -- on the theme of failure.  My survey asks respondents about superpowers they don't have.

Reading the posts of other '23 research things' participants has been most instructive, particularly Luther's notes about the limitations of surveying as a technique and the usefulness of other methods. He is quite right to note the ease with which spurious survey returns can be created; conversely, a toxic situation can be inflamed by insinuations that some survey returns are bogus, even if the insinuations have no basis in fact.  Luther's reference to 'grounded theory' took me on to unfamiliar territory, and I look forward to exploring this further.  Trying to relate it to my my own experience, I suppose it was something like grounded theorizing when I examined the free-text responses to a Haddon Library user survey, and when I asked library users informally why they thought a particular teaching session had had zero take-up.  In both cases I was trying to see if any patterns emerged.

Of these things, more when Qualtrics is in.  And any superpower survey responses.