Project management was the most prevalent message at the initial internship meeting in February. A useful all round skill, it is advocated across all disciplines to optimise time management and learning. I’ve even seen it recommended on parenting blogs as an invaluable skill to impart to young children, to better ensure a more seamless transition between ever busier school lives and extra curricular activities.
Whatever the arguments for streamlining childhood, we, students of Digital Humanities, will be applying project management philosophies to our internship module in order to ensure the smooth running and delivery of our appointed project. At a meeting in the Long Room Hub we were presented with an interesting array of projects and I set off to read through the descriptions and to form a shortlist of preferences. I was immediately drawn to the offerings in Marsh’s Library and to Mining and Mapping in Early Modern Manuscripts, the latter particularly as it formed part of an wider project relating the collection of poetry in 17th Century manuscripts to the social networking relationships of today
The Long Room Hub at Trinity is an inspiring meeting venue – the place speaks of progress and of the generation of new ideas, this occasion left me with a sense of excitement about the term ahead, borne through when I managed to get my first choice of project, the Early Modern Manuscripts work. It’s been some time since I tackled a project though the careful application of tools, milestones and the ticking off of tasks, a quick google saw a trend towards declaring all such methods obsolete, and yet the document we were first to prepare was a traditional Work Plan. I found the exercise useful forcing me to sit with pen and paper and draw up a schedule of dates and deliverables. Appealing as pulses sound, it transpired that the traditional Work Plan was, at the outset at least, still fit for purpose.
An initial meeting with my supervisor gave more direction and focus to the tasks ahead, I was tasked with developing a research paper outlining the visualisation tools used for presenting data, with a view to choosing one to represent the manuscript data on CELM, the Catalogue of English Literary Manuscripts and on a database created by my supervisor.
I went back and forth to college in unseasonably sunny weather, all the time filtering the various elements and strands of the project. Around this time my son required some dental surgery, so my focus was taken away from the project for some time, happily, having formulated this work plan meant the various strands were held together and easy to return to when I was ready to start back with the project once again.
I began with research into the current visualisation scene, comprised mainly of online reading, all writing and evaluations of data visualisation seems available online, even the seminal text, Beautiful Visualisation can be more easily accessed online. Drawing all my reading from online material caused me to feel a little uneasy. I do like the weight of lugging books about the place, it seems to add to the impression that I am labouring to craft a piece of writing, even the ritual of checking books out at the library desk is satisfying, the equivalent of ticking a box, a feeling not replicated by clicking ‘download article’.
I go with the process though, after all how often do we read that process is as important, if not more so, than product, in the realm of Digital Humanities, I tell myself that confining my research to the online reading process may be instrumental in crafting a research paper on visualisations. I read about visualisations being used for digital story telling for digital portfolios, data visualisation and data journalism. The resulting data images, video, text and embedded files become a form of data art, if you will. I scan through procedures for cleaning the raw data, with guidelines such as no nested data, no inline tables and certainly no merged cells, to instructions on file type formats for importing. A distinction is drawn between data illustration in the form of graphs and tables and data visualisation the purpose of which is to alter our perspective, enhance our sense-making and lead us to seek patterns. Seeking patterns is of course a very fundamental human and animal characteristic, one way in which we seek to impose order on the chaos or random nature of the natural world. The data we feed into the visualisation tool, in my case, the instances of the poetry of John Donne in 17th Century manuscripts, must be subjected to the same procedures, to optimise it for import into the visualisation tool of choice.
In all my reading on Data Visualisation, it is almost consistently presented in terms of how it enhances our experience. No longer need we labour through endless dry statistics: visualisation enlivens our exploratory and explanatory experiences with data. This consistent extolling of the virtues of data capture and visualisation begins to nag. There must exist some drawbacks, after all, decisions are made on what data to feed into the tool, who then makes these decisions to measure or not measure particular instances of data? Also, just as code is political, can visualisation be always neutral? Do visualisations sometimes mislead or manipulate? One of the priciples of The London Charter, a set of guidelines for using visualisation in the cultural heritage sector, is that we cannot be lazy with our visualisations, there is a need for rigorous guidelines and an understanding that visualising data or artefacts comes with responsibility.
And so I find I have clicked away from my original research, one of the peculiarities of online research, for me, is my propensity to quickly spiral off topic. Although time consuming, and most probably against the basic tenets of project management, such wanderings are enjoyable even if they don’t always lead to serendipitious discoveries. And so it’s not long before I’m deliberating over good data and bad data. Usman Hague, founding partner of Umbrellium, warns of the perils of fetishising data. His argument runs along these lines: by amassing data to make better decisions we are buying into the idea of humans beings as bugs in the system, Hague extends this to an outcome where we must better trust pure algorithms to make decisions, to ensure optimal behaviour. Although the instances of Donne’s poetry in 17th manuscripts does not immediately throw up problems of engineered behaviour, I find myself thinking about whether better things must always come from data capture and from visualisation. Yes, with data visualisation, we can capture elusive patterns in data, those not apparent by simply perusing statistics, perhaps not available by simply checking a book out of our library, and reading text on a page, my preferred research method. However, the idea that until we could visualise data, with the right tool, we were in some way profoundly lacking insight is a problematic one. The frequently touted analogy of data visualisations shining sunshine into darkness, although a neat soundbite, does not paint a complete picture. And yet I am persuaded by the argument on the Information for Humans blog that “Visualization is organizing one’s perspective of an abstraction, where the abstraction is due to dimension or scale that is beyond our grasp. We are too small to see the whole territory. We are too in the moment to see the progress. We need this help.”