Maren Deepwell

Category: CPD

  • #23things: Digital Curation meets Halloween

    img_4340I have started week 8 on the #23things course a day early. I am in a Halloween mood and the digital curation project seems like an ideal place to combine some course activity with weekend fun. This week has two parts, first on digital curation, which I am focusing on, then also digital note-taking. As I do that quite regularly I am not going to go into it, but there’s plenty to discover on my first look at Tumblr following the brief to find Tumblr blogs I like and to share them. So here goes: I started searching for things near me, which led me to the Bodleian Libraries account. From what I can see there are frequent posts, a mix of images, short articles and useful information. I really like the visual aspect of this account. Searching for libraries led me to discover a ‘Vintage Libraries’ account where I spent quite a bit of time searching through the archive by decade, having a look at the ‘Vermont Book Wagon’ for example. Looking through this made me wonder how images are licenced on Tumblr, and in the case of this particular blog, I found the following statement: “None of the photos are mine. I’ll always state the original link from where I took the pictures, unless I do not find the original source. If you know the source from any those pictures, please let me know.” . That took me back to thinking about copyright and the previous things we have explored on this course.

    Sticking with the literary theme, but also with Halloween in mind, I started looking for authors whom I like and found busy posts by Neil Gaiman. This includes all kinds of random content and it was interesting to compare how this relates to for instance Twitter posts, where I follow the same author. I am not sure whether I would find using Tumblr more useful or appealing, but it’s interesting to explore a new platform. Sticking with the Halloween thread I started looking for themed posts and came across a post that linked directly to Instagram, another platform that I don’t use. Given that it was a drawing of pumpkins and cats, I was interested – but after some more exploring I decided that I had enough.

    So, in addition to the ’23 things’ things I was exploring, I am now thinking about how alien social media platforms can feel when you don’t use them or have no familiarity to draw on. While earlier weeks looked at platforms I knew well, this week has made me consider what I could use tools like Tumblr, Instagram or Storify for. Storify I come across regularly for tweet chats or conferences, so there seems more of an obvious use for it, but it’s curious to discover a wealth of content in new places that I didn’t come across before. And it’s a useful reminder that it’s necessary to try new things even if I don’t end up using them day to day.

  • #23things: taking a “flaneur” approach to discovering digital knowledge

    passages-3
    Illustration from Walter Benjamin’s Passagenwerk http://margininversi.blogspot.co.uk/2012/06/walter-benjamin-i-passages-di-parigi.html

    The Flaneur is one of my favourite figures, in particular in the writing of Walter Benjamin whom I discovered as an undergraduate. I was, and am, interested in the Flaneur as he is a useful device for exploring a city, for thinking about how urban life changed during the industrial revolution and beyond it – and because of the idea that walking with a tortoise as a fashionably slow accessory/pet one could discover the pace of observation. The Flaneur discovers the world at his, and I think it is a predominantly male, pace and directs his gaze where others may not even glance. I was thinking about this because I have been finding that my own engagement in the 23 things of the course by the same name has very much proceeded at my own, slow pace, sometimes on my own and sometimes in company. That is because I am taking part as part of a team (and I have written earlier posts about our approach) as well as spending time exploring some of the things that I have a particular interest in.

    As a team we are in the middle of block 2 of course content and in our weekly team meetings talking about the course has become a useful focus point for discovering common questions, exploring interests and discussing areas for professional development. We, as a group, continue to benefit from the course as a joint venture in learning new things and that in itself is extremely useful.

    But beyond our common participation I have been having a look at what the next few weeks of course will bring, what things I might discover… and to return to the Flaneur, I feel very much that there is a host of wonderful things waiting to be discovered in the arcades of digital knowledge before me. One topic in particular that I am interested in is Digital Curation. Not something I am overly familiar with and also a topic that encourages us to explore Tumblr, a tool I don’t use as yet.

    So, #23things, while the first 12 things have been very rewarding to encounter and discover so far, I am looking forward to the next 11 even more. With my trusty tortoise at my side I shall proceed at my own pace.

  • #FLcoding16: we meet graphs in the second week

    week-2It’s the second week of the course ‘Learn to Code for Data Analysis‘ and we have started making graphs! Alongside my course participation on FutureLearn I am posting a short summary of my experience on my blog (you can read also my post from Week 1).

    I found this week a lot quicker to get started, partly because I am now more familiar with the course structure but also because the Anaconda interface I am using is becoming easier to navigate. That was a good thing because I have less time this week. Picking tings up where we stopped in Week 1 this part of the course introduces new concepts and methods leading to learning how generate graphs using the plot function. I found generating my first few graphs and changing what they showed immensely satisfying. The data we are using this week is about the weather and the project of the week enables you to use weather data from your own location.

    In order to practice some of the syntax and get more used to using the interface I have started creating my own fictional data set which I am experimenting with in a separate exercise book. Hopefully there will be more time to play with this and the weather project next week. For now, the course continues to engage and educate – enabling me to learn the basics at my own pace. One study resource that I have found particularly helpful is the weekly glossary. I have downloaded both of these and use them to help remember different concepts. See you in Week 3…

  • #FLcoding16: learn to code for data analysis week 1

    flcoding1It’s the first week of the course ‘Learn to Code for Data Analysis‘ and I have just completed all required steps – so this short post is a quick reflection on my experience so far and it’s been a great week!

    Once I got stuck in there were a couple of things that work extremely well for me: first, using the course instructions on the Futurelearn platform together with the Jupyter notebook and exercise data creates a clearly structured and engaging environment. I dipped into the comment sections for some exercises when I got stuck, but in general I found the first week’s exercises really interesting and helpful. I did end up getting things wrong and then learning from the errors that were generated, but it felt both challenging and achievable. Given that this is my first time with the software and the coding language, I think the course works extremely well. It provides a good balance between context and technical elements, both of which combined to draw me in even as a complete novice.

    While I am interested in the data we were using in week 1 (mainly WHO data, similar to what I have come across during graduate study) what I found most rewarding was gaining a better understanding of the various approaches and how they can be applied to small and large sets of data. Again, the course structure demonstrates the thought process alongside the mechanical steps, which was very effective. My favourite interaction with the exercises was the little messages that appeared after completing one, referring you back to the course platform. It was a small thing, but it made a big difference to how easily I could navigate an alien environment.

    I dipped into the course a couple of times during the week, first to have a look around and read some introduction material, then again to read some more and watch the first videos and then a third time to get stuck in with the actual exercises and quizzes. Sorting large tables by columns and calculating different averages was particularly satisfying… I installed the software etc the week before, so that things were ready when I got started. I liked the information and prompt provided to share the work from the course and I might do so in the following weeks, but this week I feel the whole process is still too new for me to want to share more than my thoughts.

    So far, so good – a really engaging and rewarding first week with lots of practical knowledge gained. Looking forward to week 2!

  • #23things: twitter archive, no facebook… social media reflections

    I am using thing no. 7 (Twitter) and thing no.8 (Facebook) of #23things to note some reflections on how I use social media. This is about my individual professional or personal use, rather than any organisational perspective.

    So, starting with Facebook, I find I have little to share. I am a reluctant Facebook user, strictly using it for personal relationships with far flung friends and for keeping in touch. Reviewing my Facebook timeline since I joined in 2007 reveals three clear trends: I post about the weather, the weekend and my cat. You could probably write a programme to auto-compose posts for my timeline and no one would know the difference.

    Over the past two years I have also had to use Facebook for a project, more reluctantly still, and I have to admit that I have a lot to learn if I ever want to leverage that network for my professional aims. Moving on…

    marentags
    Twitter archive using TAGS

    Twitter I joined a few years and 3k+ tweets ago – to provide holiday cover for someone who was travelling. It took me some time to get the hang of it, but since then it’s become a most useful space for me and I would echo many of the observations made by other participants in their posts about how valuable it can marentags2be. It’s easy to forget how few people in general are using it however and I find it irritating at times when media becomes to referential to what people have tweeted instead of finding other sources. Last year I installed Martin Hawksey’s TAGS twitter archive (read more about how to make your own) and ever since then I have been happily archiving my tweets and conversations. This is actually the first time I have had a look at the “top hashtags” in my own little universe of tweets and while it’s predictable to me it’s also interesting and useful and will probably be more so over time. I like tweeting about my own work as well as interesting or useful things I come across, but there is always a lot more on Twitter than I can follow. I dip in and out and enjoy the random things I find. Unless I am at an event I rarely tweet at high volume and I have plenty of days when I don’t use it at all. There isn’t always something to say.

  • #23things: (algorithmic) transparency and diversity

    This week on the #23things course that I am participating in together with my colleagues I read an article on diversity, described thus:

    Can computers be racist? Big data, inequality, and discrimination– An excellent article, including video of a lecture given by Dr. Latanya Sweeney, on how big data can perpetuate and exacerbate existing systems of racism, discrimination, and inequality (see this week’s full text here)

    I found the article really stimulating not least because I am interested in the growing movement behind public interest technologists (link to the full article). One paragraph in particular caught my eye, specifically a recommendation on how we may overcome the bias in relation to inequality inherent in big data practices:

    Pressing for “algorithmic transparency.” By ensuring that the algorithms underpinning critical systems like public education and criminal justice are open and transparent, we can better understand their biases and fight for change.

    It’s a recommendation I think makes a lot of sense, but I have come across many instances where this isn’t the case. In many cases only the expert developers involved in creating the system really understand how it works. That leads me to consider where efforts to make algorithms underpinning critical systems more open and transparent will meet the growing expertise professionals in for example education need to have in order to approach the technology at their disposal in an effective way.

    Yet while the article has certainly prompted me to think and read further, it’s also reminded me that even the simplest or most commonplace technology can create problems. #23things uses examples like exploring accessibility features on mobile devices or the use of emoji/bitmoji to get us thinking about wider issues and those are easy to relate to. Anyone who like me functions as tech support for family members for example has likely been grateful that a mobile phone’s text size or colour contrast adjusted to suit the needs of elderly users. There is a huge spectrum of issues that opens up before you when you start focusing on accessibility and diversity.

    For me, these two of the #23things are a useful reminder that this is an essential part of what we do every day and that there is always a lot of room for improvement.