I’m attending the LIBER Conference 2016 on June 29 – Juli 1st in Helsinki, Finland, with a Poster Presentation together with data literacy partner in crime and name brother, Christian B. Knudsen.
The theme of this years conference is Libraries Opening Paths to Knowledge. I really like this framing because it implies that the path to knowledge for the ones we serve, the academic community, does not only lies in the collection of the library and the navigation of this, but also in the surrounding world. As LIBER writes on the conference website:
Ensuring access to knowledge has always been at the heart of the mission of research libraries. In the digital age, and with the growth of Open Science, this implies not only preserving and providing access to content but also opening up new pathways to interacting with and creating knowledge.
The theme are focusing on the following 4 implications on this matter:
1) Content and Processes
Working ever more closely with researchers throughout the research life cycle to encourage and help them to open up their research process and to make both their outputs and methodologies available during and beyond the life of a research project, libraries are moving from curation to creation and workflows.
Engaging in user-led development of services, and a trend towards the creation of shared services as well as developing new methods and opportunities for user engagement.
3) Legal & Ethical
Keeping abreast of emerging legislative developments and considering how to act responsibly to address ethical issues in making data open. Opening up new pathways to knowledge and knowledge creation can also have legal and ethical implications related to copyright and data protection.
4) Space & Experimentation
Rethinking library spaces (physical and virtual) to open up opportunities for experimentation and the visualization of data, and leveraging e-infrastructure to support collaboration and sharing across borders and disciplines.
We are travelling to Helsinki with a poster presentation that have a leg in 1), 2) and 4). The poster is called “Connecting academia with data litearcy: The development of three data labs at Copenhagen University Library” and it looks like this:
The poster is the story about how the Copenhagen University Library, is crossing our Rubicon to expand the scope of the academic library from:
- providing access to a (library) collection + supporting information literacy to navigate in this, to also:
- point the academic community to the possibilities which is made possible with the rapid expansion and access to open data + tools, methods and skills to work with them to get wiser on the World that we are living in
In short: The building blocks for gaining new knowledge has changed. You don’t always need to actually look physical at the world to explore things. One could also set up an API track filter to harvest the Twitter hashtag for Brexit to explore what when down on Twitter when UK left the European Union. Research, education and learning has changed. And when those changes the Academic Library should take a long thorough look in the mirror to see if it’s need to change it’s setup. And I guess we should.
The development is very well illustrated by the story of when I did my master thesis in 2017 contrary to when Rasmus, a random dude studying sociology at University of Copenhagen, did his bachelor project:
Me (20o7): Did 5 interviews with a university director, a library director, two librarians and a governmental dude, to explore the function of the University Library in post modernity. Got 8 hours of interview on tape, transcript them all (took sooooo long), did word count in Word and then started analyzing different discourses from that.
Rasmus (2016): Scraped 2,4 millions posts from online forums about the shady cryptomarket to show how the political discourse has declined over time in this domain – using algorithmic topic modeling to analyze the giant corpus of text.
Our point is not that Rasmus’ works is better than mine was in 2007 – it’s still a valid method. Our point is that students and faculty members of today and the future got different opportunities and as a library we want to connect them with those opportunities.
Yours truly with the Liber 2016 poster
Below the Why, the What, the How + some more of Copenhagen University Library’s support of data literacy through three Data Labs.
Acacemic libraries have been supporting information literacy in academia for many years, but new technological possibilities requires a new skill set – data literacy. Today harvesting gigabytes of data from social media platforms, embedded sensors or open data repositories is no longer the exclusive domain of professors. First-year students have access to almost unlimited amounts of data, and the possibilities for vizualising this data, actually the necessity of visualizing huge datasets are unprecedented.
To meet this inherent demand for data literacy, Copenhagen University Library has established three Data Labs at the faculty libraries for Humanities, Social Sciences and Natural & Health Sciences. The Data Labs are open platforms for supporting data literacy within studies and research through tutorials, workshops, and events on digital methods in the diverse subjects.
The Data Labs connects academia with digital methods and skills with events and workshops and by connecting the different scholarly subjects with relevant software and hardware. We are trying to capture the whole data workflow from harvesting (e.g. NVivo, TCAT and Netvizz), cleaning (SPSS and OpenRefine), Analyzing (NVivo, Stata, SAS, SPSS and Excel) and Visualizing (Gephi). The Labs also provide relevant hardware like 3D scanners and powerful workstations.
The concept is both to provide access to establish a user driven community in the Data Labs but also to support digital methods through own library instructions. Data sciences is a faily new concept in academic libraries, and the skill set needed is not nescesarily present in the current staff. A key to success in establishing the datalabs has therefore been development of new competencies and skills in programming, data abstraction and visualization. No single information specialist is expected to be able to perform scientifically valid statistical analyses or visualizations of data. But a basic level of skills, adequate for harvesting simple data, cleaning, processing and graphing them is required.
On this matter also read: Librarians as Data Scientist, really?
Connecting with the scholarly environment has had mixed results. Some subjects have eagerly grasped the opportunity to use the physical facilities for their own purposes. Other subjects has viewed the initiative with some skepticism. Especially the natural sciences has questioned the qualifications of the library in regards to data sciences. The initiative have however been uniformly well received – the need for improving the data literacy of students is universally recognized.
The Data Lab as Space
Different approaches has been taken in the physical setup. The Digital Social Science Lab has worked specifically with the decoration of the lab and has created a mobile and aesthetic learning environment which functions as an alternative to the traditional lecture hall or class room and also provides ‘otherspaces’ like a tent with a turn table. The other Data Labs has taken a more traditional approach with basic furnishing. The impression so far is, that students respond better to unconventional interior design.
On this matter also read: To work with data is to travel: The decor story of Digital Social Science Lab
Case: The data lab as network hub: creating a digital social scientific community
Digital Social Science Lab (DSSL) at Faculty Library of Social Sciences is not only a physical space but also a conceptual platform, which acts as a network hub – connecting students and researchers interested in digital methods across subjects and institutions. The Library takes a facilitating role in that process by creating a social environment around DSSL, where digital skills can be distributed between peers. “Digital Methods Session” is a series of student-2-student-based events, where students can share their experiences with digital methods and tools and inspire and enlighten each other. Here you can e.g. meet sociology student Rasmus, who scraped 2,4 millions posts from online forums about the shady cryptomarket to show how the political discourse has declined over time in this domain – using algorithmic topic modeling to analyze the giant corpus of text. The interdisciplinarity of these sessions are a really important aspect in order to create a unique learning context with a broad range of perspectives, and to give the students a possibility to network with likeminded people with DSSL as the facilitating platform.
See you in Helsinki!