A free, open source, powerful tool for working with messy data
OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data.
Please note that since October 2nd, 2012, Google is not actively supporting this project, which has now been rebranded to OpenRefine. Project development, documentation and promotion is now fully supported by volunteers.
This means that you’ll no longer have to deal with nerve-wracking copy-and-paste headaches since all formatting preferences from Docs will automatically be applied to the copy in WordPress.
But more importantly: You’ll also be able to edit pieces with partners and colleagues simultaneously and follow the changes they make in real-time.
The nifty integration will be available for any WordPress.com blog as well as any WordPress.org website equipped with the Jetpack plugin. All you have to do to enable it is authorize the add-on with access to your blog by signing up to your WordPress account.
how data is produced, collected and analyzed. make accessible all kind of data and info
ask good q/s and find good answers, share finding in meaningful ways. this is where digital literacy overshadows information literacy and this the fact that SCSU library does not understand; besides teaching students how to find and evaluate data, I also teach them how to communicate effectively using electronic tools.
connecting people tools and resources and making it easier for everybody. building collaborative, open and interdisciplinary
robust data computational literates. developing workshops, project and events to practice new skills. to position the library as the interdisciplinary nexus
what are data: definition. items of information, facts, traces of content and form. higher level, conception discussion about data in terms of social effects: matadata capturing information about the world, social political and economic changes. move away the mystic conceptions about data. nothing objective about data.
the emergence of IoT – digital meets physical. cyber physical systems. smart objects driven by industry. . proliferation of sensor and device – smart devices.
what does privacy looks like ? what is netneutrality when IoT? library must restructure : collaborate across institutions about collections of data in opien and participatory ways. put IoT in the hands of make and break things (she is maker space aficionado)
make and break things hackathons – use cheap devices such as Arduino and Pi.
data literacy programs with higher level conception exploration; libraries empower the campus in data collection. data science norms, store and share data to existing repositories and even catalogs. commercial services to store and connect data, but very restrictive and this is why libraries must be involved.
linked data and dark data
linked data – draw connections around online data most of the data are locked. linked data uses metadata to link related information in ways computers can understand.
libraries take advantage of link data. link data opportunity for semantics, natural language processing etc. if hidden data is relative to our communities, it is a library responsibility to provide it. community data practitioners
dark data
massive data, which cannot be analyzed by relational processing. data not yield significant findings. might be valuable for researchers: one persons trash is another persons’ treasure. preserving data and providing access to info. collaborate with researchers across disciplines and assist decide what is worth keeping and what discarding and how to study.
rich learning experience working with lined and dark data enable fresh perspective and learning how to work with data architecture. data literacy programming.
in context of data is different from open source and open projects. the social side of data science . advising researchers on navigation data, ethical compilations.
open science movement .https://cos.io/ pushing beyond licences and reframe, position ourselves as collaborators
analysis and publishing ; use tools that can be shared and include data, code and executable files.
reproducibility and contestability https://www.lib.ncsu.edu/events/series/summer-of-open-science
In the age of Big Data, there is an abundance of free or cheap data sources available to libraries about their users’ behavior across the many components that make up their web presence. Data from vendors, data from Google Analytics or other third-party tracking software, and data from user testing are all things libraries have access to at little or no cost. However, just like many students can become overloaded when they do not know how to navigate the many information sources available to them, many libraries can become overloaded by the continuous stream of data pouring in from these sources. This session will aim to help librarians understand 1) what sorts of data their library already has (or easily could have) access to about how their users use their various web tools, 2) what that data can and cannot tell them, and 3) how to use the datasets they are collecting in a holistic manner to help them make design decisions. The presentation will feature examples from the presenters’ own experience of incorporating user data in decisions related to design the Bethel University Libraries’ web presence.
silos, IT barrier, focusing on student success, retention, server space is cheap, if
promotion and tenure for faculty can include incentive to work with the librarian
lack of fear, changing the mindset.
deep collaboration both within and cross-consortia
don’t rely on vendor solutions. changing mindset
development = oppty (versus development as “work”)
private higher education is PALNI
3d virtual picture of disastrous areas. unlock the digital information to be digitally accessible to all people who might be interested.
they opened the maps of Katmandu for the local community and they were coming up with the strategies to recover. democracy in action
i can’t stop thinking that the keynote speaker efforts are mere follow up of what Naomi Klein explains in her Shock Doctrine: http://www.naomiklein.org/shock-doctrine: a government country seeks reasons to destroy another country or area and then NGOs from the same country go to remedy the disasters
A question from a librarian from the U about the use of drones. My note: why did the SCSU library have to give up its drone?
Douglas County Library model. too resource intensive to continue
Marmot Library Network
ILS integrated library system – shared with other counties, same sever for the entire consortium. they have a programmer, viewfind, open source, discovery player, he customized viewfind community to viewfind plus. instead of using the ILS public access catalogue, they are using the Vufind interface
Caiifa Enki. public library – single access collection. they purchase ebooks from the publisher and they are using also the viewfind interface. but not integrated with the library catalogs. Kansas public library went from OverDrive to Viewfind. CA State library is funding for the time being this effort.
types of content – publisher will not understand issue, which clear for librarians
PDF and epub formats
purchase content –
title by title selection – academia is tired of selections. although it is intended to buy also collections
library – owned ( and shared collections)
host content from libraries – papers in academic lib, genealogy in pub lib.
options in license models .
e resource content. not only ebooks, after it is taken care of, add other types of digital objects.
instead of replicate, replacement of the commercial aggregators,
Amigos Shelf interface is the product of the presenter
instead of having a young reader collection as SCSU has on the third floor, an academic library is outsourcing through AMigos shelf ebooks for young readers
Harper Collins is too cumbersome and the reason to avoid working with them.
security issues. some of the material sent over ftp and immediately moved to sftp
decisions – use of internal resources only, if now – amazon
programmer used for the pilot. contracted programmers. lack of the ability to see the large picture. eventually hired a full time person, instead of outsourcing. RDA compliant MARC.
ONIX, spreadsheet MARC.
Decision about who to start with : public or academic.
attempt to keep pricing down –
own agreement with the customers, separate from the agreement with the Publisher
current development: web-based online reading, shared-consortial collections and SIP2 authentication
An article in The Conversation recently argued universities should ban PowerPoint because it makes students stupid and professors boring.
Originally for Macintosh, the company that designed it was bought by Microsoft. After its launch the software was increasingly targeted at business professionals, especially consultants and busy salespeople.
As it turns out, PowerPoint has not empowered academia. The basic problem is that a lecturer isn’t intended to be selling bullet point knowledge to students, rather they should be making the students encounter problems. Such a learning process is slow and arduous, and cannot be summed up neatly. PowerPoint produces stupidity, which is why some, such as American statistician Edward Tufte have said it is “evil”.
Of course, new presentation technologies like Prezi, SlideRocket or Impress add a lot of new features and 3D animation, yet I’d argue they only make things worse. A moot point doesn’t become relevant by moving in mysterious ways. The truth is that PowerPoints actually are hard to follow and if you miss one point you are often lost.
While successfully banning Facebook and other use of social media in our masters programme in philosophy and business at Copenhagen Business School, we have also recently banned teachers using PowerPoint. Here we are in sync with the US armed forces, where Brigadier-General Herbert McMaster banned it because it was regarded as a poor tool for decision-making.
Courses designed around slides therefore propagate the myth that students can become skilled and knowledgeable without working through dozens of books, hundreds of articles and thousands of problems.
A review of research on PowerPoint found that while students liked PowerPoint better than overhead transparencies, PowerPoint did not increase learning or grades
Research comparing teaching based on slides against other methods such as problem-based learning – where students develop knowledge and skills by confronting realistic, challenging problems – predominantly supports alternative methods.
PowerPoint slides are toxic to education for three main reasons:
students come to think of a course as a set of slides. Good teachers who present realistic complexity and ambiguity are criticised for being unclear. Teachers who eschew bullet points for graphical slides are criticised for not providing proper notes.
Slides discourage reasonable expectations
Measuring the wrong things
If slide shows are so bad, why are they so popular?
Exams, term papers and group projects ostensibly measure knowledge or ability. Learning is the change in knowledge and skills and therefore must be measured over time.
When we do attempt to measure learning, the results are not pretty. US researchers found that a third of American undergraduates demonstrated no significant improvement in learning over their four-year degree programs.
They tested students in the beginning, middle and end of their degrees using the Collegiate Learning Assessment, an instrument that tests skills any degree should improve – analytic reasoning, critical thinking, problem solving and writing.