Of interest to many in the Hydra Community:
We are pleased to announce that registration is now open for the 10th International Conference on Open Repositories, to be held on June 8-11, 2015 in Indianapolis, Indiana, United States of America. Full registration details and a link to the registration form may be found at: http://www.or2015.net/registration
OR2015 is co-hosted by Indiana University Bloomington Libraries, University of Illinois at Urbana-Champaign Library, and Virginia Tech Libraries.
OR2015 Registration and Fees:
An early registration fee of $450 USD will be available until May 8. After May 8, the registration fee will increase to $500 USD. This registration fee covers participation in general conference sessions, workshops, and interest group sessions, as well as the conference dinner on Wednesday, June 10 and poster reception on Tuesday, June 9. For a draft outline of the conference schedule, please see: http://www.or2015.net/program/schedule-at-a-glance
Participants may register online at: http://www.or2015.net/registration. If you have any questions about registering for OR2015, please contact the Conference Registrar at email@example.com. Any other questions about the conference may be directed to the conference organizing committee by using the form at: http://www.or2015.net/contact-us
The OR2015 conference will take place at the Hyatt Regency Indianapolis hotel, conveniently located in the heart of downtown Indianapolis. Special room rates at the Hyatt starting at $159 USD per night have been negotiated for conference attendees and will be available for booking through May 16. More information on hotel reservations and travel is available at: http://www.or2015.net/conference-hotel-and-travel
Keynote and Featured Speakers:
Reflecting the significant milestone of the 10th Open Repositories conference and this year’s theme of “Looking Back, Moving Forward: Open Repositories at the Crossroads,” we are pleased to announce the conference’s two plenary speakers:
Kaitlin Thaney will be giving the opening keynote talk on the morning of Tuesday, June 9. Kaitlin is director of the Mozilla Science Lab, an open science initiative of the Mozilla Foundation focused on innovation, best practice and skills training for research. Prior to Mozilla, she served as the Manager of External Partnerships at Digital Science, a technology company that works to make research more efficient through better use of technology. Kaitlin also advises the UK government on infrastructure for data intensive science and business, serves as a Director for DataKind UK, and is the founding co-chair for the Strata Conference series in London on big data. Prior to Mozilla and Digitial Science, Kaitlin managed the science program at Creative Commons, worked with MIT and Microsoft, and wrote for the Boston Globe. You can learn more about the Science Lab at http://mozillascience.org and follow Kaitlin online at @kaythaney.
Anurag Acharya will be the featured speaker at the plenary session on the morning of Wednesday, June 10, presenting on “Indexing repositories: pitfalls and best practices.” Anurag is a Distinguished Engineer at Google and creator of Google Scholar, and he previously led the indexing group at Google. He has a Bachelors in Computer Science from the Indian Institute of Technology, Kharagpur and a PhD in Computer Science from Carnegie Mellon. Prior to joining Google, he was a post-doctoral researcher at the University of Maryland, College Park and an assistant professor at the University of California, Santa Barbara.
We look forward to seeing you at OR2015!
Jon Dunn, Julie Speer, and Sarah Shreeves
OR2015 Conference Organizing Committee
Holly Mercer, William Nixon, and Imma Subirats
OR2015 Program Co-Chairs
Is the COBOL programming language capable of processing MARC records?
A computer programmer in 2015 could be excused for thinking to herself, what kind of question is that!?! Surely it’s obvious that any programming language capable of receiving input can parse a simple, antique record format?
In 1968, it apparently wasn’t so obvious. I turned up an article by Henriette Avram and a colleague, MARC II and COBOL, that was evidently written in response to a review article by a Hillis Griffin where he stated
Users will require programmers skilled in languages other than FORTRAN or COBOL to take advantage of MARC records.
Avram responded to Griffin’s concern in the most direct way possible: by describing COBOL programs developed by the Library of Congress to process MARC records and generate printed catalogs. Her article even include source code, in case there were any remaining doubts!
I haven’t yet turned up any evidence that Henriette Avram and Grace Hopper ever met, but it was nice to find a close, albeit indirect connection between the two of them via COBOL.
Is the debate between Avram and Griffen in 1968 regarding COBOL and MARC anything more than a curiosity? I think it is — many of the discussions she participated in are reminiscent of debates that are taking place now. To fair to Griffin, I don’t know enough about the computing environment of the late sixties to be able to definitely say that his statement was patently ill-informed at the time — but given that by 1962 IBM had announced that they were standardizing on COBOL, it seems hardly surprising that Avram and her group would be writing MARC processing code in COBOL on an IBM/360 by 1968. To me, the concerns that Griffin raised seem on par with objections to Library Linked Data that assume that each library catalog request would necessarily mean firing off a dozen requests to RDF providers — objections that have rejoinders that are obvious to programmers, but perhaps not so obvious to others.
Plus ça change, plus c’est la même chose?
Last updated March 15, 2015. Created by Peter Murray on March 15, 2015.
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Indiana University and Northwestern University are pleased to announce Avalon Media System 3.3. Release 3.3 adds the following capabilities:
- MARC Metadata Import
- Ingestion of pre-transcoded derivatives with multiple quality levels
- Script for recovering disk space taken up by temporary Matterhorn files
- UI Improvements and Bug fixes
Users of Avalon 3.2 can take advantage of these new features by Upgrading Avalon 3.2 to Avalon 3.3.
Last updated March 15, 2015. Created by Peter Murray on March 15, 2015.
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MediaSCORE (Media Selection: Condition, Obsolescence, and Risk Evaluation) enables a detailed analysis of degradation and obsolescence risk factors for most analog and physical digital audio and video formats.
MediaRIVERS (Media Research and Instructional Value Evaluation and Ranking System) guides a structured assessment of research and instructional value for media holdings.
Some additional key features of the software include:
- Browser-based web-application that works on any Windows and Mac operating systems using all popular browsers.
- Enables teams to enter and edit data simultaneously.
- Permissions based access and views across MediaSCORE and MediaRIVERS.
- Controlled vocabularies and field validation to help ensure consistent data entry.
- Provides auditing path to help with quality assurance and transparency.
The two applications are bundled together but may be used separately. They can be found along with a detailed user guide on GitHub at https://github.com/IUMDPI/MediaSCORE . Also available is a conceptual document that explores assessment of research and instructional value.
The software requires installation and configuration on a server, requiring the appropriate expertise. AVPreserve is also offering MediaSCORE/RIVERS as a hosted application on a monthly subscription basis.Package Type: Data Preservation and ManagementLicense: Apache 2.0 Package Links In DevelopmentOperating System: Browser/Cross-PlatformProgramming Language: PHPOpen Hub Link: https://www.openhub.net/p/MediaSCOREOpen Hub Stats Widget:
Last month I blogged for Safari about successfully changing fields, being fearless, and improving yourself through reading and learning. My blog post received a wonderful response, and I am proud to share that this month I begin my official new position as Safari’s Customer Success Manager. I am staying with my team and am super excited to make our product more useful to both our new and existing customers. I’ll be blogging intermittently about what I’m doing, learning, and making with Safari.
While I believe what I wrote in that post, I’ve felt a bit hypocritical because it’s come to my attention throughout this long, dark winter that
I waste a lot of time.
So much time! From time spent writing emotive letters that I never send to time reading the Wikitravel details of places I want to visit. I sleep late on weekends, occasionally drink too many glasses of wine on weeknights, often eat way more than an allotted portion while distractedly checking my phone during dinner, and spend hours looking at pairs of black pants on the Internet that I will never buy. (I love black pants, particularly loose, comfortable ones. Let this link be a hint to anyone who ever wants to buy me a present.) I believe strongly that there is a healthy balance between time-wasting and productivity, and I am afraid that this winter I crossed my own line and need to work on getting myself back to my center.
I’ve always been an over-achieving time waster; I’m the kind of person who knows all the details of Madonna’s Wikipedia page and still somehow finds the time to do all the things. I manage to consistently find the time for birthday parties, lazy afternoons, potlucks, puppet shows, and performing while always submitting applications, papers, and my taxes on time. I have always volunteered with my community, whether gardening or teaching or manning a booth, and I try to be there both in time and spirit for my friends. I am a master of very little and a generalist who can do a lot of things adequately, including playing music, speaking German and Spanish, and holding intelligent conversation on about a million topics. My lack of focus is what drew me to the interdisciplinarity of American Studies and later Library Science, but
because I am okay at a lot of things, I have often felt like I am not good at anything.
My lack of mastery augments an incredible social knowledge that makes me great at cocktail parties, but not so great at specialized skills, particularly those that I have tried and failed to learn repeatedly like drawing or programming computers.
Lounging around and wasting time makes me stressed, and yet I find myself in Wikipedia holes, on Buzzfeed lists, mindlessly thumbing through Instagram, and Googling ex-boyfriends more than I would like to admit. I have an addictive information-seeking brain, and the Internet has been both an asset and a curse for me as I find myself up late, watching the bar below my apartment close, absorbing both everything and nothing at once. (Pro-tip for other addictive minds: Never begin a television program with a seemingly unlimited number of episodes at 9PM on a week night. You will regret it.)
The Internet has made it easier to live vicariously through others, which is another double-edged sword that often makes life feel more complicated than it actually is. All my friends, professional contacts, and the celebrities who interest me seem to be living fulfilled lives, so I submit to the worst kind of voyeurism, one that’s tinged with envy and the feeling that this life could be mine if I were only more “_______.” This kind of time wasting makes me want to delete all my Internet history, take a shower, and maybe smash my phone against a wall. Even admitting that I do it in a public manner makes me feel slightly uncomfortable, but I think it’s important to recognize this is a human byproduct of the Internet age.
I’m not taking the capitalist tack that says all time has to be productive, self-improvement time, and one only has to read a Romantic novel to realize that people actually probably were not more productive in “olden days.” (I wonder how much time a Jane Austen heroine spent staring at the wall?) Instead of judging or feeling shame, (both feelings that society unfortunately encourages,) I want to practice weening myself off behaviors that don’t make me feel like my best self and hope that others feel inspired to make similar changes for their health and the health of their communities.
In order to kick off this process, I did what I do best, and what I do to make most of my decisions: I made a chart.
I titled the page:
“Be more productive. Overcome winter blues. Get moving.”
The chart’s four cardinal directions pointed to:
- Have to do
- Want to do
- Do less of
- Do more of
I brainstormed for about 25 minutes and then wrote a list of the immediate tasks I needed to do within the next week in order to make these “productivity hacks” reality (excuse the jargon.)
I wasn’t sure what was going to come out of the exercise, but when I looked at the page, I was surprised to see that most of my “negative” behaviors revolved around a few, distinct categories. In making the chart, I saw that “worrying about the opinion of others” came up 4 times, “relying too much on technology” came up 5 times, and “drinking less frequently” came up 2 times. (My 26 year old hangovers are much worse than my 21 year old hangovers!)
In contrast, doing creative work like playing music, dancing, and writing came up 7 times and giving back to my community came up 4 times on my “positive” behavior list. Being kinder to my environment, both in terms of resources and social awareness also came up frequently.
I am going to use the weeks leading up to my 27th birthday to take some steps towards doing my best work and realizing my unique talents through this exercise and others encouraged by productivity experts. I am also going to use this month to research improving productivity and share out my findings on this blog.
It’s time to focus on my creative and nurturing self and feel more alive in my body this spring. Winter has been hard on all of us Bostonians, but in adapting my behaviors to fit my goals, I am taking the first steps toward a daily practice to be my best self.
For my final session of the day I attended an interview of Ryan Leslie by Matt Mullenweg titled “A new generation: Creativity and Open Source”.
Ryan Leslie graduated from Harvard at 19 and on the forefront of technology and music. Ryan gave us all his cell phone number so we could text him during the session because he’s very in to being open and giving back. “As creators we try to find our way in the dark – we don’t have any concrete data on who’s buying our music”. When his second album was released he wondered by the label couldn’t just email everyone who bought his first album to tell them about his album. The problem is that the labels don’t have that info. So Ryan shares his info with his fans so that he can keep in touch with them. He used the Twilio API to create a tool to reply to text messages he gets asking the sender for their email address.
Ryan decided that he was going to sell records on his own instead of through a label and has made significantly more money that way. When working with the label it’s like the worst business loan that ever. Instead you can use tools like Tilt, Kickstarter and other crowdfunding sites to get that loan to start up the business and publish your own records. When you’re able to connect directly with your users you can identify who your real supports are.
Instead of spending money on a tool like salesforce Ryan decided to spend 40 days on CodeAcademy and learned Ruby on Rails and wrote his own tool using Twilio to now gather info on his audience. Before he would just get sales reports from iTunes – once he started selling direct he got a better feel for who it was who was listening to him music. “Everyone you know, whether they buy your album or not, can contribute to your project” – contacts as currency. “It’s beautiful when the communication can be two way”.
Ryan shared a story where he and several other musicians were all together and started coming up with a song together and collaborating on the sound. Matt said this was the story that was the most like open source – where several artists come together to collaborate and build something special together.
Ryan made a very open source comment – some of the most successful solutions are when they solve for a problem they face personally. He wants software that was developed by people like him. He mentioned TopSpin which never really worked for him because he didn’t know who wrote it – or where they came from (life experiences). It comes down to shared experiences – even moving up in the music industry is about the people they know and their relationship equity.
Matt recommended that we all read 1,000 True Fans by Kevin Kelly.
“When creators are inspired they share it” – Ryan Leslie
The post SxSW: A New Generation: Creativity and Open Source appeared first on What I Learned Today....
- SxSW: Building the Open Source Society
- ATO2014: Open Source Schools: More Soup, Less Nuts
- The open source behind Twitter
This afternoon Josh Clarke spoke to us about ‘Magical UX and the Internet of Things’.
A lot of what we’re seeing these days with tech interaction has come with mobile technology. Touch started it all and now we have things like voice and facial recognition. So now makers of digital products need to think about these new ways we should interact with the digital world. There is now a way for us to cast “spells” – wave our arms and something happens. We can even get our own magic wand at thewandcompany.com. Josh even showed us how his wand could be used to light candles. It’s not all novelty like that though, there are some real business and practical uses for this.
Josh showed us a video : bit.ly/grab-magic where the developer created a hack where he grabs things from his TV and puts them on his mobile phone. While it looks awesome it’s so simple with our household devices.
Magic and Technology
“Any sufficiently advanced technology is indistinguishable from magic” – Arthur C. Clarke.
For example – no one is every going to want to wear a computer on their body – but now we have smart watches. Sometimes is what’s we see now that prevents us from developing things that seem like magic.
“Fantasy fulfills a need for a simpler more controllable world” – Alan Kay
We need to make technology seem like magic. Touch for example makes it seem like we’re actually touching the data. We need to use fantasy to think about how want to interact – Alan Kay also said “One goal: the computer disappears in to the environment.” An example of this is the magic wand. But we don’t have to go to Olivander’s to find that wand – we all have one already in our smart phone. Our phone is the magic wand for everyone. The phone is the first IoT (Internet of Things) device for us all. Now we want to put more of the smarts our phone as in to other things. Our phones (and other IoT devices) have “Sensors + Smarts + Connectivity”.
Think of the first time you used Shazam – that was another kind of magic – it was paying attention to the world around you to listen to music. Now we’re seeing this kind of thing with our cameras and translation apps (we used Google Translate to translate signs while in France last week). This also means that we can carry fewer things with us – we don’t carry maps, or cameras or alarm clocks – we use our phones for this. Mobile phones actually bring computing power to immobile objects because we have these phones with us all the time – locks, light bulbs, etc. We can embed smartphone brains in everything and anything. The nappy notifier is a device and app to help you manage your baby’s diapers.
On average we spend over 3 hours a day looking at our phone screen. The more connected we are the more disconnected we are – this means that for those who have been designing mobile interfaces these last few years have been doing too good a job. We want to move these things off of the screen in our hands and out in to the world. Neiman Marcus has this magic mirror that lets you see your entire outfit and compare it to others you have tried on.
Josh recommends that we read ‘Enchanted Objects’ by David Rose. We have many magically smart devices in our homes these days – the Roomba for example is like the broom in Fantasia or Google Now can be like the sorting hat. There is even a device that emulates the ruby slippers in the Wizard of Oz! Bt.tn is a tool that’s like the easy button for life. There’s also IFTTT that is all about magically making things happen! There’s also Zapier which is similar to IFTTT.
So the point of Magic and Technology is to make the computer invisible – we want it to be easier not harder. The magic happens at the point of inspiration – we embed the smarts in our devices around the house. We have centuries of UX ideas to pull from (Wizard of Oz and Fantasia for example).
Up til now we have been tying our digital only to screens. Now we can interact with the world – the world is the interface. For example how do we make the physical shopping experience as easy as the online shopping experience. There is all this info you can’t get from both environments when in the other.
The world is a data source – we need tools that gather data from around us. For example the Snapshot device from Progressive Insurance. Automatic though provides info to the driver (us) to help the car talk to us. Propellerhealth is a device you an add to an inhaler that will help those with asthma learn more about their disease – because they’re also used in communities the devices can gather group data and explain the environment. These devices are passive – they’re the modern crystal balls. They gather data from the physical world and push them back to the digital world.
The world is reactive – the things we do in the world cause a reaction. Our actions are a source of data! The Ares Sand Table is an example of this – this way physical and digital are totally in sync. The Minkoff Mirror is a device to help bring the digital in to the dressing room in the physical store – so now the world is interacting with the data. These are intentional interfaces.
The world is a big canvas – if you thought designing for mobile and desktop was tough – imagine designing for an entire room. For example the Immersion Room or this video: bit.ly/smart-dumb or this bit.ly/room-e. These are therables (instead of wearables) – these are smart environments – which means we can wear fewer bracelets.
The world has depth and mass – we’re used to 2 dimensional interfaces – the world is not flat! Our magic has to account for that. MIT Thaw is about this. Thaw shows us how to have these expensive devices (our phone and laptop) talk to each other better. What would be a better way to move music from your phone to your computer – why not have the phone and computer work together better : bit.ly/happy-together-app.
So we want to gather data for insight, channel intention in to action, use the whole big canvas of the world – make the world smarter and keep in mind that interactions have mass.
This is not a challenge of technology, it’s a challenge of imagination!
Let’s start with Google Glass – it always looked like an engineering project. Instead they should have asked ‘what if this thing was magic?’
Let’s look at a coffee cup and ask ‘what if this thing were magic’ – what is this cup witness to and what actions is it next to? What can it hear, what can it see and how can it serve us more. We’re not turning it into something else, we’re designing for the thing’s essential thinness. The goal is not to make things talk – the goal is to improve the conversation. We want things that do their jobs better. We should be bending technology to our lives – make us more human – not less. Colorup takes the color from around it for the light. We need to bank on illusion and embrace misdirection. Context aware experiences should reflect the lies of what we tell ourselves about how these things work. One of the ways we do this is to expose as little technology as possible (make the computer invisible). If everything can be an interface we don’t want everything shouting at all. Oliver for example weaves the number of unread messages we have in our email in to our lives – instead of shouting at us. Remember that magic can be a little ridiculous. It’s okay to make things a little bit ridiculous right now.
What happens when magic goes wrong? Technology lets us down all the time. As we have more and more technology in our lives it becomes more real. “How smart does your bed have to be before you are afraid to go to bed at night” – Rich Gold. Human’s know better. We need to build systems that know they’re not smart enough. Sometimes we build these systems with people first like Lyft and Uber – then when technology catches up (self driving cars) we can bring in the magic. It’s not Harry Potter’s wand that’s magic – it’s Harry. Humans are needed.
It’s not “can” we do this – it’s ‘How will we?”!
- ATO2014: Open Source & the Internet of Things
- Planning for the handheld mobile future
- NFAIS: Creating new value for business professionals
John Miedema: A first rough cut at Lila’s calculation of association between slips. Keep it simple to scale for large volumes of text.
How will Lila calculate the strength of association between slips? Here is a first rough cut. The key thing I want to illustrate is the use of simple steps to decide the subject of a slip and compute a quantitative measure of association with other slips. The method must be simple and quick to scale for large volumes of text. A chess program has to contend with infinite combinations. It uses a simple evaluation of game rules and a sum of chess piece points. E.g., if a move leaves white with ten points and black with nine points, then a particular move is a good one for one. This simple calculation (applied for as many iterations as a game level will allow) is sufficient to beat most chess players on the planet. Lila uses a comparable approach.
The simple rules for text analysis are the following:
- Extract nouns. Basic grammar says that you find the subject of a sentence in the nouns: people, places and things.
- Use word properties to rank their relative meaningfulness. For example, if a word has a lower frequency of usage it can be considered more interesting and important. There are several such word properties that can be applied by a simple calculation. Just word frequency will be used here. Based on the properties, rank the nouns.
- Use synonyms and variant forms to match on meaning rather than just a single surface form. Variant forms and synonyms are a simple and powerful semantic matching technique.
Here is an example. Suppose Stephen Hawking used Lila when writing A Brief History of Time. Suppose this line was a slip in his writing project:
Most people would find the picture of our universe as an infinite tower of tortoises rather ridiculous, but why do we think we know better? What do we know about the universe, and how do we know it?
In this first rough cut, Lila analyzes the slip and generates the following table:Noun Frequency of usage
(academic) Rank Synonym tortoise 123 1 turtle tower 1563 2 castle universe 4868 3 cosmos
Lila has applied the rules:
- Nouns were extracted.
- For each noun, frequency of usage was used to calculate rank. An arbitrary rule for this example limits the nouns of interest to the top three ranked nouns.
- Synonyms, e.g., tortoise = turtle, were generated by simple look-up from a list.
The nouns are used to find other related slips and compute their strength of association.
A first Google search was performed on [tortoise tower universe]. It would make sense to apply a boost factor to the keywords based on the ranking; in this case I trusted Google to use word order. Many results were nearly identical to the original slip. Nearly identical slips may be interesting to Hawking but will not add much insight.
A second search was performed on the synonyms [turtle castle cosmos]. Divergent results were found, such as a website about Turtle’s ice cream. A snippet was selected from the website for analysis by the Lila algorithm:
There’s more to see…
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28 Pins •
[Image: Cosmic Castle”
(academic) Rank Association cream 419 1 No Match pins 724 2 No Match castle 788 3 Match
This site is about an unrelated subject, ice cream. Limiting again to the top three ranked nouns, there is only one match — between Hawking’s term “tower” and its synonym “castle.” A measure of association of 1/3 or 0.33 is computed. This low value could be used to obscure or exclude the slip.
Another result matched better, a blog about turtles in cosmology. A snippet was analyzed using Lila’s algorithm:
The Cosmic Turtle Around the World
In Japanese mythology, the tortoise supports the ‘Abode of the Immortals’ and the ‘Cosmic Mountain’, where the Cosmic Mountain relates to the axis mundi – the world axis.Noun Frequency of usage
(academic) Rank Association cosmos/cosmic 955 1 Match turtle 1116 2 Match axis 2046 3 No Match
Perhaps Hawking would not be interested in such a blog. Perhaps he would. In this case there are two matches. A measure of association of 2/3 or 0.66 is computed. A more refined algorithm would weigh in the triple use of “cosmic.” This site is related subject matter.
This is a first rough cut of how Lila will calculate the strength of association between slips. Certainly a more sophisticated algorithm is required, taking in account multiple word properties. The algorithm should weigh words as more important if they repeat within a slip, especially if they repeat in author-suggested categories and tags. But sophistication must always answer to the need for a simple algorithm. Simplicity is the only way to achieve reasonable performance when analyzing large quantities of text.
This was a core conversation lead by Stephanie Geerlings and Jesse Cooke.
How do you promote your project:
- Articles/blog posts
- Twitter – not as powerful as a a blog post
- Screencasts – really gets people interested – it’s important to note that this can be time consuming but practice makes perfect
- Get users to promote/education people – especially in government (in Hawaii they have released over 400 state and government sites on WordPress – but the people there still seem to think they need to pay for a system)
- Get community members to education/promote/mentor because the bigger the project the higher the barrier to entry
- Going where the developers are – be in the right IRC channels or on the right mailing lists
- Documentation is key – if people can’t use your documentation no one will use your product – a great example of documentation are the VagrantDocs
- Have first experiences be pleasant – website and personal experiences
How do we sustain the collaboration:
- Text does not lend itself to working together well – sometimes opening up a hangout or Skype will save a project
- Open communication – if you use something like a hangout to communicate then the log of that conversation is lost – it’s not transparent.
- One of that things we haven’t done well as a community is to explain that open source is not free – we need to take in to consideration the time it takes to support the project – and promote it – this includes peer review
- Get companies using your product to help financially – if those companies can’t give hours it would be great if they helped with crowdfunding
- IEEE releasing a tool this summer to help with open source communities and collaboration
- Don’t be an echo-chamber – don’t only hang out with people in the same field – keep it multidisciplinary to get the most out of it
How do we thank people who don’t participate in writing code:
- Badges or some sort of equity system where people can show their worth
- Self promoting – explain where the project would be without you/your contribution
- If people are designing logos or something that isn’t code related get them set up on git anyway so they can play too – people want to see their name on the project and get credit for their contribution even if it’s not code
- Put an acknowledgements page together to thank those who don’t write code
- Thank people by sending them to conferences (if you have the funding) maybe give it an award name so people can put it on their resume to show what they achieved
- ATO2014: Building a premier storytelling platform on open source
- Keynote: Licensing Models and Building an Open Source Community
- ATO2014: How Raleigh Became an Open Source City
[Mark]”…Codfish Islands was infested with feral cats. In other words, cats that have returned to the wild.”
[Doug]”I always think that’s an artificial distinction. I think all cats are wild cats. They just act tame if they think they’ll get a saucer of milk out of it…”
— Douglas Adams and Mark Carwardine, Last Chance to See
In my earlier post “Digital Collections and Accessibility”, I touched upon the considerations we would need to address when building or creating digital collections (or other things that rely heavily on utilizing images such as data visualization) for public use. Here are the questions I put down in that post:
“Given the ubiquitous nature of digital collections, the goal that these collections would be used as part of scholarly activities, and the library’s mission to disseminate the information as widely as possible, there is one aspect that many of us need to address when we plan for a digitization project: how do people with disabilities access these collections without getting lost? Can they also get the same access and benefit from our collections if they only rely on their screen readers (or refreshable Braille, or any other assistive technology)? Can people move around our website easily using just a keyboard (for those with hand-coordination difficulty who cannot use a mouse)?”
So: planning. Planning is an important part when incorporating accessibility into building a collection. Typically, building a digital collection starts with designing the metadata (PDF) and then proceeds to further development activities such as database design, content creation, data entry, and coding/front end development. Whichever process that we develop, we would like to see that the website is well designed and the information presented is useful for our audience (I am assuming that most digital collections created and made available are designed for web access, with an added bonus if they also employ a responsive design.)Image Display
If you visit digital collections developed by various institutions, you’ll see that they present their collections differently. Many would display the collections be like a catalog that shows an image, the physical description, and related information such as the owner, creator, and copyright statement at the minimum.) Some also include an interpretation of the object (think the label of an object or painting displayed in a museum.)
Regardless how the object is presented (by description or interpretation), accessibility considerations are still the same. The most common considerations: the web page needs to be properly structured by using proper headings; the flow of information presented on the page needa to make sense for screen reader users or keyboard-only users; search forms need to be properly labeled; images need to have alternative text (usually referred to as “alt-text”.) This is when the planning for the page design and coding becomes important.
Consider this page:
and consider how the flow of information would be read by a screen reader and how a screen reader user might hear it:
Typical screen readers read the information displayed as if the CSS is disabled; they read web content in the order that it appears in the code.
(Bonus: if you have not seen or heard how screen reader users interact with a website, you can view the recording of accessibility test of our e-resources page (.mp4) done by my blind student. We did this as part of our accessibility test routines for the library electronic resources.)
Both images above should be sufficient to give us ideas of how a sighted user might interact with the page and how a screen reader users might hear it. Our eyes can focus on and narrow down to a certain section faster while screen reader users need to listen to the whole thing first before they can work on distinguishing the part that provides the actual information of the object being displayed. Hence, careful planning when designing the metadata and the page is needed to make sure our collection is both useful and usable for our audience regardless how they access it.Data visualization
A lot of data visualization rely on colored graphics when conveying the information. It is trickier to tackle because of the colors used and, unlike most images used in digital collections, data visualization conveys very rich information.
Consider this example with three different color representations:(Data visualization of world population of children age 0-14 years old. The information is grouped by regions (South Asia, East Asia, Africa, South America, Middle East, Europe and Russia, and North America.) Original data can be found at http://datatopics.worldbank.org/hnp/popestimates.)
By looking at the colors used on the image above, we can see that the information is grouped based on the region (South Asia, East Asia and Pacific, Africa, Europe, etc.) and the color density of each individual block reflects the population density of the area.(Data visualization of world population ages 0-14 years old as seen by a person with red green color blindness, such as protanopia.)
The second image shows how the visualization might be seen by those with the red green color blindness (protanopia), one of the most common types of color blindness. Here, East Asian and African regions are no longer distinguishable. Similarly, South American,Russian, and European regions are also no longer distinguishable.(Data visualization of world population of children age 0-14 years old as seen by a person with total color blindness (chromatopsia).)
This last image shows how those colors don’t really convey the grouping of the regions to those with total color blindness (achromatopsia, which is a rare condition but still exists.)
The point of these examples: do not use color alone to convey meaning.
As far as I know, there is no practical solution yet for making data visualization fully accessible. Several options that can help increasing the accessibility: supplement the color with text or provide summaries or text description right after the image (alt-text or image caption). If the description is too long to be listed on the same page, create a separate page and link to it. Similar to designing for digital collection, designing for visualization also needs careful planning.Conclusion
Designing for accessibility for our digital collection or data visualization should be done as part of the planning phase. This would allow us to optimize the output of our work and eliminate or reduce the need to revisit the design for corrections later on. Careful planning on how we want to display the information and to convey the meaning of the graphics/images would benefit all of our users regardless how they access our collections.Resources
- Meloncon, Lisa K. Rhetorical Accessability: At the Intersection of Technical Communication and Disability Studies. Amityville, N.Y: Baywood Pub, 2012.
- Pullin, Graham. Design Meets Disability. Cambridge, Mass: MIT Press, 2009.
- Section 508 Web-based intranet and internet information and applications (http://section508.gov/section-508-standards-guide#Web)
- WebAIM Section 508 Checklist (http://webaim.org/standards/508/checklist)
- W3C Accessibility: WCAG2 at a Glance (http://www.w3.org/2009/cheatsheet/#wcag2)
Leah Cheyrnikoff, the moderator started off with this quote from Newsweek:
A combination of that very traditional Wall Street wolf-ism among Northern California’s venture capital boys’ club and the socially stunted boy-men that the money men like to finance has created a particularly toxic atmosphere for women in Silicon Valley.
On the panel were : Danika Laszuk, Nicole Sanchez, and Nellie Bowles — all successful women in the technology field.
Danika said that she started in the tech industry pretty much by accident. She did grow up in a house where you father was a tinkerer and so she was very interested in computers – but she studied play writing in college. Nellie’s path was also by accident – she wanted to be a science writer and started writing about tech parties and somehow that got her in to the tech blogging world. Now she finds herself (recently) in court blogging about the Ellen Pao and Kleiner Perkins case. Nicole didn’t imagine herself in the tech world even though she went to fancy schools and was in school with Mark Zuckerberg – it never occurred to her. She called this a tragedy – and I agree – all three women got in to tech by accident … pretty much the same way I did.
Nicole said she likes tech – it helps her get things done faster. She said you just have to see someone who looks like you do it and then you believe you can do it too.
Leah asked the panel how real are the gender issues in the tech world. Nellie says that with much of her research she has found that these issues are well founded and sexism is very real. Danika says that in addition to these overt actions, there are also a lot of things in the culture that don’t fit with the lifestyles of most women. The tech world can foster working from noon to late in the night and this doesn’t work for most people who want a family (not just women). Nicole says that while this is all true and scary it’s not all negative – no one has ever made her feel really horrible – not everyone is out to get you (this is the experience I have personally so I love that she said this).
Nicole brought up the fact that there isn’t always intentional bias – the market looks for people who look like them – so finding investors for example as a black woman is extremely difficult before she is like a ‘unicorn’. Nellie talked about ‘pattern matching’ – investors look for people who fit a certain image. They look for a 22 year old white man who went to an amazing school (Stanford or Harvard). It’s a very specific image that investors look for and that image is not us (women).
Leah mentioned that men are raised differently than women – they are raised to be more confident and more aggressive. This makes it hard for women to break in to the industry. Nicole mentioned that she wants to come across as confident but doesn’t want to come across as an ‘arrogant know it all’ – we worry about that. Unlike most women Nicole loves to pitch. Most women though seem to often apologize – and sometimes they like to talk about the team – what the team has done versus what they personally have done. Danika talked about how when a man is assertive in negotiating for a raise is seen as a good employee – if a woman does the same thing she is seen as aggressive instead of assertive. You see this in the pay gap.
Dankia talked about how diversity is great for business! Racial, gender, etc etc. This diversity breeds more innovation because everyone thinks differently. This is going to make companies stronger. She has been lucky that she works at a company that values diversity (Jawbone). This does mean that those doing the hiring have to work harder to find these people for the betterment of the company.
Another good point that was brought up is that men probably also want to spend time with their kids and coach teams – it’s just that we always pin this on women because it’s a cultural norm. It’s unfair – especially to me as a woman without children to be pigeon-holed in that way.
Nicole brought up a great point – a horrible – but true point. She was a meetup for tech people at SxSW a couple of years ago and a black woman approached her and started talking to her about the tech world and Nicole’s first thought was ‘what do you know about tech’? Men aren’t the only ones with these prejudices – women have them too. So, we need more women talking to women about tech and getting them thinking about what they can do. In addition to the employers hiring more from more diverse pools we also have to hold universities accountable for teaching more women what they can do.
Nellie says that finding a mentor is the most important thing. She had to force herself to be a mentee – she sort of latched on to people and forced them to teach her. This mentor doesn’t have to be a woman, but you might have to force the issue with men because of fears they might have about being inappropriate. Nicole mentioned the difference between a mentor and a sponsor. A mentor will help you get and keep a job, but a sponsor is in charge of pushing you to the next level. These two roles can be (but don’t have to be) the same person. Danika took a different approach – she created her own personal board of directors – instead of one mentor. She has someone on her board who is an amazing manager and someone who is a killer deal maker and someone who is a great marketer – she crafted her board around these different ‘super powers’. This group of mentors or advisers will help you with different topics and at different parts of your career. I like this model – it’s kind of what I have because I can name several mentors in several different areas of my career.
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