Jonah Bossewich and Mark Philipsonfrom Columbia University talk about Mediathread, an open source project that makes it easy to annotate various digital sources. It’s used in many courses at Columbi, as well as around the world.

It comes from Columbia’s Center for New Media Teaching and Learning. It began with Vital, a video library tool. It let students clip and save portions of videos, and comment on them. Mediathread connects annotations to sources by bookmarking, via a bookmarklet that interoperates with a variety of collections. The bookmarklet scrapes the metadata because “We couldn’t wait for the standards to be developed.” Once an item is in Mediathread, it embeds the metadata as well.

It has always been conceived of a “small-group sharing and collaboration space.” It’s designed for classes. You can only see the annotations by people in your class. It does item-level annotation, as well as regions.

Mediathread connects assignments and responses, as well as other workflows. [He’s talking quickly :)]

Mediathread’s bookmarklet approach requires it to have to accommodate the particularities of sites. They are aiming at making the annotations interoperable in standard forms.

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Phil Desenne begins with a brief history of annotation tools at Harvard. There are a lot, for annotating from everything to texts to scrolls to music scores to video. Most of them are collaborative tools. The collaborative tool has gone from Adobe AIR to Harvard iSites, to open source HTML 5. “It’s been a wonderful experience.” It’s been picked up by groups in Mexico, South America and Europe.

Phil works on edX. “We’re beginning to introduce annotation into edX.” It’s being used to encourage close reading. “It’s the beginning of a new way of thinking about teaching and assessing students.” Students tag the text, which “is the beginning of a semantic tagging system…Eventually we want to create a semantic ontology.”

What are the implications for the “MOOC Generation”? MOOC students are out finding information anywhere they can. They stick within a single learning management system (LMS). LMS’s usually have commentary tools “but none of them talk with one another . Even within the same LMS you don’t have cross-referencing of the content.” We should have an interoperable layer that rides on top of the LMS’s.

Within edX, there are discussions within classes, courses, tutorials, etc. These should be aggregated so that the conversations can reach across the entire space, and, of course, outside of it. edX is now working on annotation systems that will do this. E.g., imagine being able to discuss a particular image or fragments of videos, and being able to insert images into streams of commentary. Plus analytics of these interations. Heatmaps of activity. And a student should be able to aggregate all her notes, journal-like, so they can be exported, saved, and commented on, “We’re talking about a persistent annotation layer with API access.” “We want to go there.”

For this we need stable repositories. They’ll use URNs.

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Paolo Ciccarese begins by reminding us just how vast the scientific literature is. We can’t possibly read everything we should. But “science is social” so we rely on each other, and build on each other’s work. “Everything we do now is connected.”

Today’s media do provide links, but not enough. Things are so deeply linked. “How do we keep track of it?” How do we communicate with others so that when they read the same paper they get a little bit of our mental model, and see why we found the article interesting?

Paolo’s project — Domeo [twitter:DomeoTool] — is a web app for “producing, browsing, and sharing manual and semi-automatic (structure and unstructured) annotations, using open standards. Domeo shows you an article and lets you annotate fragments. You can attach a tag or an unstructured comment. The tag can be defined by the user or by a defined ontology. Domeo doesn’t care which ontologies you use, which means you could use it for annotating recipes as well as science articles.

Domeo also enables discussions; it has a threaded msg facility. You can also run text mining and entity recognition systems (Calais, etc.) that automatically annotates the work with those words, which helps with search, understanding, and curation. This too can be a social process. Domeo lets you keep the annotation private or share it with colleagues, groups, communities, or the Web. Also, Domeo can be extended. In one example, it produces information about experiments that can be put into a database where it can be searched and linked up with other experiments and articles. Another example: “hypothesis management” lets readers add metadata to pick out the assertions and the evidence. (It uses RDF) You can visualize the network of knowledge.

It supports open APIs for integrating with other systems., including into the Neuroscience Information Framework and Drupal. “Domeo is a platform.” It aims at supporting rich source, and will add the ability to follow authors and topics, etc., and enabling mashups.

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Neel Smith of Holy Cross is talking about the Homer Multitext project, a “long term project to represent the transmission of the Iliad in digital form.”

He shows the oldest extant ms of the Iliad, which includes 10th century notes. “The medieval scribes create a wonderful hypermedia” work.

“Scholarly annotation starts with citation.” He says we have a good standard: URNs, which can point to, for example, and ISBN number. His project uses URNs to refer to texts in a FRBR-like hierarchy [works at various levels of abstraction]. These are semantically rich and machine-actionable. You can google URN and get the object. You can put a URN into a URL for direct Web access. You can embed an image into a Web page via its URN [using a service, I believe].

An annotation is an association. In a scholarly notation, it’s associated with a citable entity. [He shows some great examples of the possibilities of cross linking and associating.]

The metadata is expressed as RDF triples. Within the Homer project, they’re inductively building up a schema of the complete graph [network of connections]. For end users, this means you can see everything associated with a particular URN. Building a facsimile browser, for example, becomes straightforward, mainly requiring the application of XSL and CSS to style it.

Another example: Mise en page: automated layout analysis. This in-progress project analyzes the layout of annotation info on the Homeric pages.

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Rob Sanderson [twitter:@azaroth42] of Los Alamos is talking about annotating Medieval manuscripts.

He says many Medieval manuscripts are being digitized. The Mellon Foundation is funding many such projects. But these have tended to reinvent the same tech, and have not been designed for interoperability with other projects. So the Digital Medieval Initiative was founded, with a long list of prestigious partners. They thought about what they’d like: distributed, linked data, interoperable, etc. For this they need a shared description format.

The traditional approach is annotate an image of a page. But it can be very difficult to know which images to annotate; he gives as an example a page that has fold-outs. “The naive assuption is that an image equals a page.” But there may be fragments, or only portions of the page have been digitized (e.g., the illuminations), etc. There may be multiple images on a page, revealed by multi-spectral imaging. There may be multiple orientations of the page, etc.

The solution? The canvas paradigm. A canvas is an empty space corresponding to the rectangle (or whatever) of the page. You allow rich resources to be associated with it, and allow users to comment. For this, they use Open Annotation. You can specify a choice of images. You can associate text with an area of the canvas. There are lots of different ways to visualize those comments: overlays, side-by-side, etc.

You can build hybrid pages. For example, and old scan might have a new color scan of its illustrations pointing at it. Or you could have a recorded performance of a piece of music pointing at the musical notation.

In summary, the SharedCanvas model uses open standards (HTML 5, Open Annotation, TEI, etc.) and can be implement distributed across reporsitories, encouraging engagement by domain experts.

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