Story board for the CSCW2012: Video Submission

Anna De Liddo Anna , Ágnes Sándor, Simon Buckingham Shum KMi - Knowledge Media Institute- The Open University, Milton Keynes, UK

Xerox Research Centre Europe

Cohere+XIP: Human Annotation Harnessing Machine Annotation

Power

Storyboard description This storyboard aims at describing the main ‘moves’ that will be made in the video submission. Each page of this storyboard is composed of an image capturing the visual aspect of the video and a text describing the rationale of the video step by step. The video submission will consist of a continuous sequence of video clips and images with background music and a narrating voice describing the video story line.

First we describe the objective of the video: demonstrate the practical application of research on human and machine annotation of online documents to support reflective reading and collective sensemaking of online documents. We present an innovative research prototype which integrates a textual analysis software (XIP) with an open source Web annotation and knowledge-mapping tool (Cohere). …(short description of the tools)

Then we show the practical application of the new prototype by describing a use case: A user browses a web resource on Open Education, this has been analyzed by XIP which highlighted and classified salient content….see in the sidebar the XIP created annotations. By clicking on each annotation the text of the document scrolls down and higlights just that specific snippet of text extracted by XIP….

Extract

Connect & Create

The user reads the higlighted text and identifies one clip that is relevant for “Promoting Openness in Archeology and Heritage” so he clicks on “connect” and “create” and connects XIP annotation to a new annotation and labels it as “Promoting Openness in Archeology and Heritage”…..(video shows how to create and connect through the browser sidebar)

The users keeps reading and finds another clip extracted by XIP that is relevant for “Promoting Openness in Archeology and Heritage”…so he connects XIP machine annotation with his newly created annotation…he keeps reading XIP extracted sentences and identifies a third relevant sentence…..

Machine Annotation

Human Annotation

The user has used machine annotation to quickly identify key sentences for his investigation, and then he has distilled and clustered them under a refined label (human annotation) He can then explore his annotations by visualizing the network of relevant machine and human annotations which have been connected to them…

Now the video move to a more Demo style it presents some specific features in action to give a proof of context of the prototype tool potential.

What happen when there is more then one annotator? Annotations in the side bar of the browser will show more faces (video shows an example)….

Annotator’s Picture

What happen when there is more then one annotator? The annotations’ network shows authors of the annotation…(see picture on the right hand side of each node)

What happen when there is more then one annotator? The social network visualization will give a quick sense of the number and type (human/machine) of annotators of a specific document (the document being the node at the center of the star graph…)

Machine Annotation

Human Annotation

What happen when there is more then one document? XIP annotations can be visualized in COHERE as nodes clustered around a central document node…Video shows the growing complexity of the network graph of machine annotations as soon as the number of annotated documents increases…

One Document

20 Documents 100 Documents

What happen when there is more then one document? ….This exemplifies the important role of our mixed initiative approach which uses human intelligence to spot connections between different documents, and to distill, summarize and cluster relevant annotations from noise…. BUT the user needs support to EXPLORE FILTER AND MAKE SENSE of the growing number of annotations

20 Documents

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Human Annotation: Connecting

Merging Re-tagging

Summarising

Support to SENSEMAKING: The user can explore the annotations by tag (tag cloud)…or filter by annotation type and by Annotation Author…. Video will show how to filter and explore…

Tag Cloud

Filter by Annotation Type

Filter by Author

Support to SENSEMAKING: The user can also filter the annotation network (human and machine generated) by SEMANTIC CONNECTION (i.e. To filter annotations which highlights QUESTIONS users can filter by “describes an open question in” , “is raised in” , “suggests an open question in” etc ..)…video will show how to perform semantic structure searches of network of annotations. .

THE VISION: The video concludes by suggesting a vision of future CSCW systems, which combines human annotation to harness machine analysis and reasoning power. Those systems will use mixed-initiative approaches, will allow GLOBAL DISTRIBUTED human and machine annotation across different annotation tools which share a common annotation language (Exploring different annotation ontologies: i.e. AO or OA),will ENABLE BLENDED online and off line annotation (Form PDF annotation to Web document annotation)…. Video will also show initial results of parallel research project to combine XIP Cohere and Utopia (a tool for PDF social annotation)…

MACHINE-HUMAN ANNOTATION ECOSYSTEM

MACHINE ANNOTATION: XIP

BLENDED ONLINE OFFLINE ANNOTATION: UTOPIA TOOL

COHERE: HUMAN ANNOTATION

INTEGRATION AND INTEROPERABILITY: THE (AO) ANNOTATION ONTOLOGY

COHERE: SOCIAL ANNOTATION NETWORK VISUALIZATION AND ANALYSIS

Thanks for your time

Anna De Liddo Anna, Ágnes Sándor, Simon Buckingham Shum

http://kmi.open.ac.uk/people/anna/index.html