Annotation graphs as a framework for multidimensional linguistic data analysis

In recent work we have presented a formal framework for linguistic annotation based on labeled acyclic digraphs. These `annotation graphs' offer a simple yet powerful method for representing complex annotation structures incorporating hierarchy and overlap. Here, we motivate and illustrate our approach using discourse-level annotations of text and speech data drawn from the CALLHOME, COCONUT, MUC-7, DAMSL and TRAINS annotation schemes. With the help of domain specialists, we have constructed a hybrid multi-level annotation for a fragment of the Boston University Radio Speech Corpus which includes the following levels: segment, word, breath, ToBI, Tilt, Treebank, coreference and named entity. We show how annotation graphs can represent hybrid multi-level structures which derive from a diverse set of file formats. We also show how the approach facilitates substantive comparison of multiple annotations of a single signal based on different theoretical models. The discussion shows how annotation graphs open the door to wide-ranging integration of tools, formats and corpora.Comment: 10 pages, 10 figures, Towards Standards and Tools for Discourse Tagging, Proceedings of the Workshop. pp. 1-10. Association for Computational Linguistic

An affect-based video retrieval system with open vocabulary querying

Content-based video retrieval systems (CBVR) are creating new search and browse capabilities using metadata describing significant features of the data. An often overlooked aspect of human interpretation of multimedia data is the affective dimension. Incorporating affective information into multimedia metadata can potentially enable search using this alternative interpretation of multimedia content. Recent work has described methods to automatically assign affective labels to multimedia data using various approaches. However, the subjective and imprecise nature of affective labels makes it difficult to bridge the semantic gap between system-detected labels and user expression of information requirements in multimedia retrieval. We present a novel affect-based video retrieval system incorporating an open-vocabulary query stage based on WordNet enabling search using an unrestricted query vocabulary. The system performs automatic annotation of video data with labels of well defined affective terms. In retrieval annotated documents are ranked using the standard Okapi retrieval model based on open-vocabulary text queries. We present experimental results examining the behaviour of the system for retrieval of a collection of automatically annotated feature films of different genres. Our results indicate that affective annotation can potentially provide useful augmentation to more traditional objective content description in multimedia retrieval

Open semantic annotation of scientific publications using DOMEO

<p>Abstract</p> <p>Background</p> <p>Our group has developed a useful shared software framework for performing, versioning, sharing and viewing Web annotations of a number of kinds, using an open representation model.</p> <p>Methods</p> <p>The Domeo Annotation Tool was developed in tandem with this open model, the Annotation Ontology (AO). Development of both the Annotation Framework and the open model was driven by requirements of several different types of alpha users, including bench scientists and biomedical curators from university research labs, online scientific communities, publishing and pharmaceutical companies.</p> <p>Several use cases were incrementally implemented by the toolkit. These use cases in biomedical communications include personal note-taking, group document annotation, semantic tagging, claim-evidence-context extraction, reagent tagging, and curation of textmining results from entity extraction algorithms.</p> <p>Results</p> <p>We report on the Domeo user interface here. Domeo has been deployed in beta release as part of the NIH Neuroscience Information Framework (NIF, <url>http://www.neuinfo.org</url><it/>) and is scheduled for production deployment in the NIF’s next full release.</p> <p>Future papers will describe other aspects of this work in detail, including Annotation Framework Services and components for integrating with external textmining services, such as the NCBO Annotator web service, and with other textmining applications using the Apache UIMA framework.</p

Annotation Studio: Multimedia Annotation for Students

Annotation Studio is a web-based annotation application that integrates a powerful set of textual interpretation tools behind an interface that makes using those tools intuitive for undergraduates. Building on students’ new media literacies, this Open-source application develops traditional humanistic skills including close reading, textual analysis, persuasive writing, and critical thinking. Initial features of the Annotation Studio prototype, supported by an NEH Start-Up Grant, include aligned multi-media annotation of written texts, user-defined sharing of annotations, and grouping of annotation by self-defined tags to support interpretation and argument development. The fully developed application will support annotation of image, video and audio documents; annotation visualization; export of texts with annotations; and a media repository. We will also identify best practices among faculty using Annotation Studio in a broad range of humanities classes across the country

Linking Text and Image with SVG

Annotation and linking (or referring) have been described as "scholarly primitives", basic methods used in scholarly research and publication of all kinds. The online publication of manuscript images is one basic use case where the need for linking and annotation is very clear. High resolution images are of great use to scholars and transcriptions of texts provide for search and browsing, so the ideal method for the digital publication of manuscript works is the presentation of page images plus a transcription of the text therein. This has become a standard method, but leaves open the questions of how deeply the linkages can be done and how best to handle the annotation of sections of the image. This paper presents a new method (named img2xml) for connecting text and image using an XML-based tracing of the text on the page image. The tracing method was developed as part of a series of experiments in text and image linking beginning in the summer of 2008 and will continue under a grant funded by the National Endowment for the Humanities. It employs Scalable Vector Graphics (SVG) to represent the text in an image of a manuscript page in a referenceable form and enables linking and annotation of the page image in a variety of ways. The paper goes on to discuss the scholarly requirements for tools that will be developed around the tracing method, and explores some of the issues raised by the img2xml method