Figure 1: Three steps in the edit-by-recommendation functionality In the world of visual storytelling, narrative development relies on a particular temporal ordering of shots and sequences and scenes. Rarely is this ordering cast in stone. Rather, the particular ordering of a story reflects a myriad of interdependent decisions about the interplay of structure, narrative arc and character development. For storytellers, particularly those developing their narratives from large documentary archives, it would be helpful to have a visualization system partnered with them to present suggestions for the most compelling story path. We present Storied Navigation, a video editing system that helps authors compose a sequence of scenes that tell a story, by selecting from a corpus of annotated clips. The clips are annotated in unrestricted natural language. Authors can also type a story in unrestricted English, and the system finds possibilities for clips that best match high-level elements of the story. Beyond simple keyword matching, these elements can include the characters, emotions, themes, and story structure. Authors can also interactively replace existing scenes or predict the next scene to continue a story, based on these characteristics. Storied Navigation gives the author the feel of brainstorming about the story rather than simply editing the media.

Abstract. In this paper we present the StoryStream system, a mobile application that constructs a documentary type of narrative of user generated non-fiction stories, which are orally presented to a visitor of a neighbourhood while he or she freely explores the surroundings. The aim of the system is to enhance the exploration experience by providing context related information that adapts to the information interests of the user.

Abstract not found

A narrative-based collaborative writing tool for constructing coherent technical documents by

Abstract. The recent media focus on Smart City services, particularly ride sharing, that provide ordinary users with the ability to advertise their resources has highlighted society’s need for transparent and accountable systems. Current systems offer little transparency behind their processes that claim to provide accountability to and for their users. To address such a concern, some applications provide a static, textual description of the automated algorithms used, with a view to promote transparency. However, this is not sufficient to inform users exactly how information is derived. These descriptions can be enhanced by explaining the actual execution of the algorithm, the data it operated on, and the parameters it was configured with. Such descriptions about a system’s execution and its information flow can be expressed using PROV, a standardised provenance data model. However, given its generic and domain-agnostic nature, PROV only provides limited information about the relationship between provenance elements. Combined with semantic information, a PROV instance becomes a rich resource, which can be exploited to provide users with understandable accounts of automated processes, thereby promoting transparency and accountability. Thus, this paper contributes, a vocabulary for Smart City resource sharing applications, an architecture for accountable systems, and a set of use cases that demonstrate and quantify how the semantics enrich an account in a ride share scenario.

How we assimilate stories into our common experiences and shape culture is the field of study known as narrative intelligence. By following these assumptions and investigating theories of conversation and rhetoric, this paper outlines a generic framework for a visual collaborative storytelling system that emphasises participatory narration and shared understanding in a situated context.

Abstract. Biographies are widely used for learning and researching history. This paper argues that biographies make a promising application case for Linked Data. We present an approach where life stories, extracted from unstructured texts and structured cultural heritage databases, are represented in terms a harmonized event-based model that is used for linking and enriching semantically heterogeneous data from distributed sources. As a result of this work, we present the first demonstration of the “Semantic National Biography”, a web application on top of a SPARQL-endpoint based on the 6,381 short biographies of the Finnish National Biography interlinked with related datasets. 1 Biographies as Linked Data Biographies are regularly found on best-seller lists of books. Publishing biographies as Linked Data on the Web provides new possibilities for enhancing reading experience: 1. Data linking. Stories can be linked with additional data, e.g., an artist’s biography to colleagues of the same artist group or information about her birth and death places. 2. Data enriching. Data form different source can be used for enriching the narrative. For example, metadata about a painting by an artists tells that he there should be the corresponding painting event in her biography that may be missing. 3. Data fusion. Similar biographical data from different sources can be conflicting: pointing out possible defects would enhance data quality. 4. Multi-linguality. Information in different languages can be aggregated. 5. Visualization. Data can be visualized in different ways and by using multimedia. The paper describes first results of a project 1, where exploitation of these possibilities is tested by publishing the Finnish National Biography 2 (NB), a collection of 6,381 short biographies, as Linked Data. This work has two practical goals: 1) Designing a data publication model and related services as a SPARQL endpoint with appropriate APIs for application development. 2) Designing novel end-user applications on top of the data publication addressing use cases for both researchers and laymen. 1 Our work was funded by Tekes and the Linked Data Finland consortium of 20 organizations.