Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling

Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques. Findings of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems. However, not only analytical visualizations may be too complex for target audience but also the information that needs to be presented. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, which involves two aspects: information and display complexity. We propose a general framework where data analysis and result presentation are linked by story synthesis, in which the analyst creates and organizes story contents. Differently, from the previous research, where analytic findings are represented by stored display states, we treat findings as data constructs. In story synthesis, findings are selected, assembled, and arranged in views using meaningful layouts that take into account the structure of information and inherent properties of its components. We propose a workflow for applying the proposed framework in designing visual analytics systems and demonstrate the generality of the approach by applying it to two domains, social media, and movement analysis

Semantics-Space-Time Cube. A Conceptual Framework for Systematic Analysis of Texts in Space and Time

We propose an approach to analyzing data in which texts are associated with spatial and temporal references with the aim to understand how the text semantics vary over space and time. To represent the semantics, we apply probabilistic topic modeling. After extracting a set of topics and representing the texts by vectors of topic weights, we aggregate the data into a data cube with the dimensions corresponding to the set of topics, the set of spatial locations (e.g., regions), and the time divided into suitable intervals according to the scale of the planned analysis. Each cube cell corresponds to a combination (topic, location, time interval) and contains aggregate measures characterizing the subset of the texts concerning this topic and having the spatial and temporal references within these location and interval. Based on this structure, we systematically describe the space of analysis tasks on exploring the interrelationships among the three heterogeneous information facets, semantics, space, and time. We introduce the operations of projecting and slicing the cube, which are used to decompose complex tasks into simpler subtasks. We then present a design of a visual analytics system intended to support these subtasks. To reduce the complexity of the user interface, we apply the principles of structural, visual, and operational uniformity while respecting the specific properties of each facet. The aggregated data are represented in three parallel views corresponding to the three facets and providing different complementary perspectives on the data. The views have similar look-and-feel to the extent allowed by the facet specifics. Uniform interactive operations applicable to any view support establishing links between the facets. The uniformity principle is also applied in supporting the projecting and slicing operations on the data cube. We evaluate the feasibility and utility of the approach by applying it in two analysis scenarios using geolocated social media data for studying people's reactions to social and natural events of different spatial and temporal scales

Modelling Reactive Multimedia: Design and Authoring

Multimedia document authoring is a multifaceted activity, and authoring tools tend to concentrate on a restricted set of the activities involved in the creation of a multimedia artifact. In particular, a distinction may be drawn between the design and the implementation of a multimedia artifact. This paper presents a comparison of three different authoring paradigms, based on the common case study of a simple interactive animation. We present details of its implementation using the three different authoring tools, MCF, Fran and SMIL 2.0, and we discuss the conclusions that may be drawn from our comparison of the three approaches

Temporal Cross-Media Retrieval with Soft-Smoothing

Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media information, where the temporal dimension emerges as a strong source of evidence for learning the temporal correlations across visual and textual modalities. So far, cross-media retrieval models, explored the correlations between different modalities (e.g. text and image) to learn a common subspace, in which semantically similar instances lie in the same neighbourhood. Building on such knowledge, we propose a novel temporal cross-media neural architecture, that departs from standard cross-media methods, by explicitly accounting for the temporal dimension through temporal subspace learning. The model is softly-constrained with temporal and inter-modality constraints that guide the new subspace learning task by favouring temporal correlations between semantically similar and temporally close instances. Experiments on three distinct datasets show that accounting for time turns out to be important for cross-media retrieval. Namely, the proposed method outperforms a set of baselines on the task of temporal cross-media retrieval, demonstrating its effectiveness for performing temporal subspace learning.Comment: To appear in ACM MM 201

Appropriately differentiated ARPE-19 cells regain phenotype and gene expression profiles similar to those of native RPE cells.

PurposeThe RPE cell line ARPE-19 provides a dependable and widely used alternative to native RPE. However, replication of the native RPE phenotype becomes more difficult because these cells lose their specialized phenotype after multiple passages. Compounding this problem is the widespread use of ARPE-19 cells in an undifferentiated state to attempt to model RPE functions. We wished to determine whether suitable culture conditions and differentiation could restore the RPE-appropriate expression of genes and proteins to ARPE-19, along with a functional and morphological phenotype resembling native RPE. We compared the transcriptome of ARPE-19 cells kept in long-term culture with those of primary and other human RPE cells to assess the former's inherent plasticity relative to the latter.MethodsARPE-19 cells at passages 9 to 12 grown in DMEM containing high glucose and pyruvate with 1% fetal bovine serum were differentiated for up to 4 months. Immunocytochemistry was performed on ARPE-19 cells grown on filters. Total RNA extracted from ARPE-19 cells cultured for either 4 days or 4 months was used for RNA sequencing (RNA-Seq) analysis using a 2 × 50 bp paired end protocol. The RNA-Seq data were analyzed to identify the affected pathways and recognize shared ontological classification among differentially expressed genes. RPE-specific mRNAs and miRNAs were assessed with quantitative real-time (RT)-PCR, and proteins with western blotting.ResultsARPE-19 cells grown for 4 months developed the classic native RPE phenotype with heavy pigmentation. RPE-expressed genes, including RPE65, RDH5, and RDH10, as well as miR-204/211, were greatly increased in the ARPE-19 cells maintained at confluence for 4 months. The RNA-Seq analysis provided a comprehensive view of the relative abundance and differential expression of the genes in the differentiated ARPE-19 cells. Of the 16,757 genes with detectable signals, nearly 1,681 genes were upregulated, and 1,629 genes were downregulated with a fold change of 2.5 or more differences between 4 months and 4 days of culture. Gene Ontology analysis showed that the upregulated genes were associated with visual cycle, phagocytosis, pigment synthesis, cell differentiation, and RPE-related transcription factors. The majority of the downregulated genes play a role in cell cycle and proliferation.ConclusionsThe ARPE-19 cells cultured for 4 months developed a phenotype characteristic of native RPE and expressed proteins, mRNAs, and miRNAs characteristic of the RPE. Comparison of the ARPE-19 RNA-Seq data set with that of primary human fetal RPE, embryonic stem cell-derived RPE, and native RPE revealed an important overall similar expression ratio among all the models and native tissue. However, none of the cultured models reached the absolute values in the native tissue. The results of this study demonstrate that low-passage ARPE-19 cells can express genes specific to native human RPE cells when appropriately cultured and differentiated