Nádia P. Kozievitch

A teaching tool for parasitology: enhancing learning with annotation and image retrieval

Parasitology is a basic course in life sciences curricula, but up to now it has few computer-assisted teaching tools. We present SuperIDR, a tool which supports annotation and search (based on a textual and a visual description) in the biodiversity domain. In addition, it provides a feature to aid comparison of morphological characteristics among different species. Preliminary results with two experiments show that students found the tool to be very useful, contributing to an alternative learning approach.

CTRnet DL for disaster information services

We describe our work in collecting, analyzing and visualizing online information (e.g., Web documents, images, tweets), which are to be maintained by the Crisis, Tragedy and Recovery Network (CTRnet) digital library. We have been collecting resources about disaster events, as well as campus and other major shooting events, in collaboration with the Internet Archive (IA). Social media data (e.g., tweets, Facebook data) also have been collected and analyzed. Analyzed results are visualized using graphs and tag clouds. Exploratory content-based image retrieval has been applied in one of our image collections. We explain our CTR ontology development methodology and collaboration with Arlington County, VA and IBM, in a Center for Community Security and Resilience funded project.

Describing OAI-ORE from the 5S framework perspective

Despite the popularity of applications which manage complex digital objects, few attempts have been made to formally characterize them and their services. This poster addresses this problem starting an analysis of OAI-ORE specifications under the 5s framework perspective, verifying how they can be integrated to describe complex digital objects as resources that could be later exchanged.

Study of Google Popularity Times Series for Commercial Establishments of Curitiba and Chicago

Urban computing is a recent area of study that helps us to understand the nature of urban phenomena. In this sense, an important aspect to study is the dynamics of commercial establishments popularity in the city. Recently, Google launched a new service that provides popularity time series of some commercial establishments in several cities. This is a valuable source of data that allow us to better understand the dynamics of establishments popularity, helping to change our perceived physical limits about the city, which can enable the development of new applications and urban services. The results of this study are: (1) characterization of Google popularity time series for bars and restaurants in the cities of Curitiba/Brazil and Chicago/USA. Among the results, we find cultural characteristics of these cities, as well as a favorable clustering of similar venues based on the temporal pattern of popularity; (2) evaluation of reproduction of Google popularity time series using Foursquare data. In this evaluation, we found evidence that Foursquare data might be used for this purpose. This means that for places where Google does not offer this service data from Foursquare, or other source, could be used. This enables the exploration of a greater number of establishments in, for example, a new venue recommendation engine.

SuperIDR: A Tool for Fish Identification and Information Retrieval

ABSTRACT Students, fisheries professionals, and the general public may value computer-facilitated assistance for fish identification and access to ecological and life history information. We developed SuperIDR, a software package supporting such applications, by utilizing the search and data retrieval capabilities of digital libraries, as well as key features of tablet PCs. We demonstrated SuperIDR utilizing a database with information on 207 freshwater fishes of Virginia. A user may annotate fish images and identify fishes by using a dichotomous key; searching for key words, similar images, subimages, or annotations on images; or combinations of these approaches. Students using the software demonstrated enhanced ability to correctly identify specimens. Their comments led to improvements, including the addition of new features. The PC-based system for identifying freshwater fishes of Virginia may be downloaded and modified. SuperIDR is a prototype for PC-based species identification applications—the syste...

Reusing a compound-based infrastructure for searching video stories

The fast evolution of technology has led to a growing demand for multimedia data, increasing the amount of research into efficient systems to manage those materials. A lot of research has being done by the Content-Based Image Retrieval (CBIR) community in the field of images. Nowadays, they play a key role in digital applications. Thus, contextual integration of images with different sources is vital. It involves reusing and aggregating a large amount of information with other media types. In particular, if we consider video data, images can be used to summarize videos into storyboards, providing an easy way to navigate and to browse large video collections. This has been the goal of a quickly evolving research area known as video summarization. In this paper, we present a novel approach to reuse the CBIR infrastructure for searching video stories, taking advantage of the compound object (CO) concept to integrate resources. Our approach relies on a specific component technology to encapsulate the CBIR related tasks and integrate them with video summarization techniques, known as Digital Content Component (DCC). Such a strategy provides an effective way to reuse, compose, and aggregate both content and processing software.

Exploring Data Fusion under the Image Retrieval Domain

Advanced services in data compression, data storage, and data transmission have been developed and are widely used to address the required capabilities of an assortment of systems across diverse application domains. In order to reuse, integrate, unify, manage, and support heterogeneous resources, a number of works and concepts have emerged as a means to facilitate aggregation of content and to help system developers. In particular, images, along with existing Content-Based Image Retrieval services, have the potential to play a key role in information systems, due to the large availability of images and the need to integrate them with existing collections, metadata, and available image manipulation softwares and applications. In this work, we explore a data fusion approach for solving data value conflicts in the context of image retrieval domain. The main novelty resides in automatically solving conflicts without user intervention. The proposed solution is based on the use of rules, which are defined in previous integration processes. Our approach reduces the need for human intervention for keeping a clean and integrated view of an image repository when new data sources are added to an image management system.

A formal approach for the specification of digital complex objects

Complex objects (COs) have surged as a way to integrate different digital resources under a same logical unit in order to facilitate aggregation and reuse. However, there is still a lack of consensus on precise theoretical foundations for COs, especially regarding design and specification, which compromise their utility and integration with existing software tools. Moreover, there has been little investigation on aspects related to the modeling of COs by the end user, much due to the lack of appropriate tools for this goal. In this work, we present a new Digital Library (DL) metamodel specially designed for the CO modeling which is grounded in formal theoretical specification for COs. More specifically, our goal is two-fold: (i) to indirectly validate our CO formalization by instantiating it within a DL modeling tool -- 5SGraph; and (ii) to investigate the difficulties of CO modeling and specification by real users using the specified metamodel. Experiments with real users indicate that the use of the metamodel and the graphical tool facilitates the understanding of the COs structure and the modeling process.