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Context and Motivation: With the increasing quantity and versatility of data in data-intensive domains, designing information systems, to effectively process the relevant information is becoming increasingly challenging. Conceptual modeling could tackle such challenges in numerous manners as a preliminary phase in the software development process. But assessing data and model synchronization becomes an issue in domains where data are heterogeneous, have a diverse provenance and are subject to continuous change. Question/problem: The problem is how to determine and demonstrate the ability of a conceptual schema to represent the concepts and the data in the particular data-intensive domain. Principal Ideas/Results: A validation approach has been designed for the Conceptual Schema of the Human Genome by investigating the particular issues in the genetic domain and systematically connecting constituents of this conceptual schema with potential instances in samples of genome-related data. As a result, this approach provided us accurate insight in terms of attribute resemblance, completeness, structure and shortcomings. Contribution: This work demonstrates how the strategy of conceptualizing a data-intensive domain and then validating that concept by reconnecting this with the attributes of the real world data domain, can be generalized. Conceptual modeling has a limited resistance to the evolution of data, which is the next problem to face.

Celiac disease affects an estimated 1% of the population. The only existing treatment is a strict gluten-free diet but there are myriad aspects of managing the disease that affect the lifestyle of both the CD patient and those close to them. The goal of this study was to design, develop and test a prototype of a mobile application to promote wellness and support for individuals with CD. The proposed application’s aim is to serve as a platform for CD patients and members from their social circle, to help with sharing general and specific information about four lifestyle aspects: social, emotional, food, and wellness. The application aids with the management of a gluten-free diet from the social circle perspective for the specific CD patient. Perceptions towards the usability of the application were gathered from 22 participants and analyzed via a USE questionnaire. The results from the survey reported overall satisfaction of the prototype and useful insights were gathered for subsequent versions. The general expected benefit of this evidence-based application is improved quality of life for the CD patient due to their social circle being well informed about the management of the disease and its potential complications.

Healthcare providers generally spend excessive time on administrative tasks at the expense of direct patient care. The emergence of new artificial intelligence and natural language processing technologies gives rise to innovations that could relieve them of this burden. In this paper, we present a pipeline structure for building dialogue summarization systems. Our pipeline summarizes a consultation of a patient with a care provider and automatically generates a report compliant with medical formats. Four pipeline components are used to generate a report based on audio input. The outputs of each component are analyzed to determine the most important challenges and issues. The current proof-of-concept, which was applied to eight doctor-to-patient sessions concerning ear infection, shows that automatic dialogue summarization and reporting is achievable, but requires improvements to increase completeness.

Reference architectures provide strong foundations for the implementation and development of enterprise architecture. It is common for enterprise architects to encounter the challenge of managing an increasingly complex architecture. This management can be enhanced by the application of domain-independent maturity models. Nevertheless, existing maturity models do not provide enterprise architects with metrics and domain-specific solutions to ensure a successful evolution path. This research in progress presents a process for tailoring domain-specific enterprise architecture maturity models. As a proof of concept, we chose the domain of hospitals because of the following reasons: wide variety of interdependencies and many medical disciplines with their own processes, technology, and data requirements; there is no specific maturity model for the enterprise architecture of hospitals; and there are many restrictions (e.g. governmental laws) for the medical domain which are expressed in a reference enterprise architecture. We follow a design science approach from the problem investigation to the treatment design. We conclude this paper with the results of the initial validation that has been conducted with architects from the healthcare domain.

Risk assessment of rare and complex diseases such as Neuroblastoma requires an efficient management of interdisciplinary data. Recent advances in genomic testing are revealing new diagnosis targets whose storage and analysis is becoming a big challenge. The use of Conceptual Models (CM) defining and structuring Neuroblastoma domain serves as a basis to determine the information required for diagnosing the disease. A Genomic Information System (GeIS) built upon a CM, greatly facilitate the integration and management of the heterogeneous and dispersed genomic data. The correct exploitation of the validated dataset leads to an efficient and early risk assessment for patients with Neuroblastoma.

Effective data management of clinical information is well-known to be a very complex task. The breast cancer context provides a good example of how challenging the problem is in Information Systems terms. In fact, it is one of the basic problems faced by clinicians who work in this area. However, this problem is even bigger when clinicians and biologists try to relate these data to biological data obtained from research studies about this disease. This paper shows how Conceptual Modeling practices provide reliable working environments where clinical and biological information are clearly linked. We focus on miRNAs expression studies in breast cancer patients as a representative study of biological data in this environment. Representing all these biological data using Conceptual Modeling techniques and connecting it with the clinical information properly modeled using the same technique, creates the appropriate background to develop an information system able to manage efficiently and analyze all this information.

Due to the complexity of genomic information and the broad amount of data produced every day, the genomic information accessible on the web has become very difficult to integrate, which hinders the research process. Using the knowledge from the Data Quality field and after a specific study of a set of genomic databases we have found problems related to six Data Quality dimensions. The aim of this paper is to highlight the problems that bioinformaticians have to face when they integrate information from different genomic databases. The contribution of this paper is to identify and characterize those problems in order to understand which ones hinder the research process, increasing the time-waste that this task means for researchers.

The catalogs of molecular biology databases does not provide a full description of databases, so the user should select databases using limited information available. Taking into account this fact, in the context of an initiative called BioDBCore, a group of experts proposes core metadata definitions to describe the molecular biology databases. However, how to use these metadata to infer the quality of a database is a clear open issue. In the present work, we propose an ontology-based approach aiming to guide the database selection process from molecular biology database catalogs using these metadata.