Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

VIKI : a semiotic-based system for multilingual knowledge retrieval

Abstract Since its creation, the Internet has permeated our daily life. The web is omnipresent for communication, research and organization. This exploitation has resulted in the rapid development of the Internet. Nowadays, the Internet is the biggest container of resources. Information databases such as Wikipedia, Dmoz and the open data available on the net are a great informational potentiality for mankind. The easy and free web access is one of the major feature characterizing the Internet culture. Ten years earlier, the web was completely dominated by English. Today, the web community is no longer only English speaking but it is becoming a genuinely multilingual community. The availability of content is intertwined with the availability of logical organizations (ontologies) for which multilinguality plays a fundamental role. In this work we introduce a very high-level logical organization fully based on semiotic assumptions. We thus present the theoretical foundations as well as the ontology itself, named Linguistic Meta-Model. The most important feature of Linguistic Meta-Model is its ability to support the representation of different knowledge sources developed according to different underlying semiotic theories. This is possible because mast knowledge representation schemata, either formal or informal, can be put into the context of the so-called semiotic triangle. In order to show the main characteristics of Linguistic Meta-Model from a practical paint of view, we developed VIKI (Virtual Intelligence for Knowledge Induction). VIKI is a work-in-progress system aiming at exploiting the Linguistic Meta-Model structure for knowledge expansion. It is a modular system in which each module accomplishes a natural language processing task, from terminology extraction to knowledge retrieval. VIKI is a supporting system to Linguistic Meta-Model and its main task is to give some empirical evidence regarding the use of Linguistic Meta-Model without claiming to be thorough.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

Use of mobile devices to answer online surveys: implications for research.

BACKGROUND: There is a growing use of mobile devices to access the Internet. We examined whether participants who used a mobile device to access a brief online survey were quicker to respond to the survey but also, less likely to complete it than participants using a traditional web browser. FINDINGS: Using data from a recently completed online intervention trial, we found that participants using mobile devices were quicker to access the survey but less likely to complete it compared to participants using a traditional web browser. More concerning, mobile device users were also less likely to respond to a request to complete a six week follow-up survey compared to those using traditional web browsers. CONCLUSIONS: With roughly a third of participants using mobile devices to answer an online survey in this study, the impact of mobile device usage on survey completion rates is a concern. TRIAL REGISTRATION: ClinicalTrials.gov: NCT01521078.

The health promotion model and rare disease patients : a mixed methods study examining adherence to treatment in men with congenital hypogonadotropic hypogonadism

Rare diseases are typically chronic medical conditions of genetic etiology characterized by low prevalence and high complexity. Patients living with rare diseases face numerous physical, psychosocial and economic challenges that place them in the realm of health disparities. Congenital hypogonadotropic hypogonadism (CHH) is a rare endocrine disorder characterized by absent puberty and infertility. Little is known about the psychosocial impact of CHH on patients or their adherence to available treatments. This project aimed to examine the relationship between illness perceptions, depressive symptoms and adherence to treatment in men with CHH using the nursing-sensitive Health Promotion Model (HPM). A community based participatory research (CBPR) framework was employed as a model for empowering patients and overcoming health inequities. The study design used a sequential, explanatory mixed-methods approach. To reach dispersed CHH men, we used web-based recruitment and data collection (online survey). Subsequently, three patient focus groups were conducted to provide explanatory insights into the online survey (i.e. barriers to adherence, challenges of CHH, and coping/support) The online survey (n=101) revealed that CHH men struggle with adherence and often have long gaps in care (40% >1 year). They experience negative psychosocial consequences because of CHH and exhibit significantly increased rates of depression (p<0.001). Focus group participants (n=26) identified healthcare system, interpersonal, and personal factors as barriers to adherence. Further, CHH impacts quality of life and impedes psychosexual development in these men. The CHH men are active internet users who rely on the web forcrowdsourcing solutions and peer-to-peer support. Moreover, they are receptive to web-based interventions to address unmet health needs. This thesis contributes to nursing knowledge in several ways. First, it demonstrates the utility of the HPM as a valuable theoretical construct for understanding medication adherence and for assessing rare disease patients. Second, these data identify a range of unmet health needs that are targets for patient-centered interventions. Third, leveraging technology (high-tech) effectively extended the reach of nursing care while the CBPR approach and focus groups (high-touch) served as concurrent nursing interventions facilitating patient empowerment in overcoming health disparities. Last, these findings hold promise for developing e-health interventions to bridge identified shortfalls in care and activating patients for enhanced self- care and wellness -- Les maladies rares sont généralement de maladies chroniques d'étiologie génétique caractérisées par une faible prévalence et une haute complexité de traitement. Les patients atteints de maladies rares sont confrontés à de nombreux défis physiques, psychosociaux et économiques qui les placent dans une posture de disparité et d'inégalités en santé. L'hypogonadisme hypogonadotrope congénital (CHH) est un trouble endocrinien rare caractérisé par l'absence de puberté et l'infertilité. On sait peu de choses sur l'impact psychosocial du CHH sur les patients ou leur adhésion aux traitements disponibles. Ce projet vise à examiner la relation entre la perception de la maladie, les symptômes dépressifs et l'observance du traitement chez les hommes souffrant de CHH. Cette étude est modélisée à l'aide du modèle de la Promotion de la santé de Pender (HPM). Le cadre de l'approche communautaire de recherche participative (CBPR) a aussi été utilisé. La conception de l'étude a reposé sur une approche mixte séquentielle. Pour atteindre les hommes souffrant de CHH, un recrutement et une collecte de données ont été organisées électroniquement. Par la suite, trois groupes de discussion ont été menées avec des patients experts impliqués au sein d'organisations reliés aux maladies rares. Ils ont été invités à discuter certains éléments additionnels dont, les obstacles à l'adhésion au traitement, les défis généraux de vivre avec un CHH, et l'adaptation à la maladie en tenant compte du soutien disponible. Le sondage en ligne (n = 101) a révélé que les hommes souffrant de CHH ont souvent de longues périodes en rupture de soins (40% > 1 an). Ils vivent des conséquences psychosociales négatives en raison du CHH et présentent une augmentation significative des taux de dépression (p <0,001). Les participants aux groupes de discussion (n = 26) identifient dans l'ordre, les systèmes de soins de santé, les relations interpersonnelles, et des facteurs personnels comme des obstacles à l'adhésion. En outre, selon les participants, le CHH impacte négativement sur leur qualité de vie générale et entrave leur développement psychosexuel. Les hommes souffrant de CHH se considèrent être des utilisateurs actifs d'internet et comptent sur le web pour trouver des solutions pour trouver des ressources et y recherchent le soutien de leurs pairs (peer-to-peer support). En outre, ils se disent réceptifs à des interventions qui sont basées sur le web pour répondre aux besoins de santé non satisfaits. Cette thèse contribue à la connaissance des soins infirmiers de plusieurs façons. Tout d'abord, elle démontre l'utilité de la HPM comme une construction théorique utile pour comprendre l'adhésion aux traitements et pour l'évaluation des éléments de promotion de santé qui concernent les patients atteints de maladies rares. Deuxièmement, ces données identifient une gamme de besoins de santé non satisfaits qui sont des cibles pour des interventions infirmières centrées sur le patient. Troisièmement, méthodologiquement parlant, cette étude démontre que les méthodes mixtes sont appropriées aux études en soins infirmiers car elles allient les nouvelles technologies qui peuvent effectivement étendre la portée des soins infirmiers (« high-tech »), et l'approche CBPR par des groupes de discussion (« high-touch ») qui ont facilité la compréhension des difficultés que doivent surmonter les hommes souffrant de CHH pour diminuer les disparités en santé et augmenter leur responsabilisation dans la gestion de la maladie rare. Enfin, ces résultats sont prometteurs pour développer des interventions e-santé susceptibles de combler les lacunes dans les soins et l'autonomisation de patients pour une meilleure emprise sur les auto-soins et le bien-être.

Transparency and trust in government (2007-2014): a comparative study

In a 2000 report entitled "Trust in government. Ethics measures in OECD countries," OECD Secretary-General Donald J. Johnston emphasized the fact that public ethics are considered as a keystone of good governance. Moreover, public ethics are a prerequisite to public trust, which is in turn vital not only to any public service, but also to any society in general. At the same time, transparency reforms have flourished over the last few years and have several times been designed as a response to public distrust. Therefore, ethics, transparency and trust are closely linked together in a supposed virtuous circle where transparency works as a factor of better public ethics and leads to more trust in government on the citizens' side. This article explores the links between transparency and levels of trust in 10 countries between 2007 and 2014, using open data indexes and access to information requests as proxies for transparency. A national ranking of transparency, based on requests submitted by citizens to the administration and open data indexes, is then proposed. Key findings show that there is no sharp decline of trust in government in all countries considered in this article, and that transparency and trust in government are not systematically positively associated. Therefore, this article challenges the common assumption, mostly found in the normative literature, about a positive interrelation between the two, where trust in government is conceived as a beneficial effect of administrative transparency.

Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.

A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Webdatanet : Innovation and quality in web-based data collection

The article discusses the development of WEBDATANET established in 2011 which aims to create a multidisciplinary network of web-based data collection experts in Europe. Topics include the presence of 190 experts in 30 European countries and abroad, the establishment of web-based teaching and discussion platforms and working groups and task forces. Also discussed is the scope of the research carried by WEBDATANET. In light of the growing importance of web-based data in the social and behavioral sciences, WEBDATANET was established in 2011 as a COST Action (IS 1004) to create a multidisciplinary network of web-based data collection experts: (web) survey methodologists, psychologists, sociologists, linguists, economists, Internet scientists, media and public opinion researchers. The aim was to accumulate and synthesize knowledge regarding methodological issues of web-based data collection (surveys, experiments, tests, non-reactive data, and mobile Internet research), and foster its scientific usage in a broader community.

An interactive web-GIS tool for risk analysis: a case study in the Fella River basin, Italy

This paper presents a prototype of an interactive web-GIS tool for risk analysis of natural hazards, in particular for floods and landslides, based on open-source geospatial software and technologies. The aim of the presented tool is to assist the experts (risk managers) in analysing the impacts and consequences of a certain hazard event in a considered region, providing an essential input to the decision-making process in the selection of risk management strategies by responsible authorities and decision makers. This tool is based on the Boundless (OpenGeo Suite) framework and its client-side environment for prototype development, and it is one of the main modules of a web-based collaborative decision support platform in risk management. Within this platform, the users can import necessary maps and information to analyse areas at risk. Based on provided information and parameters, loss scenarios (amount of damages and number of fatalities) of a hazard event are generated on the fly and visualized interactively within the web-GIS interface of the platform. The annualized risk is calculated based on the combination of resultant loss scenarios with different return periods of the hazard event. The application of this developed prototype is demonstrated using a regional data set from one of the case study sites, Fella River of northeastern Italy, of the Marie Curie ITN CHANGES project.

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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.

Big data and other challenges in the quest for orthologs.

Given the rapid increase of species with a sequenced genome, the need to identify orthologous genes between them has emerged as a central bioinformatics task. Many different methods exist for orthology detection, which makes it difficult to decide which one to choose for a particular application. Here, we review the latest developments and issues in the orthology field, and summarize the most recent results reported at the third 'Quest for Orthologs' meeting. We focus on community efforts such as the adoption of reference proteomes, standard file formats and benchmarking. Progress in these areas is good, and they are already beneficial to both orthology consumers and providers. However, a major current issue is that the massive increase in complete proteomes poses computational challenges to many of the ortholog database providers, as most orthology inference algorithms scale at least quadratically with the number of proteomes. The Quest for Orthologs consortium is an open community with a number of working groups that join efforts to enhance various aspects of orthology analysis, such as defining standard formats and datasets, documenting community resources and benchmarking. AVAILABILITY AND IMPLEMENTATION: All such materials are available at http://questfororthologs.org. CONTACT: erik.sonnhammer@scilifelab.se or c.dessimoz@ucl.ac.uk.