Search results for "Data Science"
showing 10 items of 495 documents
Timeliness of Open Data in Open Government Data Portals Through Pandemic-related Data: a long data way from the publisher to the user
2020
The paper addresses the “timeliness” of data in open government data (OGD) portals. It is one of the primary principles of open data, which is considered to be a success factor, while at the same time it is one 0f the biggest barriers that can disrupt users trust in data and even the desire to use the entire open data portal. However, assessing this aspect is a very difficult task that, in most cases, becomes an impossible for open data users. There is therefore a lack of comparative studies on the timeliness of data of different national open data portals. Unfortunately, 2020 gave the opportunity to find out this. It became easy enough to compare how long is the data path from the data hol…
A multi-perspective knowledge-driven approach for analysis of the demand side of the Open Government Data portal
2021
Abstract Open data are freely available and can be used by every stakeholder for its own purposes. However, the practice demonstrates that it is important to ensure that the source from which they are available is usable and facilitates the re-use of data to the widest possible range of stakeholders. This task is carried out by open government data (OGD) portals. Therefore, this study proposes a multi-perspective approach where an OGD portal is analyzed from (1) citizens' perspective, (2) users' perspective, (3) experts' perspective, and (4) state of the art. By considering these perspectives, we can define how to improve the portal in question by focusing on its demand side. In view of the…
Wikipedia network analysis of cancer interactions and world influence
2019
AbstractWe apply the Google matrix algorithms for analysis of interactions and influence of 37 cancer types, 203 cancer drugs and 195 world countries using the network of 5 416 537 English Wikipedia articles with all their directed hyperlinks. The PageRank algorithm provides the importance order of cancers which has 60% and 70% overlaps with the top 10 cancers extracted from World Health Organization GLOBOCAN 2018 and Global Burden of Diseases Study 2017, respectively. The recently developed reduced Google matrix algorithm gives networks of interactions between cancers, drugs and countries taking into account all direct and indirect links between these selected 435 entities. These reduced n…
Machine-learned selection of psychological questionnaire items relevant to the development of persistent pain after breast cancer surgery
2018
Background: Prevention of persistent pain after breast cancer surgery, via early identification of patients at high risk, is a clinical need. Psychological factors are among the most consistently proposed predictive parameters for the development of persistent pain. However, repeated use of long psychological questionnaires in this context may be exhaustive for a patient and inconvenient in everyday clinical practice. Methods: Supervised machine learning was used to create a short form of questionnaires that would provide the same predictive performance of pain persistence as the full questionnaires in a cohort of 1000 women followed up for 3 yr after breast cancer surgery. Machine-learned …
Molecular modeling in cardiovascular pharmacology: Current state of the art and perspectives.
2021
Abstract Molecular modeling in pharmacology is a promising emerging tool for exploring drug interactions with cellular components. Recent advances in molecular simulations, big data analysis, and artificial intelligence (AI) have opened new opportunities for rationalizing drug interactions with their pharmacological targets. Despite the obvious utility and increasing impact of computational approaches, their development is not progressing at the same speed in different fields of pharmacology. Here, we review current in silico techniques used in cardiovascular diseases (CVDs), cardiological drug discovery, and assessment of cardiotoxicity. In silico techniques are paving the way to a new era…
Challenges and Limits within the Electronic Environment, an Interdisciplinary Approach
2013
Abstract One of the main aims of this paper it to present implications and correlation between economy, religion, and electronic environment in Information Communication Technologies to develop a basic understanding of the field's ontology, by incorporating Web epistemology and theory. By focusing attention on the electronic environment, websites, as the main object of study and by presenting the hidden socio-economic and political aspects that govern this environment structural and operational, this paper offers an investigation and analyze of cyber economic and religious blend.
What’s Wrong with the Diffusion of Innovation Theory?
2001
This paper examines the usefulness of the diffusion of innovation research in developing theoretical accounts of the adoption of complex and networked IT solutions. We contrast six conjectures underlying DOI research with field data obtained from the study of the diffusion of EDI. Our analysis shows that DOI based analyses miss some important facets in the diffusion of complex technologies. We suggest that complex IT solutions should be understood as socially constructed and learning intensive artifacts, which can be adopted for varying reasons within volatile diffusion arenas. Therefore DOI researchers should carefully recognize the complex, networked, and learning intensive features of te…
BIG-AFF
2017
Recent research has provided solid evidence that emotions strongly affect motivation and engagement, and hence play an important role in learning. In BIG-AFF project, we build on the hypothesis that ``it is possible to provide learners with a personalised support that enriches their learning process and experience by using low intrusive (and low cost) devices to capture affective multimodal data that include cognitive, behavioural and physiological information''. In order to deal with the affect management complete cycle, thus covering affect detection, modelling and feedback, there is lack of standards and consolidated methodologies. Being our goal to develop realistic affect-aware learnin…
A Approach to Clinical Proteomics Data Quality Control and Import
2011
International audience; Biomedical domain and proteomics in particular are faced with an increasing volume of data. The heterogeneity of data sources implies heterogeneity in the representation and in the content of data. Data may also be incorrect, implicate errors and can compromise the analysis of experiments results. Our approach aims to ensure the initial quality of data during import into an information system dedicated to proteomics. It is based on the joint use of models, which represent the system sources, and ontologies, which are use as mediators between them. The controls, we propose, ensure the validity of values, semantics and data consistency during import process.
Deep Learning and Cultural Heritage: The CEPROQHA Project Case Study
2019
Cultural heritage takes an important part of the history of humankind as it is one of the most powerful tools for the transfer and preservation of moral identity. As a result, these cultural assets are considered highly valuable and sometimes priceless. Digital technologies provided multiple tools that address challenges related to the promotion and information access in the cultural context. However, the large data collections of cultural information have more potential to add value and address current challenges in this context with the recent progress in artificial intelligence (AI) with deep learning and data mining tools. Through the present paper, we investigate several approaches tha…