Related papers: Advancements in scientific data searching, sharing…
The efficiency and service quality in a medical environment can be improved by using electronic documents (or e-docs) and digital signatures to speed up both doctors' activity and to provide in the same time easy retrieval and use of needed…
This is a thought piece on data-intensive science requirements for databases and science centers. It argues that peta-scale datasets will be housed by science centers that provide substantial storage and processing for scientists who access…
Healthcare AI holds the potential to increase patient safety, augment efficiency and improve patient outcomes, yet research is often limited by data access, cohort curation, and tooling for analysis. Collection and translation of electronic…
Many data structures support dictionaries, also known as maps or associative arrays, which store and manage a set of key-value pairs. A \emph{multimap} is generalization that allows multiple values to be associated with the same key. For…
As XML becomes ubiquitous and XML storage and processing becomes more efficient, the range of use cases for these technologies widens daily. One promising area is the integration of XML and data warehouses, where an XML-native database…
Data warehouse store and provide access to large volume of historical data supporting the strategic decisions of organisations. Data warehouse is based on a multidimensional model which allow to express user's needs for supporting the…
Background: Electronic health records (EHRs) enable machine learning for diagnosis, prognosis, and clinical decision support. However, EHR standards vary by country and hospital, making records often incompatible. This limits large-scale…
Despite progresses in data engineering, there are areas with limited consistencies across data validation and documentation procedures causing confusions and technical problems in research involving machine learning. There have been…
AI documentation is a rapidly-growing channel for coordinating the design of AI technologies with policies for transparency and accessibility. Calls to standardize and enact documentation of algorithmic harms and impacts are now…
The information retrieval (IR) community has a strong tradition of making the computational artifacts and resources available for future reuse, allowing the validation of experimental results. Besides the actual test collections, the…
Advances in Internet-of-Things (IoT) technologies have prompted the integration of IoT devices with business processes (BPs) in many organizations across various sectors, such as manufacturing, healthcare and smart spaces. The proliferation…
In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms. Various medical image…
The development and operation of smart cities relyheavily on large-scale Internet-of-Things (IoT) networks and sensor infrastructures that continuously monitor various aspects of urban environments. These networks generate vast amounts of…
At a time when the quantity of - more or less freely - available data is increasing significantly, thanks to digital corpora, editions or libraries, the development of data mining tools or deep learning methods allows researchers to build a…
Research methods and procedures are core aspects of the research process. Metadata focused on these components is critical to supporting the FAIR principles, particularly reproducibility. The research reported on in this paper presents a…
There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make…
MPI is the most widely used data transfer and communication model in High Performance Computing. The latest version of the standard, MPI-3, allows skilled programmers to exploit all hardware capabilities of the latest and future…
We describe the current state and future plans for a set of tools for scientific data management (SDM) designed to support scientific transparency and reproducible research. SDM has been in active use at our MRI Center for more than two…
We study the formalization of a collection of documents created for a Software Engineering project from an MKM perspective. We analyze how document and collection markup formats can cope with an open-ended, multi-dimensional space of…
Harvested metadata often suffers from uneven quality to the point that utility is compromised. Although some aggregators have developed methods for evaluating and repairing specific metadata problems, it has been unclear how these methods…