相关论文: OpenHealth Lake: Designing and testing a data lake…
Data lakes are becoming increasingly prevalent for big data management and data analytics. In contrast to traditional 'schema-on-write' approaches such as data warehouses, data lakes are repositories storing raw data in its original formats…
The recently proposed Data Lakehouse architecture is built on open file formats, performance, and first-class support for data transformation, BI and data science: while the vision stresses the importance of lowering the barrier for data…
In the rapidly evolving landscape of digital assets and blockchain technologies, the necessity for robust, scalable, and secure data management platforms has never been more critical. This paper introduces a novel software architecture…
Objective: To (1) demonstrate the implementation of a data science platform built on open-source technology within a large, academic healthcare system and (2) describe two computational healthcare applications built on such a platform.…
Relational Database Management Systems designed for Online Analytical Processing (RDBMS-OLAP) have been foundational to democratizing data and enabling analytical use cases such as business intelligence and reporting for many years.…
Data lakes have emerged as a flexible and scalable solution for storing and analyzing large volumes of heterogeneous data, including structured, semi-structured, and unstructured formats. Despite their growing adoption in both industry and…
Large organizations are seeking to create new architectures and scalable platforms to effectively handle data management challenges due to the explosive nature of data rarely seen in the past. These data management challenges are largely…
Objective: The objective was to develop a cloud-based, federated system to serve as a single point of search, discovery and analysis for data generated under the NIH Helping to End Addiction Long-term (HEAL) Initiative. Materials and…
The personalized health care service utilizes the relational patient data and big data analytics to tailor the medication recommendations. However, most of the health care data are in unstructured form and it consumes a lot of time and…
This vision paper introduces a pioneering data lake architecture designed to meet Life \& Earth sciences' burgeoning data management needs. As the data landscape evolves, the imperative to navigate and maximize scientific opportunities has…
Scientific data management is at a critical juncture, driven by exponential data growth, increasing cross-domain dependencies, and a severe reproducibility crisis in modern research. Traditional centralized data management approaches are…
Data commons collate data with cloud computing infrastructure and commonly used software services, tools and applications to create biomedical resources for the large-scale management, analysis, harmonization, and sharing of biomedical…
In the last few years, the concept of data lake has become trendy for data storage and analysis. Thus, several design alternatives have been proposed to build data lake systems. However, these proposals are difficult to evaluate as there…
The proliferation of sensor technologies and advancements in data collection methods have enabled the accumulation of very large amounts of data. Increasingly, these datasets are considered for scientific research. However, the design of…
Recent advances in deep generative models have greatly expanded the potential to create realistic synthetic health datasets. These synthetic datasets aim to preserve the characteristics, patterns, and overall scientific conclusions derived…
Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices…
Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, non-standardized spreadsheets, or data repositories. This lack of structure challenges…
The Hybrid Technology Hub and many other research centers work in cross-functional teams whose workflow is not necessarily linear and where in many cases technology advances are done through parallel work. The lack of proper tools and…
Living labs have been established across different countries to evaluate how the interaction between humans and buildings can be optimized to improve comfort, health, and energy savings. However, existing living labs can be too…
Connected health is a multidisciplinary approach focused on health management, prioritizing pa-tient needs in the creation of tools, services, and treatments. This paradigm ensures proactive and efficient care by facilitating the timely…