Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study

Background There is a growing need for the integration of patient-generated health data (PGHD) into research and clinical care to enable personalized, preventive, and interactive care, but technical and organizational challenges, such as the lack of standards and easy-to-use tools, preclude the effective use of PGHD generated from consumer devices, such as smartphones and wearables. Objective This study outlines how we used mobile apps and semantic web standards such as HTTP 2.0, Representational State Transfer, JSON (JavaScript Object Notation), JSON Schema, Transport Layer Security (version 1.3), Advanced Encryption Standard-256, OpenAPI, HTML5, and Vega, in conjunction with patient and provider feedback to completely update a previous version of mindLAMP. Methods The Learn, Assess, Manage, and Prevent (LAMP) platform addresses the abovementioned challenges in enhancing clinical insight by supporting research, data analysis, and implementation efforts around PGHD as an open-source solution with freely accessible and shared code. Results With a simplified programming interface and novel data representation that captures additional metadata, the LAMP platform enables interoperability with existing Fast Healthcare Interoperability Resources–based health care systems as well as consumer wearables and services such as Apple HealthKit and Google Fit. The companion Cortex data analysis and machine learning toolkit offer robust support for artificial intelligence, behavioral feature extraction, interactive visualizations, and high-performance data processing through parallelization and vectorization techniques. Conclusions The LAMP platform incorporates feedback from patients and clinicians alongside a standards-based approach to address these needs and functions across a wide range of use cases through its customizable and flexible components. These range from simple survey-based research to international consortiums capturing multimodal data to simple delivery of mindfulness exercises through personalized, just-in-time adaptive interventions.

ATON: An Open-Source Framework for Creating Immersive, Collaborative and Liquid Web-Apps for Cultural Heritage

The web and its recent advancements represent a great opportunity to build universal, rich, multi-user and immersive Web3D/WebXR applications targeting Cultural Heritage field—including 3D presenters, inspection tools, applied VR games, collaborative teaching tools and much more. Such opportunity although, introduces additional challenges besides common issues and limitations typically encountered in this context. The “ideal” Web3D application should be able to reach every device, automatically adapting its interface, rendering and interaction models—resulting in a single, liquid product that can be consumed on mobile devices, PCs, Museum kiosks and immersive AR/VR devices, without any installation required for final users. The open-source ATON framework is the result of research and development activities carried out during the last 5 years through national and international projects: it is designed around modern and robust web standards, open specifications and large open-source ecosystems. This paper describes the framework architecture and its components, assessed and validated through different case studies. ATON offers institutions, researchers, professionals a scalable, flexible and modular solution to craft and deploy liquid web-applications, providing novel and advanced features targeting Cultural Heritage field in terms of 3D presentation, annotation, immersive interaction and real-time collaboration.

GeoSPARQL 1.1: An Almost Decadal Update to the Most Important Geospatial LOD Standard

In 2012 the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document & exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. In this paper, we describe motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use.

RCX – an R package adapting the Cytoscape Exchange format for biological networks

Motivation: The Cytoscape Exchange (CX) format is a JSON-based data structure designed for the transmission of biological networks using standard web technologies. It was developed by the network data exchange (NDEx), which itself serves as online commons to share and collaborate on biological networks. The Cytoscape software for the analysis and visualization of biological networks contributes further elements to capture the visual layout within the CX format. However, there is a fundamental difference between web standards and R of how data has to be structured. Results: Here we present a software package to create, handle, validate, visualize and convert networks in CX format to standard data types and objects within R. Networks in this format can serve as a source for biological knowledge, and also capture the results of the analysis of those while preserving the visual layout across all platforms. The RCX package connects the R environment for statistical computing with platforms for collaboration, analysis and visualization of biological networks. Availability: RCX is a free and open-source R package, available via GitHub (https://github.com/frankkramer-lab/RCX) and submitted to Bioconductor.

ContSOnto: A Formal Ontology for Continuity of Care

The global pandemic over the past two years has reset societal agendas by identifying both strengths and weaknesses across all sectors. Focusing in particular on global health delivery, the ability of health care facilities to scale requirements and to meet service demands has detected the need for some national services and organisations to modernise their organisational processes and infrastructures. Core to requirements for modernisation is infrastructure to share information, specifically structural standardised approaches for both operational procedures and terminology services. Problems of data sharing (aka interoperability) is a main obstacle when patients are moving across healthcare facilities or travelling across border countries in cases where emergency treatment is needed. Experts in healthcare service delivery suggest that the best possible way to manage individual care is at home, using remote patient monitoring which ultimately reduces cost burden both for the citizen and service provider. Core to this practice will be advancing digitalisation of health care underpinned with safe integration and access to relevant and timely information. To tackle the data interoperability issue and provide a quality driven continuous flow of information from different health care information systems semantic terminology needs to be provided intact. In this paper we propose and present ContSonto a formal ontology for continuity of care based on ISO 13940:2015 ContSy and W3C Semantic Web Standards Language OWL (Web Ontology Language). ContSonto has several benefits including semantic interoperability, data harmonization and data linking. It can be use as a base model for data integration for different healthcare information models to generate knowledge graph to support shared care and decision making.

Optimizing RDF Stream Processing for Uncertainty Management

RDF Stream Processing (RSP) has been proposed as a way of bridging the gap between the Complex Event Processing (CEP) paradigm and the Semantic Web standards. Uncertainty has been recognized as a critical aspect in CEP, but it has received little attention within the context of RSP. In this paper, we investigate the impact of different RSP optimization strategies for uncertainty management. The paper describes (1) an extension of the RSP-QL⋆ data model to capture bind expressions, filter expressions, and uncertainty functions; (2) optimization techniques related to lazy variables and caching of uncertainty functions, and a heuristic for reordering uncertainty filters in query plans; and (3) an evaluation of these strategies in a prototype implementation. The results show that using a lazy variable mechanism for uncertainty functions can improve query execution performance by orders of magnitude while introducing negligible overhead. The results also show that caching uncertainty function results can improve performance under most conditions, but that maintaining this cache can potentially add overhead to the overall query execution process. Finally, the effect of the proposed heuristic on query execution performance was shown to depend on multiple factors, including the selectivity of uncertainty filters, the size of intermediate results, and the cost associated with the evaluation of the uncertainty functions.

The strongest link: libraries and linked data

Since 1999 the W3C has been working on a set of Semantic Web standards that have the potential to revolutionize web search. Also known as Linked Data, the Machine‐Readable Web, the Web of Data, or Web3.0, the Semantic Web relies on highly structured metadata that allow computers to understand the relationships between objects. Semantic web standards are complex, and difficult to conceptualize, but they offer solutions to many of the issues that plague libraries, including precise web search, authority control, classification, data portability, and disambiguation. This article will outline some of the benefits that linked data could have for libraries, will discuss some of the non‐technical obstacles that we face in moving forward, and will finally offer suggestions for practical ways in which libraries can participate in the development of the semantic web.

Semantic Representation of Domain Knowledge for Professional VR Training

Domain-specific knowledge representation is an essential element of efficient management of professional training. Formal and powerful knowledge representation for training systems can be built upon the semantic web standards, which enable reasoning and complex queries against the content. Virtual reality training is currently used in multiple domains, in particular, if the activities are potentially dangerous for the trainees or require advanced skills or expensive equipment. However, the available methods and tools for creating VR training systems do not use knowledge representation. Therefore, creation, modification and management of training scenarios is problematic for domain experts without expertise in programming and computer graphics. In this paper, we propose an approach to creating semantic virtual training scenarios, in which users’ activities, mistakes as well as equipment and its possible errors are represented using domain knowledge understandable to domain experts. We have verified the approach by developing a user-friendly editor of VR training scenarios for electrical operators of high-voltage installations.