Interoperable Management Research Articles

Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.

In an environment, microbes often work in communities to achieve most of their essential functions, including the production of essential nutrients. Microbial biofilms are communities of microbes that attach to a nonliving or living surface by embedding themselves into a self-secreted matrix of extracellular polymeric substances. These communities work together to enhance their colonization of surfaces, produce essential nutrients, and achieve their essential functions for growth and survival. They often consist of diverse microbes including bacteria, viruses, and fungi. Biofilms play a critical role in influencing plant phenotypes and human microbial infections. Understanding how these biofilms impact plant health, human health, and the environment is important for analyzing genotype-phenotype-driven rule-of-life functions. Such fundamental knowledge can be used to precisely control the growth of biofilms on a given surface. Metagenomics is a powerful tool for analyzing biofilm genomes through function-based gene and protein sequence identification (functional metagenomics) and sequence-based function identification (sequence metagenomics). Metagenomic sequencing enables a comprehensive sampling of all genes in all organisms present within a biofilm sample. However, the complexity of biofilm metagenomic study warrants the increasing need to follow the Findability, Accessibility, Interoperability, and Reusable (FAIR) Guiding Principles for scientific data management. This will ensure that scientific findings can be more easily validated by the research community. This study proposes a dockerized, self-learning bioinformatics workflow to increase the community adoption of metagenomics toolkits in a metagenomics and meta-transcriptomics investigation. Our biofilm metagenomics workflow self-learning module includes integrated learning resources with an interactive dockerized workflow. This module will allow learners to analyze resources that are beneficial for aggregating knowledge about biofilm marker genes, proteins, and metabolic pathways as they define the composition of specific microbial communities. Cloud and dockerized technology can allow novice learners-even those with minimal knowledge in computer science-to use complicated bioinformatics tools. Our cloud-based, dockerized workflow splits biofilm microbiome metagenomics analyses into four easy-to-follow submodules. A variety of tools are built into each submodule. As students navigate these submodules, they learn about each tool used to accomplish the task. The downstream analysis is conducted using processed data obtained from online resources or raw data processed via Nextflow pipelines. This analysis takes place within Vertex AI's Jupyter notebook instance with R and Python kernels. Subsequently, results are stored and visualized in Google Cloud storage buckets, alleviating the computational burden on local resources. The result is a comprehensive tutorial that guides bioinformaticians of any skill level through the entire workflow. It enables them to comprehend and implement the necessary processes involved in this integrated workflow from start to finish. This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

A reference architecture for personal health data spaces using decentralized content-addressable storage networks.

This paper addresses the dilemmas of accessibility, comprehensiveness, and ownership related to health data. To resolve these dilemmas, we propose and justify a novel, globally scalable reference architecture for a Personal Health Data Space (PHDS). This architecture leverages decentralized content-addressable storage (DCAS) networks, ensuring that the data subject retains complete control and ownership of their personal health data. In today's globalized world, where people are increasingly mobile for work and leisure, healthcare is transitioning from episodic symptom-based treatment toward continuity of care. The main aims of this are patient engagement, illness prevention, and active and healthy longevity. This shift, along with the secondary use of health data for societal benefit, has intensified the challenges associated with health data accessibility, comprehensiveness, and ownership. The study is structured around four health data use case scenarios from the Estonian National Health Information System (EHIS): primary medical use, medical emergency use, secondary use, and personal use. We analyze these use cases from the perspectives of accessibility, comprehensiveness, and ownership. Additionally, we examine the security, privacy, and interoperability aspects of health data. The proposed architectural solution allows individuals to consolidate all their health data into a unified Personal Health Record (PHR). This data can come from various healthcare institutions, mobile applications, medical devices for home use, and personal health notes. The comprehensive PHR can then be shared with healthcare providers in a semantically interoperable manner, regardless of their location or the information systems they use. Furthermore, individuals maintain the autonomy to share, sell, or donate their anonymous or pseudonymous health data for secondary use with different systems worldwide. The proposed reference architecture aligns with the principles of the European Health Data Space (EHDS) initiative, enhancing health data management by providing a secure, cost-effective, and sustainable solution.

A Knowledge Graph Service Composition Model for E-Government

In an era of Artificial Intelligence (AI), governments around the world are advancing their digital footprints, and using AI to achieving their objectives of effective and efficient public service delivery and citizens engagement. Knowledge Graph (KG), a constituent AI technology, has proven to be the means through which a government can use to manage the complexity of an e-Government instance, and realize its objective. One area in e-Government that KG is used to address, is the challenge of automated composition of web services, where web services are created and maintained by one government department, but is used by another, in an integrated and interoperable manner. Service composition is the combination of two or more web services to create a composite service in order to accomplish a task. In this paper, we present a KG-based approach for automatically composing web services in an e-Government context. Our aim is to advance the e-Government objective of effective and efficient public service delivery and citizens engagement, given a complex e-Government. We focus on creating a Service Dependency Graph (SDG), which captures the semantic relationships between the services, and we further describe the services with QoS characteristics, and then we create a weighted graph based on these two descriptions. We then adapted the Uniform Cost Search algorithm to find the shortest path between a start node and a goal node. We implement our algorithm, and carried-out experiments to obtain execution times, and we compared our results with benchmark results of comparable experimental setup. The difference in execution times of the service composition task is dependent on factors such as the design of the composition model, the complexity of the composition graph, and the hardware and software environments. Our research approach affords us the means to analyze and design our model; and validate and evaluate our work. Our model and the development approach help to achieve the e-Government goals of efficient and effective service delivery and citizens engagement.

Nuclear-Conventional Entanglement in Northeast Asia: The Case for Crisis Management Interoperability

ABSTRACT The dangers associated with the entanglement of nuclear and conventional forces have become an area of increasing concern. In this article, I survey the growing nuclear-conventional entanglement risks in Northeast Asia as well as the ways in which entanglement is driving a new era of nuclear arms racing in response. In order to better manage the risks of nuclear crises occurring, I outline the need for a greater emphasis on assurance policies to match the current focus on making deterrent threats. Given the high chance of such crisis nevertheless occurring in Northeast Asia in the years ahead, I make the case for developing what I call “crisis management interoperability” between allies armed with nuclear and strategic non-nuclear weapons. Such interoperability is aimed at ensuring that the difficult task of crisis signalling is not further complicated by alliances with entangled nuclear and conventional forces.

Development of Interoperability Principles for Disaster and Emergency Management System of Türkiye

Due to their complex nature, disasters and emergencies require a data-intensive management system in which many actors from different sectors participate and simultaneous processes are managed. Due to this complexity, there are problems in managing and sharing process services and geographic data effectively. The key to solving these problems is the introduction of a complete interoperability model. In this context, interoperability models based on existing international standards are analyzed in this study. FEI and EIF models are taken as basis in terms of disaster and emergency management interoperability requirements. Accordingly, the interoperability reference model was created in legal, organizational, semantic and technical frameworks to meet the interoperability levels. This general framework model has been evaluated in the service and data layers that need to be fully defined in disaster and emergency management phases, and a basic model including interoperability solutions for the service and data model has been created.

A hackathon as a tool to enhance research and practice on electronic health record systems' interoperability for chronic disease management and prevention.

The development of a standardized technical framework for exchanging electronic health records is widely recognized as a challenging endeavor that necessitates appropriate technological, semantic, organizational, and legal interventions to support the continuity of health and care. In this context, this study delineates a pan-European hackathon aimed at evaluating the efforts undertaken by member states of the European Union to develop a European electronic health record exchange format. This format is intended to facilitate secure cross-border healthcare and optimize service delivery to citizens, paving the way toward a unified European health data space. The hackathon was conducted within the scope of the X-eHealth project. Interested parties were initially presented with a representative clinical scenario and a set of specifications pertaining to the European electronic health record exchange format, encompassing Laboratory Results Reports, Medical Imaging and Reports, and Hospital Discharge Reports. In addition, five onboarding webinars and two professional training events were organized to support the participating entities. To ensure a minimum acceptable quality threshold, a set of inclusion criteria for participants was outlined for the interested teams. Eight teams participated in the hackathon, showcasing state-of-the-art applications. These teams utilized technologies such as Health Level Seven-Fast Healthcare Interoperability Resources (HL7 FHIR) and Clinical Document Architecture (CDA), alongside pertinent IHE integration profiles. They demonstrated a range of complementary uses and practices, contributing substantial inputs toward the development of future-proof electronic health record management systems. The execution of the hackathon demonstrated the efficacy of such approaches in uniting teams from diverse backgrounds to develop state-of-the-art applications. The outcomes produced by the event serve as proof-of-concept demonstrators for managing and preventing chronic diseases, delivering value to citizens, companies, and the research community.

A Strategic Framework for the Development, Implementation and Management of Digital Platform Ecosystems in Healthcare

Purpose: Several studies have shown that community management and platform engagements promote value co-creation in the automobile, housing, e-commerce, education and IT industries. The potential of digital technologies to support more inclusive and sustainable growth is transforming traditional business ecosystems. However, this value co-creation in digital platform ecosystems has struggled across healthcare due to the challenges associated with privacy, security and data management. By viewing healthcare as a business rather than a social intervention, this study aims to design a strategic framework supporting the development, implementation and management of digital platform ecosystems within the business environment.Design/methodology/approach: This study builds upon existing literature on value co-creation strategies, implementation initiatives, and interoperability management requirements, as well as leveraging data and insights from a survey to develop a management framework for digital platform ecosystems in healthcare.Findings: The study shows that a strategic framework provides a systematic approach to integrating multiple actors in developing, implementing and managing healthcare platform ecosystems. It also offers practical implications and recommendations for healthcare delivery and service providers.Originality/value: The researchers present an original framework based on in-depth theoretical and empirical studies of the digital platform ecosystem in healthcare. Moreover, they demonstrate the application of this framework by assessing a selected digital platform ecosystem. Keywords: digital platform ecosystems, healthcare, management, value co-creation, interoperability, actor engagement.

BAM Data Store

As a partner in several NFDI consortia, the Bundesanstalt für Materialforschung und -prüfung (BAM, German federal institute for materials science and testing) contributes to research data standardization efforts in various domains of materials science and engineering (MSE). To implement a central research data management (RDM) infrastructure that meets the requirements of MSE groups at BAM, we initiated the Data Store pilot project in 2021. The resulting infrastructure should enable researchers to digitally document research processes and store related data in a standardized and interoperable manner. As a software solution, we chose openBIS, an open-source framework that is increasingly being used for RDM in MSE communities. The pilot project was conducted for one year with five research groups across different organizational units and MSE disciplines. The main results are presented for the use case “nanoPlattform”. The group registered experimental steps and linked associated instruments and chemicals in the Data Store to ensure full traceability of data related to the synthesis of ~400 nanomaterials. The system also supported researchers in implementing RDM practices in their workflows, e.g., by automating data import and documentation and by integrating infrastructure for data analysis. Based on the promising results of the pilot phase, we will roll out the Data Store as the central RDM infrastructure of BAM starting in 2023. We further aim to develop openBIS plugins, metadata standards, and RDM workflows to contribute to the openBIS community and to foster RDM in MSE.

Platformization in the built environment: the political techno-economy of Building Information Modeling

ABSTRACT The digital transformation of architecture, engineering, and construction (AEC) is being hailed as a panacea for the sectors’ problems, with major actors in government and business promoting it as a benevolent harbinger of greater efficiency, productivity, better quality, and environmental performance. However, advancing digitalization in AEC is intertwined with a distinct political-economic logic that involves new constraints, dependencies, and a reconfiguration of power relations. Specifically, Building Information Modeling (BIM) as a digital convergence of three-dimensional building models, databases, and interfaces for multidisciplinary collaboration operates as a runway technology for digitalization and an entry point for platformization impelled by global software giants, such as this article’s empirical case of software company Autodesk and its BIM product portfolio shows. BIM’s linkage of governmental policy strategies with the techno-economic platform logic of software subscription models, open application programming interfaces, and cloud-enabled collaboration ensures management and control of construction data and software interoperability. At the same time, BIM’s techno-economic and political configuration facilitates a near-monopolistic structure in the global architecture and construction software market. It thus grants one hegemonic company immense power to define what formats, standards, and data for building models and design processes are being used in creating the built environment. The expansive, intersecting logics of assetization, platformization, and datafication have been taking hold in the AEC sector, raising questions about their stratifying effects in the built environment and society.

A framework for multi-robot control in execution of a Swarm Production System

Swarm Production Systems adopt an agile, reconfigurable and flexible production philosophy using mobile robot platforms for workstations and material transport. As a result, the factory floor can continuously restructure itself to an optimal spatial topology suited to any given production mix. This new production paradigm has to deal with frequently changing factory layouts and an execution plan for a fleet of autonomous robots in the planning stage. For every reconfiguration in the event of a change of order, the carrier and process robots require an initial task plan prior to runtime production and a reactive mechanism to adapt to uncertainties on the shop floor. An interoperable management system across the production and robotics domain called the Swarm Manager handles the task planning, allocation and scheduling for process and product transport robots. This research provides conceptualization with an abstract framework and an architecture describing methods with required functionalities for a Swarm Manager. A generic framework based on multi-agent systems addresses the explicit functional scope for individual agents inside the Swarm Manager. Based on the functional needs, a system-level architecture is proposed to explain algorithms within task planning, allocation and scheduling agents, and information flow within them.

Big data analytics in programme evaluation: Examining models for the assessment of sustainable development goals in Colombia

New paradigms for evidence-based decisions such as big data analytics (BDA) have emerged to assess programmes in sustainable development goals (SDGs). The arguments supporting the contributions of BDA in the assessment of SDGs in Colombia are mixed. This article presents a qualitative review of a list of programmes that adopted BDA and assesses whether problems such as bias and wrong impressions of programme performance can be controlled with the adoption of these methods. The results vary depending on the quality of the data and the collection method. Unfortunately, Colombia faces challenges such as data privacy management and deficiency of institutional interoperability to exploit these techniques conveniently.

System on a Package Innovations With Universal Chiplet Interconnect Express (UCIe) Interconnect

Universal Chiplet Interconnect Express (UCIe) is an open industry standard interconnect for developing an open chiplet ecosystem, where chiplets from any supplier can be packaged anywhere in an interoperable manner. This article delves into the architectural and protocol aspects that we developed and have been adopted in the UCIe 1.0 specification. We present our results on these aspects based on our implementation studies.

Urban-Level Data Interoperability for Management of Building and Civil Infrastructure Systems during the Disaster Phases Using Model View Definitions

Urban-Level Data Interoperability for Management of Building and Civil Infrastructure Systems during the Disaster Phases Using Model View Definitions

Interoperability: Our exciting and terrifying Web3 future

This article introduces the next major generational evolution of the web: Web3. We review the fundamental evolution of the internet and the web over the past 3 decades, including a brief presentation of the publications in Business Horizons that are important in a discussion of the emergence of Web3. We then discuss what these recent developments mean to organizations, consumers, and the public. Though the degree to which Web3 will be widely adopted is uncertain, these technologies are already creating both exhilarating and terrifying implications for e-commerce, digital media, online social networking, online marketplaces, search engines, supply chain management, and finance, among others. We propose the consideration and management of technical, organizational, and regulatory interoperability for Web3 to deliver on its promises of value and that failure to consider these interoperability components may destroy economic value, consumer confidence, or social issues online. We also call on our fellow researchers to focus on these interoperability issues and how they might impact the positive and negative sides of Web3 technologies to help us understand and shape our Web3 future.

Universal Chiplet Interconnect Express (UCIe): An Open Industry Standard for Innovations With Chiplets at Package Level

Universal Chiplet Interconnect Express (UCIe) is an open industry standard interconnect for developing an open chiplet ecosystem, where chiplets from any supplier can be packaged anywhere in an interoperable manner. This article delves into the architectural, circuit, channel, and packaging aspects that we developed that has been adopted in the UCIe 1.0 Specification. We present our results based on our channel and circuit implementation studies.

A semantic web approach to uplift decentralized household energy data

In a decentralized household energy system comprised of various devices such as home appliances, electric vehicles, and solar panels, end-users are able to dig deeper into the system’s details and further achieve energy sustainability if they are presented with data on the electric energy consumption and production at the granularity of the device. However, many databases in this field are siloed from other domains, including solely information pertaining to energy. This may result in the loss of information (e.g. weather) on each device’s energy use. Meanwhile, a large number of these datasets have been extensively used in computational modeling techniques such as machine learning models. While such computational approaches achieve great accuracy and performance by concentrating only on a local view of datasets, model reliability cannot be guaranteed since such models are very vulnerable to data input fluctuations when information omission is taken into account. This article tackles the data isolation issue in the field of smart energy systems by examining Semantic Web methods on top of a household energy system. We offer an ontology-based approach for managing decentralized data at the device-level resolution in a system. As a consequence, the scope of the data associated with each device may easily be expanded in an interoperable manner throughout the Web, and additional information, such as weather, can be obtained from the Web, provided that the data is organized according to W3C standards.

Pharmaceutical Serialization : A Challenge for Small Manufacturers

The purpose of this paper is to focus on the Challenges faced by Small Manufacturers due to the Serialization compliance. Pharmaceutical serialization is the process of assigning unique serial number to each saleable product pack. Each product pack contains information about product source, Global Trade Identification Number (GTIN), Batch number, Expiry date and unique serial number. Pharmaceutical serialization is not new compliance, and it was initially introduced by Turkey in 2010, and other market such as the China and South Korea. Since many years China made compulsory for all supply chain partners to record drug distribution information of individuals drugs units in a traceability system. As we are approaching to 2023, It will be final phase of 10 yearlong implementation of Drug Supply Chain Security Act (DSCSA) since compliance enacted in 2013. Verification router services (Saleable Return) is another compliance which was scheduled to enforce on 2020 but it is now push back to 2023 due to Covid-19 impact. Under 2023 DSCSA Act, manufacturers need to provide product tracing information in secure and interoperable manner electronically to distributors and wholesaler in supply chain. Wholesaler must transfer product tracing information to dispensers and pharmacy and verify saleable returns receive from supply chain stakeholders. Dispenser/Pharmacy should be able to receive Electronic Product Code Information Services (EPCIS) and product tracing information electronically and to be able to reconcile physical product unique identifier with electronic records. Finally, everyone in supply chain must be connected electronically through interoperable network which will allow regulatory bodies to track and trace the information’s. The importance of drug traceability has been increasingly emphasized and mandated by several countries across the world. The Drug Supply Chain Security Act (DSCSA) has been working on a pilot project with big pharmaceutical companies, wholesalers and distributors to design and test interoperable network to trace pharmaceutical prescribed drug electronically at package level. This will help supply chain stakeholders to verify the authenticity of drug in United States.

Abstract 2131: Curating cartography: Enabling the harmonisation, visualisation, and reuse of diverse multiplexed imaging data through the Human Tumor Atlas Network Data Coordinating Center

Abstract The Human Tumor Atlas Network (HTAN) is a National Cancer Institute (NCI) Cancer Moonshot Initiative to generate three-dimensional molecular and spatial atlases of diverse human tumors and characterize crucial transitions in cancer progression and treatment. A series of manuscripts describing an extensive array of genomics, transcriptomics, proteomics, and imaging datasets are emerging but careful curation is required to maximize the data’s utility. HTAN centers have generated data from over 30 assay types including more than a dozen imaging methods (e.g., fluorescence microscopy, metal-tagged imaging, digital pathology, spatial transcriptomics, and electron microscopy). The HTAN Data Coordinating Center (DCC) develops infrastructure and tools to ingest, curate, explore, and share these data in a findable, accessible, interoperable, and reusable (FAIR) manner. As of November 2021 the DCC had ingested over 150 TB of data, including nearly 150,000 imaging data files. HTAN metadata schemas were developed through a community-driven Request for Comments process, including schemas for raw, processed and QC-checked imaging data, segmentation masks and feature arrays. This work led to a set of Minimum Information for Highly Multiplexed Tissue Imaging (MITI) guidelines, which are complemented by detailed metadata on participants and biospecimens. The Schematic python package is used to provide a user-friendly interface for defining data-model schemas, generate (meta)data submission spreadsheets, and asset-store interfaces on various cloud platforms. Across assay types, the HTAN schema currently encompasses over 700 attributes from 35 components. The DCC manages the HTAN Data Portal, which provides community access to the atlases and enables filtering of released atlas data based on metadata fields, and pointers to data availability. To enable visualization and exploration of imaging data directly from the portal, centers can submit Minerva stories, which provide guided storytelling of multiplexed tissue images. We provide methods to automatically generate default stories with visually appropriate overlays of sequential four-channel groups. We developed Miniature to generate unsupervised and interpretable multiplexed image thumbnails to provide rapid contextual information when browsing image collections. Dimensionality reduction is used to reduce a multiplexed image pyramid to three dimensions. Pixels are recolored according to their coordinates in low-dimensional space, where Pixels with similar marker expression are assigned similar colours. Public data sharing requires careful consideration of data egress costs and de-identification of images and their metadata. The DCC is working closely with NCI Cancer Research Data Commons to ensure long term-legacy and reuse of HTAN data. Citation Format: Adam J. Taylor, Milen Nikolov, Ino de Brujin, Jeremy Muhlich, Mialy De Felice, Artem Sokolov, Denis Schapiro, Peter Sorger, Julie Bletz, Nikolaus Schultz, Vésteinn Thorsson, James Eddy, Ethan Cerami. Curating cartography: Enabling the harmonisation, visualisation, and reuse of diverse multiplexed imaging data through the Human Tumor Atlas Network Data Coordinating Center [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2131.

Supply Chain Security Act 2023 : Interoperable Data Exchange for Drug Traceability

The purpose of this paper is to focus on the requirements of the 2023 DSCSA Act. recommended by HDA. Drug Supply Chain Security Act (DSCSA) has outlined the guidelines to develop and enhance drug supply chain security act by 2023. This includes product tracing requirements that went into effect in 2015 for manufacturers, re-packagers, wholesale distributors and dispensers (primarily pharmacies) [1]. As we are approaching to 2023, It will be final phase of 10 yearlong implementation of Drug Supply Chain Security Act (DSCSA) since compliance enacted in 2013. Verification router services (Saleable Return) is another compliance which was scheduled to enforce on 2020 but it is now push back to 2023 due to Covid-19 impact. Under 2023 DSCSA Act, manufacturers need to provide product tracing information in secure and interoperable manner electronically to distributors and wholesaler in supply chain. Wholesaler must transfer product tracing information to dispensers and pharmacy and verify saleable returns receive from supply chain stakeholders. Dispenser/Pharmacy should be able to receive Electronic Product Code Information Services (EPCIS) and product tracing information electronically and to be able to reconcile physical product unique identifier with electronic records. Finally, everyone in supply chain must be connected electronically through interoperable network which will allow regulatory bodies to track and trace the information’s. DSCSA 2023 Act is very impactful regulation which also requires supply chain partners to exchange traceability information’s such as Transaction History (TH), Transaction Information (TI), and Transaction Statement (TS) electronically. Electronic product Code Information Services (EPCIS) version 1.2 will have all provisions of TH, TI, TS, and adaptation of EPCIS version 1.2 will fulfill the requirement for all stakeholders in supply chain.

As Data Flows Surge Data Infrastructure Groans

As Data Flows Surge Data Infrastructure Groans