Data-sharing Framework Research Articles

From FAIR to FAIRS: Data security by design for the global burden of animal diseases.

Solving complex global problems involving data and data analysis can require data from both the public and private sectors. The sharing of data has traditionally been restricted to open data. To facilitate the use of both open and private data, a new data-sharing framework has been constructed as an extension to the popular Findable-Accessible-Interoperable-Reusable (FAIR) framework. The "Secure by Design" approach has been taken to define the FAIRS data-sharing framework where S stands for Secure. A Cloud infrastructure architecture is proposed that would allow data brokers to implement FAIRS. This architecture is being constructed for the Global Burden of Animal Diseases (GBADs) to facilitate the sharing of livestock data.

Fine-grained Access Control Method for Blockchain Data Sharing based on Cloud Platform Big Data

Blockchain technology has the advantages of decentralization, de-trust, and non-tampering, which breaks through the limitations of traditional centralized technology, so it has gradually become the key technology of power data security storage and privacy protection. In the existing smart grid framework, the grid operator is a centralized key distribution organization, which is responsible for sending all the secret credentials, so it is easy to have a single point of failure, resulting in a large number of personal information losses. To solve the problems of inflexible access control in smart grid data-sharing framework and considering the limitation of multi-party cooperation among grid operators and efficiency, an attribute-based access control scheme supporting privacy preservation in smart grid is constructed in this paper. A fine-grained access control scheme supporting privacy protection is designed and extended to the smart grid system, which enables the system to achieve fine-grained access control of power data. A decryption test algorithm is added before the decryption algorithm. Finally, through performance analysis and comparison with other schemes, it is verified that the performance of this system is 7% higher than the traditional method, and the storage cost is 9.5% lower, which reflects the superiority of the system. Full optimization of the access policy is achieved. It is proved that the scheme is more efficient to implement the coordination and cooperation of multiple authorized agencies in the system initialization.

A Hyperledger Fabric-Based System Framework for Healthcare Data Management

This study examined the requirements for privacy-preserving and interoperability in healthcare data sharing and proposed a blockchain-based solution. The Hyperledger Fabric framework was adopted due to its enterprise-grade data processing capabilities and enhanced privacy protection functions. In addition to the Fabric’s built-in privacy-preserving functions, healthcare data-specific smart contracts with hierarchical access control were developed to strengthen privacy protection in data sharing. The proposed healthcare data-sharing framework is based on Australian medical practices with the aim to upgrade, rather than to replace, the existing data management models. The outcome of this study demonstrates the feasibility of applying blockchain technology to improve privacy-preservation while enhancing interoperability in healthcare data management.

EdgeShare: A blockchain-based edge data-sharing framework for Industrial Internet of Things

Industrial Internet of Things (IIoT) is facing significant scalability and security challenges in sharing massive device data across heterogeneous network domains. Traditional cloud-based sharing solutions for IIoT applications that are getting closer to devices are uneconomical and inefficient because of their centralized architecture. We propose a blockchain-based data-sharing framework called EdgeShare for edge data-sharing services among heterogeneous network domains by introducing a two-layer overlay network topology and an edge computing paradigm that can dramatically alleviate system pressure and reduce communication delays to improve data-sharing efficiency. Under such framework, a novel smart contract is designed to construct access control strategies with dissimilar granularities to achieve different levels of data access control in an undeniable and automated manner. All IIoT data-sharing activities are recorded in a blockchain for secured transaction logging and auditing. We implement an EdgeShare prototype and conduct extensive experiments and analyses to evaluate the feasibility of our proposals. In contrast with centralized sharing methods, results demonstrate that the proposed framework can effectively improve the reliability, efficiency, and security of massive data sharing while introducing reasonable and acceptable overheads.

3.A. Workshop: Integrating the use of genomic data in personalised healthcare: implications across the board

Abstract Genomics has the potential to benefit overall health by ensuring that citizens and patients receive timely and effective diagnosis, information, and treatment. Much progress has been made in genetic risk assessment for a wide variety of conditions, with implications for implementation of personalized medicine (PM). PM strategies include the use of decision-making processes based on biomarker-driven approaches that may have the desired discriminatory accuracy to distinguish between high-risk and low-risk subjects and may guide prevention strategies, prophylactic and therapeutic decisions. Many countries in Europe have nascent PM programmes, and human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through healthcare. However, for any healthcare system, the integration of genomic data for PM requires extensive adjustments. These adjustments include, the development of technical infrastructure, competences and ethical legal social implications frameworks, for acquiring, storing, sharing, interpreting and delivering genomic information. This workshop will discuss how the access to genomic and linked phenotypic data at population-scale has tremendous potential to effectively advance PM in healthcare systems, but to fully realise this ambition, it is crucial that a genome and health data-sharing framework is developed and can effectively reach healthcare systems in European Member States and beyond. Key messages The adoption of genomics by European healthcare systems is crucial to fulfill the potential of Personalised Medicine for patients and citizens. Effective data sharing agreements are needed, because without them the personalised healthcare approach will not work.

Considerations for an integrated population health databank in Africa: lessons from global best practices

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

Security, Privacy, and Reliability in Digital Healthcare Systems Using Blockchain

According to the security breach level index, millions of records are stolen worldwide on every single day. Personal health records are the most targeted records on the internet, and they are considered sensitive, and valuable. Security and privacy are the most important parameters of cryptography and encryption. They reduce the availability of data on patients and healthcare to the appropriate personnel and ultimately lead to a barrier in the transfer of healthcare into a digital health system. Using a permission blockchain to share healthcare data can reduce security and privacy issues. According to the literature, most healthcare systems rely on a centralized system, which is more prone to security vulnerabilities. The existing blockchain-based healthcare schemes provide only a data-sharing framework, but they lack security and privacy. To cope with these kinds of security issues, we have designed a novel security algorithm that provides security as well as privacy with much better efficiency and a lower cost. Hence, in this research, we have proposed a patient healthcare framework that provides greater security, reliability, and authentication compared to existing blockchain-based access control.

Considerations for an integrated population health databank in Africa: lessons from global best practices.

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

HDS: A Fast Hybrid Data Location Service for Hierarchical Mobile Edge Computing

The hierarchical mobile edge computing satisfies the stringent latency requirements of data access and processing for emerging edge applications. The data location service is a basic function to provide data storage and retrieval to enable these applications. However, it still lacks research of a scalable and low-latency data location service in the environment. The existing solutions, such as DNS and DHT, fail to meet the requirement of those latency-sensitive applications. Therefore, in this article, we present a low-latency hybrid data-sharing framework, HDS. The HDS divides the data location service into two parts: intra-region and inter-region. More precisely, we design a data sharing protocol called Cuckoo Summary to achieve fast data localization in intra-region. Furthermore, for the inter-region data sharing, we develop a geographic routing based scheme to achieve efficient data localization with only one overlay hop. The advantages of HDS include short response latency, low implementation overhead, and few false positives. We implement the HDS framework based on a P4 prototype. The experimental results show that, compared to the state-of-the-art solutions, our design achieves 50.21% shorter lookup paths and 92.75% fewer false positives.

GlobeChain: An Interoperable Blockchain for Global Sharing of Healthcare Data—A COVID-19 Perspective

Contagious diseases are prevalent even in the current era of advanced technology. A uniformed initiative is required to build a reliable interactive information exchange service targeting vaccination data management and other medical services. The conventional data exchange mechanism is centralized, creating many vulnerable issues such as a single point failure, data leakage, access control, etc. This article introduces a Blockchain-based medical data-sharing framework (called GlobeChain) to overcome the technical challenges to handle the outbreak records. The challenges that might arise due to the proposed Blockchain-based framework are also presented as a future direction that grabs the proposal's effectiveness.

How Do Data Bolster Pandemic Preparedness and Response? How Do We Improve Data and Systems to Be Better Prepared?

How are data driving the response for the ongoing COVID-19 pandemic? How do data support preparedness toward epidemics and pandemics? How do data inform the potential severity and spread of an outbreak? Past infectious disease outbreaks have demonstrated several challenges associated with rapid aggregation, integration, and sharing of data to inform a response during an outbreak. The ongoing pandemic response has demonstrated the value of timely data collection and sharing and the usage of data for decision-making.

Privacy Protection for Medical Data Sharing in Smart Healthcare

In virtue of advances in smart networks and the cloud computing paradigm, smart healthcare is transforming. However, there are still challenges, such as storing sensitive data in untrusted and controlled infrastructure and ensuring the secure transmission of medical data, among others. The rapid development of watermarking provides opportunities for smart healthcare. In this article, we propose a new data-sharing framework and a data access control mechanism. The applications are submitted by the doctors, and the data is processed in the medical data center of the hospital, stored in semi-trusted servers to support the selective sharing of electronic medical records from different medical institutions between different doctors. Our approach ensures that privacy concerns are taken into account when processing requests for access to patients’ medical information. For accountability, after data is modified or leaked, both patients and doctors must add digital watermarks associated with their identification when uploading data. Extensive analytical and experimental results are presented that show the security and efficiency of our proposed scheme.

Towards a European Health Data Ecosystem

The digital health ecosystem is rife with opportunities to improve healthcare through data-driven services in the European Union (EU). The value of health data, in the multiple forms in which they come (from health records to lifestyle data collected by smartphones or wearables), can truly emerge when they are allowed to flow in the ecosystem within a governance framework supported by all relevant stakeholders, with trust as the common and clear thread underpinning it. The coronavirus pandemic has provided an additional impetus for change, showing the importance of coordination and adequate communication between Member States and quality data to inform decision-making. Significant challenges remain, however, in order to achieve a fully integrated European digital health ecosystem, including: (1) the potentially diverging rules set by Member States at the national level and the need for an EU framework for the secondary use of health data; (2) the need for transparency and accountability for sustaining a data-sharing framework involving public authorities, research organisations, industry and citizens; and (3) the need for interoperable data and processes. Taking stock of these challenges, this article puts forward policy recommendations to enable the provision of pan-European data-driven healthcare services and to build a transparent and trustworthy framework for citizens.

A secure and efficient data sharing scheme based on blockchain in industrial Internet of Things

Blockchain possesses potential for enabling secure data sharing of industrial big data generated by the Industrial Internet of Things (IIoT). However, the existing data-sharing schemes based on blockchain secure only the data exchange process between the data-sharing parties; they do not consider the efficiency of data sharing at all. In this study, we propose a data-sharing scheme based on blockchain that comprehensively considers the security and efficiency of data sharing. In this scheme, a secure data-sharing framework is designed based on identity authentication and Hyperledger Fabric to ensure the security of data sharing. We also propose a community detection algorithm to divide the clients into different data-sharing communities according to the similarity of label data. The scope of data sharing is selected according to the results of the community detection evaluated by the sharing degree, which can effectively narrow the scope of query-shared data and improve the efficiency of data sharing. The experimental results show that the proposed scheme is effective for secure and efficient data sharing among different clients.

Secure Online/Offline Data Sharing Framework for Cloud-Assisted Industrial Internet of Things

Ciphertext-policy attribute-based keyword search (CP-ABKS) schemes facilitate the fine-grained keyword search over encrypted data, such as those sensed/collected from Industrial Internet of Things (IIoT) devices and stored in the cloud. However, existing CP-ABKS schemes generally have significant computation and storage requirements, which are beyond those of resource-constrained IIoT devices. Therefore, in this paper, we design a secure online/offline data sharing framework (DSF), which supports online/offline encryption and outsourced decryption. Using the healthcare setting as a case study, we demonstrate how DSF can be deployed in the cloud-assisted Healthcare IIoT (HealthIIoT) system. We not only prove that the DSF is selectively secure in the chosen access structure security model but also demonstrate its efficiency and feasibility in practical scenarios using experiments.

Japan\u2019s initiative on rare and undiagnosed diseases (IRUD): towards an end to the diagnostic odyssey

Japan has been facing challenges relating to specifically defined rare diseases, called Nan-Byo in Japanese (literally ‘difficult’+‘illness’), and has already taken measures for them since 1972. This governmental support has surely benefited Nan-Byo patients; however, those suffering from medically unidentified conditions do not fall into this scheme and thus still confront difficulty in obtaining an examination, a diagnosis, and a treatment. To identify such rare and often undiagnosed diseases, we must integrate systematic diagnosis by medical experts with phenotypic and genetic data matching. Thus, in collaboration with Nan-Byo researchers and the Japanese universal healthcare system, the Japan Agency for Medical Research and Development launched the Initiative on Rare and Undiagnosed Diseases (IRUD) in 2015. IRUD is an ambitious challenge to construct a comprehensive medical network and an internationally compatible data-sharing framework. Synergizing with existing next-generation sequencing capabilities and other infrastructure, the nationwide medical research consortium has successfully grown to accept more than 2000 undiagnosed registrants by December 2016. We also aim at expanding the concept of microattribution throughout the initiative; that is, proper credit as collaborators shall be given to local primary care physicians, nurses and paramedics, patients, their family members, and those supporting the affected individuals whenever appropriate. As it shares many challenges among similar global efforts, IRUD’s future successes and lessons learned will significantly contribute to ongoing international endeavors, involving players in basic research, applied research, and societal implementation.

Guest Editorial: Assessing the Processes, Tools, and Value of Sharing and Learning From Offshore E&P Safety-Related Data

Guest editorial In 2014, the US Department of the Interior’s Bureau of Safety and Environmental Enforcement (BSEE) approached SPE regarding a proposed collaboration opportunity to develop a voluntary industrywide near-miss data-sharing framework. The goal of this framework was envisioned as a resource to enhance the industry’s ability to capture and share key learnings from significant near-miss events with the objective of identifying and mitigating potential high-consequence risks. While the scope of this collaboration initially focused on only near misses, further discussion of the desired outcome resulted in increasing the scope to include a broader range of data that have learning value to help the industry to achieve improved safety performance. Further, in the spirit of continuous improvement, a related objective was identified to bring government and industry together to make a safe industry safer, and to enhance public confidence in the industry. SPE and BSEE agreed to cochair a summit steering committee that included representatives from SPE, BSEE, exploration and production (E&P) operators, service companies, the US Bureau of Transportation Statistics, the Center for Offshore Safety, American Bureau of Shipping, and the International Association of Oil and Gas Producers. During the planning process of the summit, it was agreed that the scope of a data collection and reporting framework would start with the US Outer Continental Shelf (OCS). Additionally, a secondary objective was to consider how existing processes might be leveraged with an overarching objective to extend influence beyond the US OCS to align with other systems and requirements globally. In considering industry alternatives for developing a safety-data management framework, caution was advised to avoid creating an additional layer of reporting expectations over and above the current requirements by regulators and industry associations. During the summit, Vice Admiral Brian Salerno, the director of BSEE, shared his perspective on the importance of industrywide safety-data collection and sharing. He also encouraged the E&P industry to demonstrate to the public how a safe industry could be made safer through more open data sharing.

Data Sharing of Transport Research Data

With the rapid progress of the development of intelligent transport systems over the last 15 years, the need for testing them in the real world and collecting data about their impact became more and more important. We have seen a fast growth in the number of Field Operational Tests (FOT) and Naturalistic Driving Studies (NDS) performed worldwide. The need to better understand the benefits of safety systems and the factors behind the occurrence of incidents and accidents have been a main driving force and the data has therefore been collected through naturalistic driving by volunteer drivers. As the number of different datasets has increased and so also the awareness of the substantial effort and funding needed to run these FOT/NDS, the interest in data sharing has increased worldwide.The availability of a common Data Sharing Framework (DSF) could highly facilitate a larger use of the collected FOT/NDS data. The FOT-Net Data project has developed such a framework, in collaboration with a variety of stakeholders from Europe, the US, Japan and other countries. The seven topics addressed by the DSF are (1) project agreements, (2) data and metadata descriptions, (3) data protection, (4) training, (5) support and research services, (6) financial models and (7) applications procedures. Many of the topics are general and can be used for other types of transport research data as well.There remain challenges to make data sharing possible on a global scale. Some of these are: the project funding schemes, leading to multiple schemas of ownerships of data, and the legal settings in different countries. On a technical level, the documentation of datasets and of the metadata describing the test is not always sufficient. Furthermore, new projects need to be made aware of the importance of inserting the pre-requisites for data sharing into the different project agreements right from the start.This paper describes the content of the DSF with its hands-on recommendations on how to prepare for and perform data sharing of transport research data. It also presents the status of a use case, implementing the DSF into the European project UDRIVE.

PDVLoc

Location-Based Mobile Service (LBMS) is one of the most popular smartphone services. LBMS enables people to more easily connect with each other and analyze the aspects of their lives. However, sharing location data can leak people's privacy. We present PDVLoc, a controlled location data-sharing framework based on selectively sharing data through a Personal Data Vault (PDV). A PDV is a privacy architecture in which individuals retain ownership of their data. Data are routinely filtered before being shared with content-service providers, and users or data custodian services can participate in making controlled data-sharing decisions. Introducing PDVLoc gives users flexible and granular access control over their location data. We have implemented a prototype of PDVLoc and evaluated it using real location-sharing social networking applications, Google Latitude and Foursquare. Our user study of 19 participants over 20 days shows that most users find that PDVLoc is useful to manage and control their location data, and are willing to continue using PDVLoc.

Using GIS servers and interactive maps in spectral data sharing and administration: Case study of Ahvaz Spectral Geodatabase Platform (ASGP)

With emergence of air-borne and space-borne hyperspectral sensors, spectroscopic measurements are gaining more importance in remote sensing. Therefore, the number of available spectral reference data is constantly increasing. This rapid increase often exhibits a poor data management, which leads to ultimate isolation of data on disk storages. Spectral data without precise description of the target, methods, environment, and sampling geometry cannot be used by other researchers. Moreover, existing spectral data (in case it accompanied with good documentation) become virtually invisible or unreachable for researchers. Providing documentation and a data-sharing framework for spectral data, in which researchers are able to search for or share spectral data and documentation, would definitely improve the data lifetime. Relational Database Management Systems (RDBMS) are main candidates for spectral data management and their efficiency is proven by many studies and applications to date. In this study, a new approach to spectral data administration is presented based on spatial identity of spectral samples. This method benefits from scalability and performance of RDBMS for storage of spectral data, but uses GIS servers to provide users with interactive maps as an interface to the system. The spectral files, photographs and descriptive data are considered as belongings of a geospatial object. A spectral processing unit is responsible for evaluation of metadata quality and performing routine spectral processing tasks for newly-added data. As a result, by using internet browser software the users would be able to visually examine availability of data and/or search for data based on descriptive attributes associated to it. The proposed system is scalable and besides giving the users good sense of what data are available in the database, it facilitates participation of spectral reference data in producing geoinformation.