This poster was presented at the 2019 NIH NCI Childhood Cancer Data Initiative (CCDI) Symposium by Brigitte Raumann and Ian Foster of Globus, University of Chicago and Argonne National Lab.
Curoverse Presentation at ICG-11 (November 2016)Arvados
Huge genomic datasets are being created all around the world, and their scale is accelerating. But these data gain greater meaning when analyzed in concert with other datasets stored in institutions around the world. Due to data residency restrictions, regulatory barriers, and sheer data volume, it is impossible to effectively centralize all of these data in one place. In order to achieve regional and global use of many data sets in concert, we must overcome these challenges with a new approach to managing, analyzing and sharing sequencing data: Federated Computing.
Federated Computing is difficult from a technical perspective because of the variety of IT infrastructures and workflow engines available, which makes reproducibility across environments nearly impossible, and from a practical perspective because of privacy and competitive concerns among researchers. Federated Computing becomes easier with a scalable, open source, multi-platform, standards-based biomedical big data computing platform that can be deployed in public cloud, private cloud, and HPC environments, and enables bit-for-bit reproducibility of analyses across every deployment.
We present Arvados (http://arvados.org), a free and open source platform for managing and processing biomedical data designed for scale, reproducibility, and federation. Workflows and queries can travel across multiple Arvados clusters, running exactly the same way on each one, regardless of the underlying compute & storage infrastructure.
The document proposes a framework for securely sharing personal health records (PHRs) stored in the cloud using attribute-based encryption (ABE). It aims to achieve fine-grained access control over PHRs while addressing challenges like privacy risks, complex key management, and user revocation. The framework divides users into multiple security domains to reduce complexity and uses multi-authority ABE to guarantee patient privacy. Access policies and file attributes can also be dynamically modified. Experimental results demonstrate the security, scalability and efficiency of the proposed scheme.
A FAIR Data Sharing Framework for Large-Scale Human Cancer ProteogenomicsBrett Tully
A FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
Islam M1,2, Christiansen J3, Mahboob S4, Valova V4, Baker M4, Capes-Davis D4, Hains P4, Balleine R1,4, Zhong Q1,4, Reddel R1,4, Robinson P1,4, Tully B4
1 The University of Sydney, Camperdown, Sydney, NSW, 2050, Australia
2 Intersect, Level 13/50 Carrington St, Sydney, NSW, 2000, Australia
3 Queensland Cyber Infrastructure Foundation Ltd, Axon Building 47, University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
4 Children’s Medical Research Institute, Westmead, NSW, 2145, Australia
Background
The ACRF International Centre for the Proteome of Cancer (ProCan) at Children’s Medical Research Institute (CMRI) is an “industrial scale” program specialising in small-sample proteomics analysis from human cancer tissue.
ProCan seeks to generate both a wide and deep analytics pipeline and requires an enabling data framework. The framework must accommodate initial analysis and proteomic profiling of a large number of tumor samples, along with the clinical and demographic information, subsequent multi-omics studies, and any previously recorded responses to treatment. The curated datasets will provide a valuable resource beyond their primary use and ProCan is committed to making its data accessible to collaborators and the wider scientific community.
Objectives
The objective of the project is to an establish efficient, reliable, secure and ethical data sharing and publication framework based on the best practice data sharing principles, such as the FAIR principle. The framework must address various challenges that stem from the scale and complexity of the program, and ProCan’s focus on human-derived data and associated challenges presented in sharing these data while maintaining the privacy of any research participants.
Method
The project adopted a requirements-driven methodology and engaged with a wide range of ProCan stakeholders nationally and internationally. Together, various industrial-scale proteomics data management and sharing scenarios were explored such that robust and ethical sharing of the data would be achieved.
Results
The project developed a data sharing framework based on the FAIR principle that currently forms the basis of ongoing implementation work within the ProCan program.
secured storage of Personal health record in cloudeMahaveer kandgule
This document proposes a framework for securely storing personal health records (PHRs) in the cloud. It aims to achieve fine-grained access control and protect privacy. The framework uses attribute-based encryption to encrypt each patient's PHR file under access policies. This allows patients to selectively share records with users based on their attributes without knowing a full user list. It also divides the system into public and personal domains for different user access needs. Analytical and experimental results show the framework provides data confidentiality, revocation of access rights, write access control, and scalability.
Scalable and secure sharing of personal health
records in cloud computing us...Duraiyarasan S
This document proposes a framework for fine-grained access control of personal health records (PHRs) stored in cloud computing environments. It aims to give patients full control over their PHR data while reducing the key management complexity in multi-owner settings. The framework uses attribute-based encryption to encrypt each patient's PHR data according to access policies. It divides the system into multiple security domains to distribute key management responsibilities and reduce overhead for each owner and user.
This document proposes a cloud-based architecture for wireless sensor networks used in e-health applications. It discusses three key components: 1) a wireless sensor network that collects patient health data, 2) monitoring applications for healthcare professionals to access stored data, and 3) a Healthcare Authority that specifies security policies. It then proposes using attribute-based encryption and symmetric encryption to encrypt health data and implement access control policies while outsourcing storage to the cloud. Performance analysis shows the proposed approach reduces overhead compared to solely using attribute-based encryption.
Scalable and secure sharing of public health record using attribute based Enc...shreyank byadagi
This document proposes using attribute-based encryption techniques to securely share personal health records in cloud computing. The objectives are to provide secure patient-centric access to personal health records while efficiently managing access keys. The proposed system encrypts patient health records before outsourcing them to the cloud using attribute-based encryption to guarantee privacy. This addresses challenges with unauthorized access and enables flexible yet secure data access control.
Curoverse Presentation at ICG-11 (November 2016)Arvados
Huge genomic datasets are being created all around the world, and their scale is accelerating. But these data gain greater meaning when analyzed in concert with other datasets stored in institutions around the world. Due to data residency restrictions, regulatory barriers, and sheer data volume, it is impossible to effectively centralize all of these data in one place. In order to achieve regional and global use of many data sets in concert, we must overcome these challenges with a new approach to managing, analyzing and sharing sequencing data: Federated Computing.
Federated Computing is difficult from a technical perspective because of the variety of IT infrastructures and workflow engines available, which makes reproducibility across environments nearly impossible, and from a practical perspective because of privacy and competitive concerns among researchers. Federated Computing becomes easier with a scalable, open source, multi-platform, standards-based biomedical big data computing platform that can be deployed in public cloud, private cloud, and HPC environments, and enables bit-for-bit reproducibility of analyses across every deployment.
We present Arvados (http://arvados.org), a free and open source platform for managing and processing biomedical data designed for scale, reproducibility, and federation. Workflows and queries can travel across multiple Arvados clusters, running exactly the same way on each one, regardless of the underlying compute & storage infrastructure.
The document proposes a framework for securely sharing personal health records (PHRs) stored in the cloud using attribute-based encryption (ABE). It aims to achieve fine-grained access control over PHRs while addressing challenges like privacy risks, complex key management, and user revocation. The framework divides users into multiple security domains to reduce complexity and uses multi-authority ABE to guarantee patient privacy. Access policies and file attributes can also be dynamically modified. Experimental results demonstrate the security, scalability and efficiency of the proposed scheme.
A FAIR Data Sharing Framework for Large-Scale Human Cancer ProteogenomicsBrett Tully
A FAIR Data Sharing Framework for Large-Scale Human Cancer Proteogenomics
Islam M1,2, Christiansen J3, Mahboob S4, Valova V4, Baker M4, Capes-Davis D4, Hains P4, Balleine R1,4, Zhong Q1,4, Reddel R1,4, Robinson P1,4, Tully B4
1 The University of Sydney, Camperdown, Sydney, NSW, 2050, Australia
2 Intersect, Level 13/50 Carrington St, Sydney, NSW, 2000, Australia
3 Queensland Cyber Infrastructure Foundation Ltd, Axon Building 47, University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
4 Children’s Medical Research Institute, Westmead, NSW, 2145, Australia
Background
The ACRF International Centre for the Proteome of Cancer (ProCan) at Children’s Medical Research Institute (CMRI) is an “industrial scale” program specialising in small-sample proteomics analysis from human cancer tissue.
ProCan seeks to generate both a wide and deep analytics pipeline and requires an enabling data framework. The framework must accommodate initial analysis and proteomic profiling of a large number of tumor samples, along with the clinical and demographic information, subsequent multi-omics studies, and any previously recorded responses to treatment. The curated datasets will provide a valuable resource beyond their primary use and ProCan is committed to making its data accessible to collaborators and the wider scientific community.
Objectives
The objective of the project is to an establish efficient, reliable, secure and ethical data sharing and publication framework based on the best practice data sharing principles, such as the FAIR principle. The framework must address various challenges that stem from the scale and complexity of the program, and ProCan’s focus on human-derived data and associated challenges presented in sharing these data while maintaining the privacy of any research participants.
Method
The project adopted a requirements-driven methodology and engaged with a wide range of ProCan stakeholders nationally and internationally. Together, various industrial-scale proteomics data management and sharing scenarios were explored such that robust and ethical sharing of the data would be achieved.
Results
The project developed a data sharing framework based on the FAIR principle that currently forms the basis of ongoing implementation work within the ProCan program.
secured storage of Personal health record in cloudeMahaveer kandgule
This document proposes a framework for securely storing personal health records (PHRs) in the cloud. It aims to achieve fine-grained access control and protect privacy. The framework uses attribute-based encryption to encrypt each patient's PHR file under access policies. This allows patients to selectively share records with users based on their attributes without knowing a full user list. It also divides the system into public and personal domains for different user access needs. Analytical and experimental results show the framework provides data confidentiality, revocation of access rights, write access control, and scalability.
Scalable and secure sharing of personal health
records in cloud computing us...Duraiyarasan S
This document proposes a framework for fine-grained access control of personal health records (PHRs) stored in cloud computing environments. It aims to give patients full control over their PHR data while reducing the key management complexity in multi-owner settings. The framework uses attribute-based encryption to encrypt each patient's PHR data according to access policies. It divides the system into multiple security domains to distribute key management responsibilities and reduce overhead for each owner and user.
This document proposes a cloud-based architecture for wireless sensor networks used in e-health applications. It discusses three key components: 1) a wireless sensor network that collects patient health data, 2) monitoring applications for healthcare professionals to access stored data, and 3) a Healthcare Authority that specifies security policies. It then proposes using attribute-based encryption and symmetric encryption to encrypt health data and implement access control policies while outsourcing storage to the cloud. Performance analysis shows the proposed approach reduces overhead compared to solely using attribute-based encryption.
Scalable and secure sharing of public health record using attribute based Enc...shreyank byadagi
This document proposes using attribute-based encryption techniques to securely share personal health records in cloud computing. The objectives are to provide secure patient-centric access to personal health records while efficiently managing access keys. The proposed system encrypts patient health records before outsourcing them to the cloud using attribute-based encryption to guarantee privacy. This addresses challenges with unauthorized access and enables flexible yet secure data access control.
The document discusses sharing research data through open data platforms. It describes the CGIAR as uniquely positioned to collect agricultural data worldwide and argues that most CGIAR data should be archived and shared to increase its value. However, data archiving across CGIAR centers is currently poor. The document then discusses using the Dataverse platform to improve data sharing. Dataverse allows researchers to publish, share, cite, and analyze data. It also facilitates making data available while giving credit to data authors and institutions.
The document describes the eTRIKS Data Harmonization Service Platform, which aims to provide a common infrastructure and services to support cross-institutional translational research. It discusses challenges around data integration and harmonization. The platform utilizes standards and controlled vocabularies to syntactically and semantically harmonize data from various sources. It employs a metadata framework and modular workflow to structure, standardize, and integrate observational data into a harmonized repository for exploration and analysis. A demo of the platform's capabilities for project setup, data staging, exploration, export, and integration with tranSMART is also provided.
This document describes a proposed system for scalable and secure sharing of personal health records in cloud computing using attribute-based encryption. The system aims to address security issues with existing personal health record systems, such as privacy risks, scalability of key management, access control and user revocation. The proposed system uses attribute-based encryption to encrypt personal health records and a novel patient-centric framework with access control mechanisms. It allows for multiple data owners, dynamic access policies, and on-demand revocation of user access. The system is intended to be scalable, secure and efficient while ensuring patient control over personal health information.
Scalable and secure sharing of personal health recordscolourswathi
This document outlines a proposed system to securely store personal and medical information of patients online using attribute-based encryption. The existing system of storing this information in physical files has disadvantages like unauthorized access and high costs. The proposed system would encrypt the information using each user's unique attributes and only allow access by users with matching attributes, addressing issues of the existing system while providing universal access through the cloud at a lower cost.
Data repositories -- Xiamen University 2012 06-08Jian Qin
The document discusses data repositories and services. It begins by defining what a data repository is, noting that it is a logical and sometimes physical partitioning of data where multiple databases reside. It then outlines some key aspects of data repositories, including technical features like standards, software, and staffing requirements. The document also discusses functions of repositories like content management, archiving, dissemination and system maintenance. It provides examples of institutional repositories and data repositories, highlighting characteristics of each. Finally, it provides a case study on Dryad, an international repository for data and publications in biosciences.
The DataTags System: Sharing Sensitive Data with ConfidenceMerce Crosas
This talk was part of a session at the Research Data Alliance (RDA) 8th Plenary on Privacy Implications of Research Data Sets, during International Data Week 2016:
https://rd-alliance.org/rda-8th-plenary-joint-meeting-ig-domain-repositories-wg-rdaniso-privacy-implications-research-data
Slides in Merce Crosas site:
http://scholar.harvard.edu/mercecrosas/presentations/datatags-system-sharing-sensitive-data-confidence
Psdot 4 scalable and secure sharing of personal health records in cloud compu...ZTech Proje
FINAL YEAR IEEE PROJECTS,
EMBEDDED SYSTEMS PROJECTS,
ENGINEERING PROJECTS,
MCA PROJECTS,
ROBOTICS PROJECTS,
ARM PIC BASED PROJECTS, MICRO CONTROLLER PROJECTS
This document discusses several challenges related to managing and sharing genomic and biomedical data. It identifies key issues such as data annotation, analysis, storage, sharing, long-term planning, funding, and making data available in public repositories. It also discusses the importance of metadata, using ontologies and standards, developing data sharing policies that meet funder and journal requirements, and ensuring data is processed ethically and securely in accordance with privacy regulations.
Building Protected Data Sharing Networks to Advance Cancer Risk Assessment an...Mary Bass
This document discusses using the Globus data management platform to build protected data sharing networks that advance cancer risk assessment and treatment. It describes how Globus can securely manage and share data from instruments and analysis between personal resources, national resources, public clouds, and collaborators. It also allows publishing data for discoverability and establishes automated workflows for cancer research consortiums to leverage high-performance networks and cloud infrastructure.
FAIR Data Management and FAIR Data SharingMerce Crosas
Presentation at the Critical Perspective on the Practice of Digiral Archeology symposium: http://archaeology.harvard.edu/critical-perspectives-practice-digital-archaeology
Data Publishing at Harvard's Research Data Access SymposiumMerce Crosas
Data Publishing: The research community needs reliable, standard ways to make the data produced by scientific research available to the community, while giving credit to data authors. As a result, a new form of scholarly publication is emerging: data publishing. Data publishing - or making data reusable, citable, and accessible for long periods - is more than simply providing a link to a data file or posting the data to the researcher’s web site. We will discuss best practices, including the use of persistent identifiers and full data citations, the importance of metadata, the choice between public data and restricted data with terms of use, the workflows for collaboration and review before data release, and the role of trusted archival repositories. The Harvard Dataverse repository (and the Dataverse open-source software) provides a solution for data publishing, making it easy for researchers to follow these best practices, while satisfying data management requirements and incentivizing the sharing of research data.
How Portable Are the Metadata Standards for Scientific Data?Jian Qin
The one-covers-all approach in current metadata standards for scientific data has serious limitations in keeping up with the ever-growing data. This paper reports the findings from a survey to metadata standards in the scientific data domain and argues for the need for a metadata infrastructure. The survey collected 4400+ unique elements from 16 standards and categorized these elements into 9 categories. Findings from the data included that the highest counts of element occurred in the descriptive category and many of them overlapped with DC elements. This pattern also repeated in the elements co-occurred in different standards. A small number of semantically general elements appeared across the largest numbers of standards while the rest of the element co-occurrences formed a long tail with a wide range of specific semantics. The paper discussed implications of the findings in the context of metadata portability and infrastructure and pointed out that large, complex standards and widely varied naming practices are the major hurdles for building a metadata infrastructure.
Dotnet scalable and secure sharing of personal health records in cloud compu...Ecway Technologies
This document proposes a framework for securely storing personal health records (PHRs) in cloud computing using attribute-based encryption (ABE). The framework divides users into security domains to reduce complexity in key management for PHR owners and users. It exploits multi-authority ABE to guarantee patient privacy. The proposed scheme also enables dynamic access policies and file attributes as well as efficient user/attribute revocation and emergency access. Analysis and experiments show the security, scalability and efficiency of the scheme.
Streamlined data sharing and analysis to accelerate cancer researchIan Foster
Advances in genomics and data analytics create new opportunities for cancer research and personalized medical treatment via large-scale federation of genomic, clinical, imaging and other data from many thousands of patients across institutions around the world. Despite these opportunities and promising early results, cancer research is often stymied by information technology barriers. One major barrier is a lack of tools for the reliable, secure, rapid, and easy transfer, sharing, and management of large collections of human data. In the absence of such tools, security and performance concerns often prevent sharing altogether or force researchers to resort to slow and error prone shipping of physical media. If data are received, timely analysis is further impeded by the difficulties inherent in verifying data integrity and managing who can access data and for what purpose. I will discuss how the mature Globus data management platform addresses these obstacles to discovery and explain how its intuitive, web-based interfaces enable use by researchers without specialized IT knowledge. I also describe how Globus technologies can be extended to meet the security requirements of human data so as to enable use in data-intensive cancer research.
Introduction to Data Transfer and Sharing for ResearchersGlobus
We will provide a summary review of Globus features targeted at those new to Globus. We will present various use cases that illustrate the power of Globus data sharing capabilities.
Globus is a non-profit service that aims to increase research efficiency by unifying access to disparate storage systems and simplifying secure data sharing. It allows users to easily, securely, and reliably transfer data between different resources like HPC systems, cloud storage, instruments, and personal computers. Globus also provides APIs and SDKs to help researchers build data-centric applications and automate workflows. Funding comes partly from government grants, with subscriptions enabling additional features and supporting ongoing operations.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document summarizes a presentation about Globus Genomics, a service that provides genomic data analysis tools and workflows through a web interface. It allows users to securely transfer data, run standardized analysis pipelines, access computational resources on demand through Amazon Web Services, and collaborate on shared data and workflows. The service aims to make genomic analysis more accessible, reproducible, and sustainable through various pricing models and support for individual labs and bioinformatics cores.
The document discusses sharing research data through open data platforms. It describes the CGIAR as uniquely positioned to collect agricultural data worldwide and argues that most CGIAR data should be archived and shared to increase its value. However, data archiving across CGIAR centers is currently poor. The document then discusses using the Dataverse platform to improve data sharing. Dataverse allows researchers to publish, share, cite, and analyze data. It also facilitates making data available while giving credit to data authors and institutions.
The document describes the eTRIKS Data Harmonization Service Platform, which aims to provide a common infrastructure and services to support cross-institutional translational research. It discusses challenges around data integration and harmonization. The platform utilizes standards and controlled vocabularies to syntactically and semantically harmonize data from various sources. It employs a metadata framework and modular workflow to structure, standardize, and integrate observational data into a harmonized repository for exploration and analysis. A demo of the platform's capabilities for project setup, data staging, exploration, export, and integration with tranSMART is also provided.
This document describes a proposed system for scalable and secure sharing of personal health records in cloud computing using attribute-based encryption. The system aims to address security issues with existing personal health record systems, such as privacy risks, scalability of key management, access control and user revocation. The proposed system uses attribute-based encryption to encrypt personal health records and a novel patient-centric framework with access control mechanisms. It allows for multiple data owners, dynamic access policies, and on-demand revocation of user access. The system is intended to be scalable, secure and efficient while ensuring patient control over personal health information.
Scalable and secure sharing of personal health recordscolourswathi
This document outlines a proposed system to securely store personal and medical information of patients online using attribute-based encryption. The existing system of storing this information in physical files has disadvantages like unauthorized access and high costs. The proposed system would encrypt the information using each user's unique attributes and only allow access by users with matching attributes, addressing issues of the existing system while providing universal access through the cloud at a lower cost.
Data repositories -- Xiamen University 2012 06-08Jian Qin
The document discusses data repositories and services. It begins by defining what a data repository is, noting that it is a logical and sometimes physical partitioning of data where multiple databases reside. It then outlines some key aspects of data repositories, including technical features like standards, software, and staffing requirements. The document also discusses functions of repositories like content management, archiving, dissemination and system maintenance. It provides examples of institutional repositories and data repositories, highlighting characteristics of each. Finally, it provides a case study on Dryad, an international repository for data and publications in biosciences.
The DataTags System: Sharing Sensitive Data with ConfidenceMerce Crosas
This talk was part of a session at the Research Data Alliance (RDA) 8th Plenary on Privacy Implications of Research Data Sets, during International Data Week 2016:
https://rd-alliance.org/rda-8th-plenary-joint-meeting-ig-domain-repositories-wg-rdaniso-privacy-implications-research-data
Slides in Merce Crosas site:
http://scholar.harvard.edu/mercecrosas/presentations/datatags-system-sharing-sensitive-data-confidence
Psdot 4 scalable and secure sharing of personal health records in cloud compu...ZTech Proje
FINAL YEAR IEEE PROJECTS,
EMBEDDED SYSTEMS PROJECTS,
ENGINEERING PROJECTS,
MCA PROJECTS,
ROBOTICS PROJECTS,
ARM PIC BASED PROJECTS, MICRO CONTROLLER PROJECTS
This document discusses several challenges related to managing and sharing genomic and biomedical data. It identifies key issues such as data annotation, analysis, storage, sharing, long-term planning, funding, and making data available in public repositories. It also discusses the importance of metadata, using ontologies and standards, developing data sharing policies that meet funder and journal requirements, and ensuring data is processed ethically and securely in accordance with privacy regulations.
Building Protected Data Sharing Networks to Advance Cancer Risk Assessment an...Mary Bass
This document discusses using the Globus data management platform to build protected data sharing networks that advance cancer risk assessment and treatment. It describes how Globus can securely manage and share data from instruments and analysis between personal resources, national resources, public clouds, and collaborators. It also allows publishing data for discoverability and establishes automated workflows for cancer research consortiums to leverage high-performance networks and cloud infrastructure.
FAIR Data Management and FAIR Data SharingMerce Crosas
Presentation at the Critical Perspective on the Practice of Digiral Archeology symposium: http://archaeology.harvard.edu/critical-perspectives-practice-digital-archaeology
Data Publishing at Harvard's Research Data Access SymposiumMerce Crosas
Data Publishing: The research community needs reliable, standard ways to make the data produced by scientific research available to the community, while giving credit to data authors. As a result, a new form of scholarly publication is emerging: data publishing. Data publishing - or making data reusable, citable, and accessible for long periods - is more than simply providing a link to a data file or posting the data to the researcher’s web site. We will discuss best practices, including the use of persistent identifiers and full data citations, the importance of metadata, the choice between public data and restricted data with terms of use, the workflows for collaboration and review before data release, and the role of trusted archival repositories. The Harvard Dataverse repository (and the Dataverse open-source software) provides a solution for data publishing, making it easy for researchers to follow these best practices, while satisfying data management requirements and incentivizing the sharing of research data.
How Portable Are the Metadata Standards for Scientific Data?Jian Qin
The one-covers-all approach in current metadata standards for scientific data has serious limitations in keeping up with the ever-growing data. This paper reports the findings from a survey to metadata standards in the scientific data domain and argues for the need for a metadata infrastructure. The survey collected 4400+ unique elements from 16 standards and categorized these elements into 9 categories. Findings from the data included that the highest counts of element occurred in the descriptive category and many of them overlapped with DC elements. This pattern also repeated in the elements co-occurred in different standards. A small number of semantically general elements appeared across the largest numbers of standards while the rest of the element co-occurrences formed a long tail with a wide range of specific semantics. The paper discussed implications of the findings in the context of metadata portability and infrastructure and pointed out that large, complex standards and widely varied naming practices are the major hurdles for building a metadata infrastructure.
Dotnet scalable and secure sharing of personal health records in cloud compu...Ecway Technologies
This document proposes a framework for securely storing personal health records (PHRs) in cloud computing using attribute-based encryption (ABE). The framework divides users into security domains to reduce complexity in key management for PHR owners and users. It exploits multi-authority ABE to guarantee patient privacy. The proposed scheme also enables dynamic access policies and file attributes as well as efficient user/attribute revocation and emergency access. Analysis and experiments show the security, scalability and efficiency of the scheme.
Streamlined data sharing and analysis to accelerate cancer researchIan Foster
Advances in genomics and data analytics create new opportunities for cancer research and personalized medical treatment via large-scale federation of genomic, clinical, imaging and other data from many thousands of patients across institutions around the world. Despite these opportunities and promising early results, cancer research is often stymied by information technology barriers. One major barrier is a lack of tools for the reliable, secure, rapid, and easy transfer, sharing, and management of large collections of human data. In the absence of such tools, security and performance concerns often prevent sharing altogether or force researchers to resort to slow and error prone shipping of physical media. If data are received, timely analysis is further impeded by the difficulties inherent in verifying data integrity and managing who can access data and for what purpose. I will discuss how the mature Globus data management platform addresses these obstacles to discovery and explain how its intuitive, web-based interfaces enable use by researchers without specialized IT knowledge. I also describe how Globus technologies can be extended to meet the security requirements of human data so as to enable use in data-intensive cancer research.
Introduction to Data Transfer and Sharing for ResearchersGlobus
We will provide a summary review of Globus features targeted at those new to Globus. We will present various use cases that illustrate the power of Globus data sharing capabilities.
Globus is a non-profit service that aims to increase research efficiency by unifying access to disparate storage systems and simplifying secure data sharing. It allows users to easily, securely, and reliably transfer data between different resources like HPC systems, cloud storage, instruments, and personal computers. Globus also provides APIs and SDKs to help researchers build data-centric applications and automate workflows. Funding comes partly from government grants, with subscriptions enabling additional features and supporting ongoing operations.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document summarizes a presentation about Globus Genomics, a service that provides genomic data analysis tools and workflows through a web interface. It allows users to securely transfer data, run standardized analysis pipelines, access computational resources on demand through Amazon Web Services, and collaborate on shared data and workflows. The service aims to make genomic analysis more accessible, reproducible, and sustainable through various pricing models and support for individual labs and bioinformatics cores.
Delivering a Campus Research Data Service with GlobusIan Foster
Keynote talk at the 2014 GlobusWorld conference (www.globusworld.org). Reviews science success stories, new features introduced over the past year, status of adoption, and our sustainability plans. Previewed our new publication service.
Accelerating Data-driven Discovery in Energy ScienceIan Foster
A talk given at the US Department of Energy, covering our work on research data management and analysis. Three themes:
(1) Eliminate data friction (use of SaaS for research data management)
(2) Liberate scientific data (research on data extraction, organization, publication)
(3) Create discovery engines at DOE facilities (services that organize data + computation)
Recording and Reasoning Over Data Provenance in Web and Grid ServicesMartin Szomszor
The document discusses the importance of provenance data in distributed computing environments like grids and web services. It proposes a service-oriented architecture and data model for capturing and querying provenance information. The architecture includes a provenance service for storage and analysis of provenance data gathered during workflow executions across multiple services and systems.
Introduces the Globus software-as-a-service for file transfer and data sharing. Includes step-by-step instructions for creating a Globus account, transferring a file, and setting up a Globus endpoint on your laptop.
HathiTrust Research Center Secure CommonsBeth Plale
Introduces HTRC secure commons, expanded secure infrastructure and services for text mining of HT digital data. Shows results comparing n-gram discovery using Solr full text index and a framework using mapReduce. Compute time over 1 million digital volumes is 1 day with 1024 cores. Weaknesses of Solr in n-gram identification are explored.
Simplified Research Data Management with the Globus PlatformGlobus
Overview of the Globus research data management platform, as presented at the Fall 2018 Membership Meeting of the Coalition for Networked Information (CNI), held in Washington, D.C., December 10-11, 2018
Introduction to Globus (GlobusWorld Tour - UMich)Globus
This document provides an agenda for a Globus World Tour event taking place on Monday and Tuesday. On Monday, there will be sessions on introductions to Globus for new and administrative users. On Tuesday, sessions will focus on developing with Globus, including building research data portals, automating workflows, and working with instrument data. The document also provides background information on Globus and how it aims to make research data movement, sharing, and synchronization easy, reliable and secure for researchers.
The BlueBRIDGE approach to collaborative researchBlue BRIDGE
Gianpaolo Coro, ISTI-CNR, at BlueBRIDGE workshop on "Data Management services to support stock assessement", held during the Annual ICES Science conference 2016
We provide a summary review of Globus features targeted at those new to Globus. We demonstrate how to transfer and share data, and install a Globus Connect Personal endpoint on your laptop.
This document proposes a framework for securely sharing personal health records (PHRs) stored in the cloud. It uses attribute-based encryption (ABE) to encrypt PHR files and allow flexible access control. The framework divides users into public and personal domains to address key management challenges at scale. It also introduces an efficient revocation mechanism and supports dynamic policy updates. Evaluation shows the framework provides security, scalability and efficiency for patient-centric PHR sharing in cloud computing environments.
This document proposes a framework for securely sharing personal health records (PHRs) stored in the cloud. It uses attribute-based encryption to encrypt PHR files under access policies. It divides users into public and personal domains to address key management challenges at scale. In the public domain, multiple attribute authorities distribute keys to manage professional users' role attributes without a single point of failure. Owners specify access policies during encryption. The personal domain allows owners to directly manage access for personal users. The framework supports dynamic policy updates, break-glass access, and an efficient revocation scheme.
Similar to NIH NCI Childhood Cancer Data Initiative (CCDI) Symposium Globus Poster (20)
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
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First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Understanding Globus Data Transfers with NetSageGlobus
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How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
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The Department of Energy's Integrated Research Infrastructure (IRI)Globus
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Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
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Extending Globus into a Site-wide Automated Data Infrastructure.pdfGlobus
The Rosalind Franklin Institute hosts a variety of scientific instruments, which allow us to capture a multifaceted and multilevel view of biological systems, generating around 70 terabytes of data a month. Distributed solutions, such as Globus and Ceph, facilitates storage, access, and transfer of large amount of data. However, we still must deal with the heterogeneity of the file formats and directory structure at acquisition, which is optimised for fast recording, rather than for efficient storage and processing. Our data infrastructure includes local storage at the instruments and workstations, distributed object stores with POSIX and S3 access, remote storage on HPCs, and taped backup. This can pose a challenge in ensuring fast, secure, and efficient data transfer. Globus allows us to handle this heterogeneity, while its Python SDK allows us to automate our data infrastructure using Globus microservices integrated with our data access models. Our data management workflows are becoming increasingly complex and heterogenous, including desktop PCs, virtual machines, and offsite HPCs, as well as several open-source software tools with different computing and data structure requirements. This complexity commands that data is annotated with enough details about the experiments and the analysis to ensure efficient and reproducible workflows. This talk explores how we extend Globus into different parts of our data lifecycle to create a secure, scalable, and high performing automated data infrastructure that can provide FAIR[1,2] data for all our science.
1. https://doi.org/10.1038/sdata.2016.18
2. https://www.go-fair.org/fair-principles
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As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and I will give a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Reactive Documents and Computational Pipelines - Bridging the GapGlobus
As scientific discovery and experimentation become increasingly reliant on computational methods, the static nature of traditional publications renders them progressively fragmented and unreproducible. How can workflow automation tools, such as Globus, be leveraged to address these issues and potentially create a new, higher-value form of publication? LivePublication leverages Globus’s custom Action Provider integrations and Compute nodes to capture semantic and provenance information during distributed flow executions. This information is then embedded within an RO-crate and interfaced with a programmatic document, creating a seamless pipeline from instruments, to computation, to publication.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
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UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
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A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
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- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
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Dr. Sean Tan, Head of Data Science, Changi Airport Group
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How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
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In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
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* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
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NIH NCI Childhood Cancer Data Initiative (CCDI) Symposium Globus Poster
1. How Globus works
Researcher initiates
transfer request; or
requested automatically
by script, science
gateway
1
Instrument
Compute Facility
Globus transfers files
reliably, securely
2
Globus controls
access to shared
files on existing
storage; no need
to move files to
cloud storage!
4
Researcher
selects files to
share, selects
user or group,
and sets access
permissions
3
Collaborator logs in to
Globus and accesses
shared files; no local
account required;
download via Globus
5
Personal Computer
Transfer
Share
• Use a Web browser or
platform services
• Access any storage
• Use an existing identity
Globus provides
researchers a fast,
reliable, and secure
way to move and
share sensitive data.
Streamlined sharing of
clinical patient data for
cancer research networks
Brigitte E. Raumann1 and Ian T. Foster1, 2
1Globus, University of Chicago
2Department of Computer Science
University of Chicago
We thank the Globus team for implementing and operating Globus services. Globus products
and services are developed and operated by the University of Chicago and supported by
funding from the Department of Energy, the National Science Foundation, the National
Institutes of Health, the National Institute of Standards and Technology, and the Alfred P.
Sloan Foundation. We also thank Globus subscribers for supporting the operation and
development of Globus, and users of Globus services for their continued support.
Challenge
Advances in genomics and data analytics create new
opportunities to advance cancer research via large-scale
sharing of genomic, clinical, imaging and other data types from
patients across institutions around the world. Yet these
opportunities are often stymied by a lack of tools for the
reliable, secure, rapid, and easy transfer and sharing of large
collections of human research data. In the absence of such
tools, security and performance concerns often force
researchers to resort to slow and error prone shipping of
physical media, or worse still, prevent sharing altogether. If data
are received, timely analysis is further impeded by the
difficulties inherent in verifying data integrity and managing
who can access data and for what purpose.
Solution
Globus addresses these obstacles to data management in data-
intensive cancer research by providing
• Secure, high-quality services to move, replicate, synchronize,
and share data sets.
• Intuitive, web-based interfaces.
• High reliability and speed, thanks to integrated monitoring,
failure recovery, and optimization.
• A command line interface for automation and simple REST
application programming interfaces (APIs), allowing
developers to provide robust file transfer and sharing
capabilities within their own research data applications and
services.
• Advanced identity management, single sign-on, and
authorization and authentication capabilities.
• Encryption in transit, auditing, access control, and other
features are provided to meet the security requirements of
human research data and HIPAA.
• By researchers for researchers
Globus capabilities are widely used to move, update, share,
and synchronize large data in distributed environments. It is
purpose built to serve the non-profit research community.
Globus provides
researchers a fast,
reliable, and secure
way to move and
share sensitive data.
RCC
Applications
Globus is widely used in the research community, with over
20,000 users in the past year, representing most leading US
universities, national laboratories, and many sites overseas.
Globus capabilities are ideal for managing the voluminous
datasets produced by next generation sequencing and the
many biomedical imaging modalities, data types especially
relevant in cancer research. Our technology has been applied in
a variety of biomedical research contexts where science can be
accelerated with rapid, reliable, and secure data transfer and
sharing, such as collaborative networks, sequencing and
imaging facilities, data portals, campus computing clusters,
supercomputers, and public and private clouds
Research Computing HPC
Desktop Workstations
Mass Storage Instruments
Personal Resources
Public Cloud
National Resources
I need to move or replicate data between systems.
I need to move or replicate data between systems.
Analysis
store
Next-Gen Sequencer
MRI
Advanced Light Source
Personal system
Remote visualization
High-durability,
low-cost store
Light Sheet Microscope
I need to get data from instrument to analysis system.
Cryo-EM
Public / private cloud stores
External
campus
storage
EC2
Project
repositories,
replication stores
Public repositories
I need to share my data with my colleagues.
I need to get data from instrument to analysis system.
I need to share my data with my colleagues.
Researchers have a unified view of all of their data, whether at
campus computing centers, national resources, lab servers,
cloud providers, instrument facilities, or on their laptop.
Instrument facilities have a fast, secure, automated mechanism
to distribute data to their users, without needing to create a
new account for each user.
Investigators can safely share data directly from where the
data are stored, without needed to upload data to the cloud.
Use a Web browser to access
your data wherever it is.
Share your data with your
colleagues using their
existing identities.