scholarly journals BC Data ScoutTM: A New Tool To Investigate Datasets For Health Research

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Sarah Kesselring ◽  
Jessica Galo ◽  
Kelly Sanderson ◽  
Shirley Wong ◽  
Maureen Neuman ◽  
...  
Keyword(s):  
User Satisfaction ◽  
Population Data ◽  
Data Access ◽  
Data Availability ◽  
Administrative Databases ◽  
Hospital Data ◽  
Full Data ◽  
High Quality Research ◽  
Support Unit ◽  
Access Request

IntroductionBC’s Ministry of Health (MOH) maintains many administrative databases with rich information and analytical potential. Researchers are keen to use these data for both discovery and applied research. Historically, limited views of data availability and populations therein have supported study feasibility. Therefore, we developed BC Data ScoutTM, a cohort browser. Objectives and ApproachWe developed a cohort browser service to provide information to researchers planning a study using MOH data. The objective was to create a tool that is simple to use, provides quick results and is free to users to encourage its use. A better understanding of the data available can improve study quality and expand the user-base by giving researchers access to information not previously available during the planning stages. The tool will be evaluated by examining the number of requests received and a user satisfaction survey. Plans are in place to expand into additional data sources and extend query sophistication. ResultsThe BC Data ScoutTM online tool provides cohort information in the form of highly aggregated, approximate results to researchers planning a study. It was developed by the MOH, the BC SUPPORT Unit and Population Data BC (PopData) and was launched in February 2018. The service is delivered by PopData. BC Data ScoutTM offers province-wide information for query, is accessible to a wide group of eligible researchers, and has data availability from the year 2000 onwards. Four types of MOH data are available for query: hospital data; physician data; pharmaceutical data; and demographics. In addition to determining study feasibility, the aggregate reports also help to further refine a full data access request and provide enough information to complete and strengthen a funding application. Conclusion/ImplicationsBC Data ScoutTM will be beneficial for researchers planning to request data. This preliminary information may increase the chances of meaningful research studies to obtain funding, and the production of relevant, high-quality research results. BC will be among the first jurisdictions across Canada to offer this type of feasibility service.

PPHA-Popularity Prediction Based High Data Availability for Multimedia Data Center

2019 ◽  
Vol 11 (1) ◽  
pp. 17-29
Author(s):  
Kuo-Chi Fang ◽  
Husnu S. Narman ◽  
Ibrahim Hussein Mwinyi ◽  
Wook-Sung Yoo
Keyword(s):  
Data Center ◽  
Service Providers ◽  
Data Access ◽  
Current Data ◽  
Multimedia Data ◽  
Data Availability ◽  
Full Data ◽  
Data Center Management ◽  
Popularity Prediction ◽  
Data Objects

Due to the growth of internet-connected devices and extensive data analysis applications in recent years, cloud computing systems are largely utilized. Because of high utilization of cloud storage systems, the demand for data center management has been increased. There are several crucial requirements of data center management, such as increase data availability, enhance durability, and decrease latency. In previous works, a replication technique is mostly used to answer those needs according to consistency requirements. However, most of the works consider full data, popular data, and geo-distance-based replications by considering storage and replication cost. Moreover, the previous data popularity based-techniques rely on the historical and current data access frequencies for replication. In this article, the authors approach this problem from a distinct aspect while developing replication techniques for a multimedia data center management system which can dynamically adapt servers of a data center by considering popularity prediction in each data access location. Therefore, they first label data objects from one to ten to track access frequencies of data objects. Then, they use those data access frequencies from each location to predict the future access frequencies of data objects to determine the replication levels and locations to replicate the data objects, and store the related data objects to close storage servers. To show the efficiency of the proposed methods, the authors conduct an extensive simulation by using real data. The results show that the proposed method has an advantage over the previous works in terms of data availability and increases the data availability up to 50%. The proposed method and related analysis can assist multimedia service providers to enhance their service qualities.

scholarly journals The BC SUPPORT Unit Data Platform: Offering Data-Related Services To Researchers In British Columbia

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Sarah Kesselring ◽  
Bryony Mander ◽  
Ognjenka Djurdjev ◽  
Kenneth Moselle ◽  
Elodie Portales-Casamar ◽  
...  
Keyword(s):  
Data Collection ◽  
Research Question ◽  
Population Data ◽  
Data Access ◽  
Direct Access ◽  
Sensitive Data ◽  
Ministry Of Health ◽  
Support Unit ◽  
Data Platform ◽  
Oriented Research

IntroductionThe Canadian Institutes of Health Research (CIHR) and provinces co-fund local Units to increase the quality and quantity of patient-oriented research. These SUPPORT (Support for People and Patient-Oriented Research and Trials) Units include a prominent Data Plan component. The BC Plan is the result of collaboration between many organizational partners. Objectives and ApproachA Data Advisory Committee comprised of eight organizational partners worked together for several months in 2016-2017 to develop BC’s provincial Data Plan. The Data Plan includes seven objectives; in general, the plan seeks to make additional data available for research, increase the speed and transparency of data access, and offer services to enable more efficient data use. The services resulting from the Data Plan are intended to improve support for the entire continuum of a research project, from developing a research question to analyzing the results. Several projects are part of Ministry of Health-led work developing a Health Data Platform. ResultsThe projects initiated so far as part of the Data Plan include: BC Data Scout\textsuperscript{TM}: an online tool that provides aggregate cohort information to inform research question development; REDCap: software to support privacy-sensitive data collection and management; INFORM: software to support data collection for complex clinical research studies and trials; Direct Access: enables Population Data BC to access BC Ministry of Health databases so researchers have access to up-to-date data; Streamlining: making the data request process more efficient; New datasets: several projects that will provide new data sources, including patient experience and outcome measures and secondary use data drawn from electronic medical records; and Inventory: an online catalog for all high-value and linkable data sets available to researchers. Conclusion/ImplicationsThe services and tools included in BC’s Data Plan will help researchers develop and deliver world-class research and inform important health care decisions. The patient-oriented focus of these services help to ensure that research is done in partnership with patients and centered on research questions that matter to them.

scholarly journals Navigating Legal and Ethical Requirements for Multi-Stakeholder Data Access Requests Through Harmonized Documentation

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Jessica Galo ◽  
Tim Choi ◽  
Maria Kim-Bautista
Keyword(s):  
Data Storage ◽  
Data Transfer ◽  
Population Data ◽  
Data Access ◽  
Data Sets ◽  
Multiple Sources ◽  
Multiple Data ◽  
Access Request ◽  
Multiple Data Sets ◽  
Multi Stakeholder

IntroductionResearch increasingly involves linking data from multiple sources, including data collected by researchers. This creates complexity because data providers often have differing policies and requirements for data access. Harmonization of processes requires resources, especially as new data providers are added, and needs to be prioritized appropriately. ObjectivesOur objectives were to: 1. understand the challenges encountered by researchers interested in collecting data and/or linking multiple data sets; and 2. outline and evaluate Population Data (PopData) BC’s efforts into harmonizing documentation and processes to address these challenges. With this information, we aim to better support research and streamline the data access request process. ApproachWe compared data access timelines of projects that did and did not utilize harmonized templates, including consent forms, data access request forms, and research agreements. We then identified the challenges arising from non-harmonized requirements including their number and complexity, and developed priorities for action. ResultsWhile existing consent form templates provided the ethics board-required language to support the collection of researcher-collected data, they lacked the text requirements of the administrative data stewards/providers. These text deficiencies slow down the data access request process, affect data provider workflow, and can be associated with researcher costs to re-consent. To address these gaps, harmonized consent templates were developed and finalized in November 2017. These templates included the data steward text requirements on governance, data sets, data transfer, data storage, and withdrawal. Non-harmonized data access request forms and research agreements varied in format and detail and resulted in coordination challenges and delays. A harmonized form was developed to capture key information required by all stakeholders. Research agreement harmonization discussions are underway. Impact evaluation is ongoing. Conclusion/ImplicationsThe complexity multi-stakeholder dataset research need not extend to the data access process. Coordinated requirements and harmonized documentation reduce the burden on all stakeholders including researchers, ethics boards, and data stewards and improve the project timelines.

Design and Evaluation of a Continuous Data Level Auditing System

2014 ◽  
Vol 33 (4) ◽  
pp. 221-245 ◽  
Author(s):  
Alexander Kogan ◽  
Michael G. Alles ◽  
Miklos A. Vasarhelyi ◽  
Jia Wu
Keyword(s):  
Business Processes ◽  
Population Data ◽  
Daily Basis ◽  
Data Availability ◽  
Continuous Data ◽  
Continuous Auditing ◽  
Major Health ◽  
Analytical Monitoring ◽  
Data Level ◽  
Unique Capability

SUMMARY: This study develops a framework for a continuous data level auditing system and uses a large sample of procurement data from a major health care provider to simulate an implementation of this framework. In this framework, the first layer monitors compliance with deterministic business process rules and the second layer consists of analytical monitoring of business processes. A distinction is made between exceptions identified by the first layer and anomalies identified by the second one. The unique capability of continuous auditing to investigate (and possibly remediate) the identified anomalies in “pseudo-real time” (e.g., on a daily basis) is simulated and evaluated. Overall, evidence is provided that continuous auditing of complete population data can lead to superior results, but only when audit practices change to reflect the new reality of data availability. Data Availability: The data are proprietary. Please contact the authors for details.

scholarly journals Resource-Aware Cooperative Caching on Mobile Ad-hoc Peer to Peer Networks

2021 ◽  
Author(s):  
Hoda R.K. Nejad
Keyword(s):  
Ad Hoc Networks ◽  
Overlay Networks ◽  
Ad Hoc ◽  
Data Access ◽  
Peer To Peer ◽  
Data Availability ◽  
Cooperative Caching ◽  
P2p Systems ◽  
Hoc Networks ◽  
Resource Aware

With the emergence of wireless devices, service delivery for ad-hoc networks has started to attract a lot of attention recently. Ad-hoc networks provide an attractive solution for networking in the situations where network infrastructure or service subscription is not available. We believe that overlay networks, particularly peer-to-peer (P2P) systems, is a good abstraction for application design and deployment over ad-hoc networks. The principal benefit of this approach is that application states are only maintained by the nodes involved in the application execution and all other nodes only perform networking related functions. On the other hand, data access applications in Ad-hoc networks suffer from restricted resources. In this thesis, we explore how to use Cooperative Caching to improve data access efficiency in Ad-hoc network. We propose a Resource-Aware Cooperative Caching P2P system (RACC) for data access applications in Ad-hoc networks. The objective is to improve data availability by considering energy of each node, demand and supply of network. We evaluated and compared the performance of RACC with Simple Cache, CachePath and CacheData schemes. Our simulation results show that RACC improves the lay of query as well as energy usage of the network as compared to Simple Cache, CachePath and CacheData.

scholarly journals Research-ready data for multi-cohort analyses: The Dementias Platform UK (DPUK) C-Surv data model

2021 ◽  
Author(s):  
Sarah Bauermeister ◽  
Joshua R Bauermeister ◽  
R Bridgman ◽  
C Felici ◽  
M Newbury ◽  
...  
Keyword(s):  
Data Model ◽  
Data Access ◽  
Data Discovery ◽  
Standard Data ◽  
Technology Standard ◽  
Access Request ◽  
Nested Structure ◽  
Using Data ◽  
Model C ◽  
Cohort Analyses

Abstract Research-ready data (that curated to a defined standard) increases scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following user consultation, a standard data model (C-Surv), optimised for data discovery, was developed using data from 12 Dementias Platform UK (DPUK) population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. It was concluded that developing and applying a standard data model (C-Surv) for research cohort data is feasible and useful.

scholarly journals The Brazilian cohort of pulp and paper workers: the logistic of a cancer mortality study

1998 ◽  
Vol 14 (suppl 3) ◽  
pp. S117-S123 ◽  
Author(s):  
Anaclaudia Gastal Fassa ◽  
Luiz Augusto Facchini ◽  
Marinel Mór Dall'Agnol
Keyword(s):  
Data Access ◽  
Pulp And Paper ◽  
Data Accuracy ◽  
Data Availability ◽  
International Agency ◽  
Historical Cohort ◽  
Increased Risk ◽  
Risk Of Cancer ◽  
Access Data ◽  
Brazilian Cohort

The International Agency for Research on Cancer (IARC) proposed this international historical cohort study trying to solve the controversy about the increased risk of cancer in the workers of the Pulp and Paper Industry. One of the most important aspects presented by this study in Brazil was the strategies used to overcome the methodological challenges, such as: data access, data accuracy, data availability, multiple data sources, and the large follow-up period. Through multiple strategies it was possible to build a Brazilian cohort of 3,622 workers, to follow them with a 93 percent success rate and to identify in 99 percent of the cases the cause of death. This paper, has evaluated the data access, data accuracy and the effectiveness of the strategies used and the different sources of data.

scholarly journals Symposium: Distributed Networks of Federated Secure Research Data Environments – Enabling Analytics Across Multiple Platforms

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Matthias Schneider
Keyword(s):  
Population Data ◽  
Data Access ◽  
Distributed Networks ◽  
Research Data ◽  
Data Governance ◽  
Virtual Database ◽  
South Wales ◽  
Challenges And Opportunities ◽  
Storage Location ◽  
Time Required

IntroductionUsers of linked data require access to an increasing number of heterogeneous datasets from diverse domains, often held in different secure research data environments, especially for multi-jurisdictional projects. Under the traditional model of data access, projects are required to transfer and harmonise the necessary datasets in one central location before analysis can be undertaken, increasing the time required for data acquisition and preparation. Objectives and ApproachIn a federated data environment, analysts query distributed datasets held in a network of multiple secure data environments via a central virtual database, without requiring the data to move. Instead, the data is analysed as close as possible to its storage location, minimising the amount of data transfers and giving data custodians more control over their data. This symposium explores the challenges and opportunities of establishing and operating a distributed network of federated secure research data environments. Leading organisations operating data platforms in various jurisdictions present for 15 minutes each the current capabilities of their platforms, the landscape of data environments in their jurisdictions and potential approaches to key questions such as: Harmonising/federating data sources Data security Data governance Discoverability/metadata Performance The audience is the then invited to participate in discussing the topic for the remaining 30 minutes. The following individuals have been approached to represent their organisations in this symposium: Professor David Ford, Swansea University: UK Secure eResearch Platform (UK SErP) Charles Victor, Institute for Clinical Evaluative Sciences (ICES): ICES Data & Analytic Virtual Environment (IDAVE) Professor Louisa Jorm, Centre for Big Data Research in Health, University of New South Wales: E-Research Institutional Cloud Architecture (ERICA) Professor Kimberlyn McGrail, Population Data BC: Secure Research Environment (SRE) Results / Conclusion / ImplicationsThis symposium will help formulate requirements for and barriers to distributed networks of federated secure research data environments, and create a foundation for data analytics across multiple platforms.

The Perceived Impact of Journal of Information Systems on Promotion and Tenure

2014 ◽  
Vol 29 (1) ◽  
pp. 73-93 ◽  
Author(s):  
Diane J. Janvrin ◽  
Jee-Hae Lim ◽  
Gary F. Peters
Keyword(s):  
Information Systems ◽  
Doctoral Program ◽  
Data Availability ◽  
Private Institution ◽  
High Quality Research ◽  
Accounting Information Systems ◽  
Promotion And Tenure ◽  
Supportive Role ◽  
Perceived Impact ◽  
Tenure Process

ABSTRACT During the promotion and tenure process, most institutions evaluate whether the candidate has published in high-quality research journals. This study examines the perceived impact of the Journal of Information Systems (JIS) on the promotion and tenure process. The research surveys 149 accounting information systems professors and 36 accounting department leaders. Results suggest that 62 percent of respondents indicated the JIS was very impactful on the promotion and tenure process, while 34 percent perceived the journal to play only a supportive role to higher-ranked journals. Further, senior scholars hold a higher perception of JIS's impact, while those who have served as external reviewers for promotion and tenure committees hold lower perceptions. Finally, results indicate a negative association between perceived promotion and tenure impact and whether the respondent is from a private institution, a larger-sized institution, and if the institution offers a doctoral program. Data Availability: All data used in this study are available upon request. The survey may be found in the online resources.

A Spatio-Temporal Cache Replacement Policy for Location Dependent Data in Mobile Environments

2010 ◽  
Vol 6 (3) ◽  
pp. 31-48 ◽  
Author(s):  
Mary Magdalene Jane.F ◽  
R. Nadarajan ◽  
Maytham Safar
Keyword(s):  
Data Access ◽  
Data Availability ◽  
Replacement Policy ◽  
Dependent Data ◽  
Access Time ◽  
Cache Replacement ◽  
Cache Replacement Policy ◽  
Active Sets ◽  
Mobile Clients ◽  
Spatio Temporal

Data caching in mobile clients is an important technique to enhance data availability and improve data access time. Due to cache size limitations, cache replacement policies are used to find a suitable subset of items for eviction from the cache. In this paper, the authors study the issues of cache replacement for location-dependent data under a geometric location model and propose a new cache replacement policy RAAR (Re-entry probability, Area of valid scope, Age, Rate of Access) by taking into account the spatial and temporal parameters. Mobile queries experience a popularity drift where the item loses its popularity after the user exhausts the corresponding service, thus calling for a scenario in which once popular documents quickly become cold (small active sets). The experimental evaluations using synthetic datasets for regular and small active sets show that this replacement policy is effective in improving the system performance in terms of the cache hit ratio of mobile clients.

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