Understanding survey data available for researchers working in ageing: the CEPAR Metadata Database on Ageing

Background For researchers working in gerontology or the demography of ageing, knowledge of and access to population-based data, which includes mature age respondents, is critical. The collection of metadata (information describing data) supports researchers in their search for relevant data. Aims This proof-of-concept project seeks to develop a metadata database including metadata on Australian sample surveys relevant to ageing over the period 2010–2018. Data and methods We used a five-stage approach to create the Centre for Excellence in Population Ageing Research (CEPAR) metadata database on ageing: 1) identification of in-scope survey datasets; 2) indexing the in-scope surveys; 3) scraping metadata from publicly available sources; 4) appending metadata to a master database; and 5) creation of a webtool to enable users to search and export metadata and obtain contact details for the relevant data custodian. Results The CEPAR Metadata Database webtool is available from: https://mspgh.unimelb.edu.au/centres-institutes/centre-for-health-policy/research-group/metadata-database. Conclusions Metadata database collections can assist researchers to identify what data has been collected (for their specific research interest in ageing), how it was collected and how to gain access to the data.

Linking Registry Data with Australian Medicare And Medication Dispensing Claims Data: Feasibility, Benefits and Limitations

IntroductionRecent advances in Australia mean that it is possible to link national clinical registries with government held administrative datasets. However, formal evaluations of such activities and the potential impact for research are lacking. Objectives and ApproachWe aimed to assess the feasibility and accuracy of linking registrants from the Australian Stroke Clinical Registry (AuSCR) with the Medicare enrolment file. Following data custodian and ethics approvals, personal linkage identifiers were submitted to the Australian Institute of Health and Welfare (AIHW). De-identified data from AuSCR and the AIHW were submitted into the Secure Unified Research Environment and merged using project specific person-based IDs. We calculated the proportion of patients linked with the Medicare enrolment file that were present in the associated Medicare and medication dispensing datasets and the proportion with claims after their date of death. Logistic regression was used to identify factors associated with a non-merged patient. Results17,980 AuSCR registrants (January 2010-July 2014) were submitted for linkage (median age 76 years; 46% female; 67% ischaemic stroke; 16% TIA). Of these, 93% were merged with Medicare (N=16,648) and 95% with subsidised medication dispensing claims data (N=17,079). In those who died, 127 (0.8%) had one or more Medicare claim and 411 (2.4%) had one or more medications dispensed after their death date. Asian born registrants were less likely to be merged with Medicare (adjusted Odds Ratio [aOR]: 0.54; 95% Confidence Interval [CI]: 0.40, 0.72) than Australian born registrants. Those aged ≥85 years were less likely to be merged with Medicare data than those aged <65 years (aOR 0.24; 95% CI: 0.19, 0.29) but were more likely to be merged with dispensing data (aOR: 2.22 (95% CI: 1.73, 2.84). Conclusion/ImplicationsLinkage between a national clinical quality registry and the Medicare spine is feasible. These linkages will provide novel insights into post-stroke care.

Population Data Centre Profiles: Centre for Data Linkage

The Centre for Data Linkage (CDL) was established at Curtin University, Western Australia, to develop infrastructure to enable cross-jurisdictional record linkage in Australia. The CDL’s operating model makes use of the ‘separation principle’, with content data typically provided to researchers directly by the data custodian; jurisdictional linkage where available are used within the linkage process. Along with conducting record linkage, the team has also invested in establishing a research programme in record linkage methodology and in developing modern record linkage software which can handle the size and complexity of today’s workloads. The Centre has been instrumental in the development of practical methods for privacy-preserving record linkage, with this methodology now regularly used for real-world linkages. While the promise of a nation-wide linkage system in Australia has yet to be met, distributed models provide a potential solution.

Context-Based Roles and Competencies of Data Curators in Supporting Research Data Lifecycle Management: Multi-Case Study in China

Focusing on the main research question of what the critical roles and competencies of data curation are in supporting research data life cycle management, this paper adopts a multi-case study method, with data governance frameworks, to analyze stakeholders and data curators, and their competencies, based on different contexts from cases from enterprises and academic libraries in mainland China. Via the context and business analysis on different cases, critical roles such as data supervisor, data steward, and data custodian in guaranteeing data quality and efficiency of data reuse are put forward. Based on the general factor framework summarized via existing literature, suggestions for empowering data curators’ competencies are raised according to the cases. The findings of this paper are as follows: besides digital archiving and preservation, more emphasis should be placed on data governance in the field of data curation. Data curators are closely related but not equivalent to stakeholders of data governance. The different roles of data curators would play their own part in the process of data curation and can be specified as data supervisor, data steward, and data custodian according to given contexts. The roles, competencies, and empowerment strategies presented in this paper might have both theoretical and practical significance for the fields of both data curation and data governance.

Challenges in sharing of geospatial data by data custodians in South Africa

As most development planning and rendering of public services happens at a place or in a space, geospatial data is required. This geospatial data is best managed through a spatial data infrastructure, which has as a key objective to share geospatial data. The collection and maintenance of geospatial data is expensive and time consuming and so the principle of “collect once &amp;ndash; use many times” should apply. It is best to obtain the geospatial data from the authoritative source &amp;ndash; the appointed data custodian. In South Africa the South African Spatial Data Infrastructure (SASDI) is the means to achieve the requirement for geospatial data sharing. This requires geospatial data sharing to take place between the data custodian and the user. All data custodians are expected to comply with the Spatial Data Infrastructure Act (SDI Act) in terms of geo-spatial data sharing. Currently data custodians are experiencing challenges with regard to the sharing of geospatial data.<br> This research is based on the current ten data themes selected by the Committee for Spatial Information and the organisations identified as the data custodians for these ten data themes. The objectives are to determine whether the identified data custodians comply with the SDI Act with respect to geospatial data sharing, and if not what are the reasons for this. Through an international comparative assessment it then determines if the compliance with the SDI Act is not too onerous on the data custodians.<br> The research concludes that there are challenges with geospatial data sharing in South Africa and that the data custodians only partially comply with the SDI Act in terms of geospatial data sharing. However, it is shown that the South African legislation is not too onerous on the data custodians.

Introduction of the Community Rehabilitation Northern Queensland Service

Objective: To analyse trends in length of hospital stay before and after the implementation of the Community Rehabilitation Northern Queensland Service (CRNQ) in Townsville, Australia. Design: Retrospective analysis of collected administrative data provided by the data custodian Townsville Hospital Health Service District. Setting: All patients discharged from the Townsville hospital between 1 July 2008 and 30 June 2013 for whom the Australian Refined Diagnosis Related Groups were stroke (B70), degenerative nervous system disorders (B67) or rehabilitation (Z60). Main outcome measures: Average length of stay and total number of inpatient episodes coded stroke, degenerative nervous system disorders or rehabilitation. Results: Length of stay for the selected diagnosis related groups was consistently ranging from 23 days to 25 days for the period 2008-2012. In the first year of full operational capacity of CRNQ (2012-13), there was an average reduction of six days in length of stay. The major reductions in length of stay occurred in patients admitted for rehabilitation care. Conclusions: This study adds additional evidence that earlier discharge can be facilitated for patients with neurological conditions living outside metropolitan areas when appropriate rehabilitation services are available in the community. Abbreviations: AR-DRG – Australian Refined Diagnosis Related Groups; CRNQ – Community Rehabilitation Northern Queensland Service.

Custodian Controlled Data Repository - supporting the timely, easy and cost effective access to linked data

ABSTRACTObjectivesIn response to Data Custodian and Researcher's request to assist improving the timeliness and ease of data extractions, SA NT DataLink established the Custodian Controlled Data Repository (CCDR). Issues including conflicting work priorities and limited resources do prevent timely data extractions. SA NT DataLink, as a trusted third party enable Custodians to hold separate copies of their de-identified content data ready for timely release. The CCDR is opt-in for Custodians. Its key strength being the data remains under the control of participating Custodians, with Custodians updating and correcting their data. SA NT DataLink staff are work with Data Custodians to clean, standardise, update and prepare data in advance of anticipated approvals, including spatial enabled GIS variables. SA NT DataLink staff work under the direction of the Data Custodians, taking responsibility for preparing the data extractions required for the approved project. ApproachThe SA NT DataLink Custodian Controlled Data Repository (CCDR) takes advantage of the Secure Unified Research Environment (SURE), which is a secure remote access data laboratory operated by the Sax Institute in Sydney Australia. Using thin client and two-factor authentication, Data Custodians from South Australia and across Australia are able to securely store and maintain de-identified copies of their content data in SURE, ready for standardisation, quality review, and more timely release for approved use and data linkage projects. ResultsThe CCDR functional diagram provides an understanding of the data flow and processes that support more timely, easy and cost effective collation and provision of de-identified and privacy protected data. The Curated Gateway feature of SURE manages all the data coming into and being released from the Repository. Agreed regular updates of Data Custodian's data is able to be stored into their sub-directory, with access to the sub-directory managed by authentication and passwords. The SA NT DataLink Analysts is able to perform the role of data integrator for approved projects and use, also running privacy protecting algorithms and verification of the data being provided against the approvals. ConclusionThe CCDR securely stores the de-identified data ready for it to be integrated and released to Researchers. Use of secure remote access technologies allows Data Custodians to maintain control of their preloaded and pre-cleaned data in CCDR. In doing so this allows Custodians to authorise the use, from which SA NT DataLink staff dedicated to working only in the CCDR, integrate and release the data in a more timely manner.

An Innovative Government Architecture with Semantic Technology

Over the past decade, authorities invested highly in public service provision over the Internet via portals. Back office systems of authorities collect and store data entered by citizens and enterprises to support decision-making by civilians. The data represents both the state of citizens and enterprises, public service transactions, and the physical infrastructure including ownership relations. Whilst civilians use the data for decisions, data quality influences decision quality. As data steward, civilians have improved data quality by removing duplicate data and created specific data stores for reference data like addresses, enterprises, and citizens. Citizens and enterprises can use reference data to complete electronic public service request forms. To further improve data quality, civilians perform physical inspections and/or assess external data sources to validate for instance data consistency. Besides data steward, civilians are also data custodian: they provide processing and storage facilities. In this contribution, the author will argue that an innovative architecture separating data steward and data custodian roles, currently held by civilians, decreases the Total Cost of Ownership of authorities' IT and contributes to economic growth. In the proposed approach, persons and organizations take the data stewardship role, facilitated by a provider of a data custodian role either in the public or private domain. Civilians can access the data for decision-making. Civilians still act as data steward with respect to additional data resources than provided by citizens and enterprises in decision-making. The approach is illustrated by a case and supported by the governance policy of for instance Dutch Customs Authority.

Disclosure-Protected Inference with Linked Microdata Using a Remote Analysis Server

Large amounts of microdata are collected by data custodians in the form of censuses and administrative records. Often, data custodians will collect different information on the same individual. Many important questions can be answered by linking microdata collected by different data custodians. For this reason, there is very strong demand from analysts, within government, business, and universities, for linked microdata. However, many data custodians are legally obliged to ensure the risk of disclosing information about a person or organisation is acceptably low. Different authors have considered the problem of how to facilitate reliable statistical inference from analysis of linked microdata while ensuring that the risk of disclosure is acceptably low. This article considers the problem from the perspective of an Integrating Authority that, by definition, is trusted to link the microdata and to facilitate analysts’ access to the linked microdata via a remote server, which allows analysts to fit models and view the statistical output without being able to observe the underlying linked microdata. One disclosure risk that must be managed by an Integrating Authority is that one data custodian may use the microdata it supplied to the Integrating Authority and statistical output released from the remote server to disclose information about a person or organisation that was supplied by the other data custodian. This article considers analysis of only binary variables. The utility and disclosure risk of the proposed method are investigated both in a simulation and using a real example. This article shows that some popular protections against disclosure (dropping records, rounding regression coefficients or imposing restrictions on model selection) can be ineffective in the above setting.

The Dean of Information

The author focuses on the institutional researcher as an institutional leader, over and above providing traditional reporting and support. IR practitioners hold authority over the institution’s data. Leadership and social psychological theory can explain their effectiveness. The author combines effective leadership theory with the Theory of Planned Behavior to produce framework for IR leadership. This framework should help the IR professional be more than a data custodian. It should help the IR professional adopt both a transformative and facilitative leadership stance as needed, in order to help the institution reach its goals.