National Centre for Longitudinal Data Access and Use Protocols March 2018

Transcription

1 National Centre for Longitudinal Data Access and Use Protocols March 2018

2 Table of Contents Introduction... 2 Datasets... 2 Accessing and using the DSS longitudinal datasets... 2 Data storage... 3 Sharing Research Materials... 3 Acknowledgement of Use... 5 Appendix 1 Terms and Conditions of Use... 7 Appendix 2 - Longitudinal Study of Indigenous Children data protocols Appendix 3 Authorised Training Activities Appendix 4 - LSAC Australian Early Development Census (AEDC) linked Data Appendix 5 - HILDA-CNEF Datasets

3 Introduction The Department of Social Services (DSS), on behalf of the Australian Government, undertakes research and policy development to support the lifetime wellbeing of individuals, families and communities. To support its objectives, DSS funds four longitudinal studies that contribute to the evidence base on the lives of Australians and the social, economic, housing and family issues that impact on them: The Household, Income and Labour Dynamics in Australia (HILDA) Survey Growing up in Australia: The Longitudinal Study of Australian Children (LSAC) Footprints in Time: The Longitudinal Study of Indigenous Children (LSIC) Building a New Life in Australia (BNLA): The Longitudinal Study of Humanitarian Migrants. The National Centre for Longitudinal Data (NCLD) within DSS is responsible for the management of the studies and their output datasets. Datasets Datasets available from DSS longitudinal studies include: HILDA General Release HILDA Restricted Release LSAC General Release LSAC Restricted Release LSIC General Release BNLA General Release. General Release means a release of data from which more sensitive information such as names, addresses (including postcodes) and date of birth have been removed and some other information has been modified by various methods such as top coding and the application of classification codes at a more general level. Restricted Release means a release of data from which the names and addresses have been removed but some information such as postcodes, date of birth and other data are provided at a more detailed level than the General Release datasets. Because of this, access arrangements to Restricted Release data are more rigorous than for General Release data. There is no cost to access each General release dataset. There is a fee of $64 (GST exclusive) to access each Restricted release dataset. Each release includes data files and supporting materials relating to the data. All data files that are made available through Dataverse (both General and Restricted) have conditions of access, meaning eligibility and verification requirements need to be met prior to accessing these files. All supporting documentation for the data files are published as open access files, meaning there are no access controls applied. The differences between each General and Restricted release dataset are outlined in supporting documentation (such as data dictionaries or data user manuals) published online at the time of each new data release. If applying for Restricted release, applicants must provide a rationale for seeking access. The online application form asks additional questions about specific variables. Applications are reviewed by NCLD staff who may contact applicants to discuss their request. Currently, applicants based outside Australia are not permitted access to Restricted release data files. If you are based overseas you will need to contact the NCLD to seek advice on possible collaboration solutions. Other datasets may be developed and made available from time to time. Accessing and using the DSS longitudinal datasets Access to DSS longitudinal data is conditional on agreement to the Terms and Conditions of Use (Appendix 1). Agreement to the Terms and Conditions of Use is sought at the point of submitting the online application form 2

4 for any controlled access data file. DSS may specify other mechanisms for agreeing to the Terms and Conditions of Use from time to time. Any person wishing to access DSS longitudinal data must apply online through the NCLD Dataverse site, which is managed by the Australian Data Archive (ADA). The following quick reference guides (QRG) contain step-bystep instructions: Dataverse Registration QRG Data Access Request QRG DSS has an obligation to ensure security and privacy protocols are adhered to in order to protect the privacy of the study participants: Applicants must accurately identify themselves when registering with Dataverse. Details supplied in the application form must accurately reflect the intended use of the dataset. DSS may, through the ADA or independently, seek to verify an applicant s identity and/or confirm the intended use of the dataset. Authorised Users (approved applicants) are responsible for mandatory data breach handling and notifications. Data storage Authorised Users must adhere to the storage and destruction conditions outlined in this section of the Protocols and in the Terms and Conditions of Use (Appendix 1). Only the following data storage options are acceptable for storing DSS longitudinal data holdings: On a cloud server which has been awarded Australian Signals Directorate (ASD) certification to provide cloud services; or On a secure network; or On a password protected removable drive; or On a local drive on password protected PC or laptop. Storage of DSS longitudinal data holdings on an Australian private cloud server is permitted where evidence can be provided that the cloud service provider has completed an Information Security Registered Assessors Program (IRAP) security assessment and been awarded Australian Signals Directorate (ASD) certification to provide cloud services to Australian Government organisations. Any service agreement or contract entered into between the Authorised User and the cloud service provider must not change or transfer ownership of the dataset. ASD-certified cloud storage complies with Australian Privacy Principle (APP) 11 Security of personal information. However, ASD-certified cloud storage does not mitigate the need for Authorised Users to adhere to the security requirements outlined in this section of the Protocols and in the Terms and Conditions of Use (Appendix 1). By exception only, DSS may consider data storage on cloud services that have undergone an IRAP security assessment reviewed by internal stakeholders. Approval for alternate cloud storage arrangements may also be given on a case by case basis where DSS, in consultation with relevant internal stakeholders, believes sufficient controls are in place to protect the data. Sharing Research Materials DSS longitudinal studies are funded by the Australian Government so that research resulting from their use can form part of the evidence base for policy development in line with the Department s mission to improve the lifetime wellbeing of people and families in Australia. 3

5 Authorised Users are required to upload to Dataverse, under permissive copyright (CC BY 3.0 AU license), any final Research Material produced using the dataset, within 30 days of being publicly available, including and not limited to: Journal article Book/chapter Paper Abstract Presentation Print article Editorial Interview Webinar Video Training material. Authorised Users should consider all possible privacy implications of publishing any research materials that could result in individuals in the dataset being identified. Authorised Users must adhere to the DSS Data Confidentialisation Policy. It is acknowledged that research conducted for the purpose of internal administration of Australian Government agencies or for confidential business purposes of the Australian Government is not always made public, and in such instances would be exempt from this requirement. You may request an exemption or extension to the time period for publishing research material (for example, if there are Intellectual Property related issues) by contacting the NCLD. Document Object Identifier (DOI) All datasets, research materials and replication materials uploaded to the NCLD Research Materials Dataverse will be given an automatically generated DOI (if necessary). The DOI system provides a technical and social infrastructure for the registration and use of persistent interoperable identifiers for use on digital networks into the future. Once published, Research Materials will be permanently archived on the NCLD Research Materials Dataverse, meaning that outputs, code, documentation and data will be in the public domain and should be edited carefully. Please refer to the Research Materials Upload QRG for further information on how to upload Research Materials. Replication Materials DSS encourages Authorised Users to consider their ethical obligation to facilitate analytical transparency so that their work can be tested or replicated, with due consideration of the following principles: Authorised Users should offer a full account of the procedures used to manipulate the data. Authorised Users should provide a full account of how they draw their analytical conclusions from the data (i.e. publishing replication code). No unit record data should be provided in the replication materials. Authorised Users are encouraged to spend time preparing their replication materials, in particular developing usable documentation for eventual users of their replication package. Replication Materials are requested for all analyses supporting any publicly reported (attributed) results, including (but not limited to) quantitative results, simulations, and qualitative analyses. 4

6 DSS reserves the right to audit the quality of the replication materials. Where serious or repeat replication errors occur, DSS may choose to suspend the access of the Authorised User. Authorised Users are asked to provide sufficient information to replicate their results noting full disclosure may increase the utility of the research, leading to increased citation, which also elevates scientific rigour. Upload guidelines 1. In summary, a replication package should contain: a. A brief README.txt file that summarises the materials that are part of the replication package (see detail below). b. Well-documented and well-named code for producing the publicly available results. c. Documentation so that replicators know how to use the data and code to reproduce the publicly available results. 2. Any self-generated data necessary to reproduce publicly available results can be provided directly to DSS for verification purposes. a. At DSS discretion, and on the written agreement of the Authorised User, any self-generated data (such as linked variables) can be made available on Dataverse as a controlled access file, mitigating any possible privacy risk such data might create. 3. To facilitate ease of replication, the README.txt file should include, at a minimum: a. Table of contents: a brief description of every file in the replication folder. b. Notes for each table and figure: a short list of where replicators will find the code needed to replicate all parts of the results. c. Base software dependencies: a list of all software required for replication, including the version of software used by the author (e.g. Stata 11.1, R , 32bit Windows 7, OSX ), and references to specialised software packages, modules, or routines that are not a standard component of publicrelease, off-the-shelf software. d. Additional dependencies: a list of all libraries or added functions required for replication, as well as the versions of the libraries and functions that were used and the location from which those libraries and functions were obtained. e. Seed locations: Please set seeds in your code for any analyses that employ randomness (i.e. simulations or bootstrapped standard errors). i. The README.txt file should include a list of locations where seeds are set in the analyses so that replicators can find and change the seeds to check the robustness of the results. Acknowledgement of Use The Australian Government owns all intellectual property rights in the data. Under the Terms and Conditions of Use, Authorised Users have agreed to acknowledge DSS and the relevant Study Providers in all Research Material. The Household, Income and Labour Dynamics in Australia (HILDA) Survey If you have used HILDA data in your research, you must include the relevant data release DOI (obtainable from Dataverse) and the following paragraph This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Survey was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the author and should not be attributed to the Australian Government, DSS or the Melbourne Institute. 5

7 Growing up in Australia: The Longitudinal Study of Australian Children (LSAC) If you have used LSAC data in your research, you must include the relevant data release DOI (obtainable from Dataverse) and the following paragraph This paper uses unit record data from Growing Up in Australia, the Longitudinal Study of Australian Children. The study is conducted in partnership between the Department of Social Services (DSS), the Australian Institute of Family Studies (AIFS) and the Australian Bureau of Statistics (ABS). The findings and views reported in this paper are those of the author and should not be attributed to the Australian Government, DSS, AIFS or the ABS. Footprints in Time: The Longitudinal Study of Indigenous Children (LSIC) If you have used LSIC data in your research, you must include the relevant data release DOI (obtainable from Dataverse) and the following paragraph This paper uses unit record data from the Longitudinal Study of Indigenous Children (LSIC). LSIC was initiated and is funded and managed by the Australian Government Department of Social Services (DSS). The findings and views reported in this paper, however, are those of the author and should not be attributed to the Australian Government, DSS or the Indigenous or non-indigenous people and their communities involved in the study. Building a New Life in Australia (BNLA): The Longitudinal Study of Humanitarian Migrants If you have used BNLA data in your research, you must include the relevant data release DOI (obtainable from Dataverse) and the following paragraph This paper uses unit record data from the Building a New Life in Australia (BNLA), the Longitudinal Study of Humanitarian Migrants. The study is funded by the Australian Government Department of Social Services (DSS) and is conducted in partnership with the Australian Institute of Family Studies (AIFS). The findings and views reported in this paper, however, are those of the author and should not be attributed to the Australian Government, DSS or AIFS. Notes If data from more than one of the surveys, each survey must be acknowledged. The word paper may be changed to better describe the research. If an Authorised User wishes to use different wording, they must seek prior written approval from DSS, unless they are publishing research on behalf of one of the institutions or organisations listed, in which case they may amend the acknowledgement text accordingly. 6

8 Appendix 1 Terms and Conditions of Use The Department of Social Services (DSS) on behalf of the Australian Government undertakes research and policy development to support its objectives of building the capacity and wellbeing of individuals, families and communities. To support its objectives, DSS funds a number of longitudinal studies for research purposes and to inform Australian Government policy. DSS will provide access to the nominated Dataset only if the individual requesting access undertakes to comply with the Terms and Conditions of Use outlined in this document. Individuals must accurately identify themselves when interacting with any entity or technology supporting access to DSS funded longitudinal data. Applications must accurately reflect the intended use of the Dataset. DSS either directly or through an entity delivering services on its behalf, may seek to verify an applicant s identity and/or confirm the intended use of the Dataset. Access, Use and Storage 1. The Authorised User must acknowledge they hold a Position of Trust when accessing, using and storing the nominated Dataset. 2. The Authorised User must not: a. copy, send or provide the Dataset to non-authorised individuals b. publish any research materials that could result in individuals in the Dataset being identified i. Authorised Users must apply data confidentialisation or suppression techniques where the count refers to between one (1) and four (4) people ii. In addition to suppressing cells with values less than five, surrounding cells will need to be suppressed where it is possible to derive the suppressed cell s count. This is done to prevent the disclosure of a primary suppressed cell iii. Authorised Users may choose a greater threshold if appropriate c. perform any matching, sharing, merging or linkage of any Dataset or Unit Record Data with any other data without the prior written consent of DSS d. attempt to identify any individual in the Dataset e. use the ACARA My School institution level data (LSAC only) to calculate or publish material which ranks schools or creates league tables f. re-publish any Unit Record Data or any part of the Dataset other than to directly quote free text responses 1 on the basis that such usage does not reasonably identify any individual. i. Quotes may be accompanied by relevant Unit Record Data such as age or occupation if these details are required for meaningful interpretation but the Unit Record Data used must be the minimum required for the research purpose and must not identify any individual. 3. The Authorised User must only use the nominated Dataset for the primary purpose specified in the application form and must obtain written approval from DSS before using the Dataset for any other purpose. 4. The Authorised User acknowledges they have obtained and read the National Centre for Longitudinal Data Access and Use Protocols (the Protocols) and they: a. understand each of their obligations set out in the Protocols; and 1 For example, it is acceptable to report that One mother who has a Bachelor degree commented I want him to go to university and have a good career but it is not acceptable to report that One mother, who works as a Professor of Indigenous Studies at a university, commented I want him to go to university and have a good career. 7

9 b. will comply with each of the obligations in the Protocols. 5. If the Authorised User is unable or unwilling to comply with the obligations set out in these Terms and Conditions of Use, or in the Protocols, the Authorised User must immediately notify DSS and destroy, without limitation, all documents containing any Dataset or Unit Record Data in the possession, custody or control of the Authorised User. 6. In the event that these Terms and Conditions of Use are inconsistent with the Protocols, these Terms and Conditions of Use will prevail to the extent of any inconsistency. 7. DSS may amend these Terms and Conditions of Use from time to time at its absolute discretion and notify Authorised Users. 8. Only the Authorised User may view and access the Unit Record Data from the Dataset. 9. The Authorised User acknowledges and agrees to immediately notify DSS via if the Authorised User becomes aware of any unauthorised access to, or use or disclosure of, any Dataset or Unit Record Data. 10. The Authorised User agrees to notify DSS of, and co-operate with DSS, the ADA or the Office of the Australian Information Commissioner in the resolution of, any complaint alleging an interference with privacy. 11. The Authorised User must ensure that they include in any Research Material the acknowledgement text provided in the latest version of the Protocols. 12. The Authorised User must only store the Dataset by the following methods: a. On a cloud server which has been awarded Australian Signals Directorate (ASD) certification to provide cloud services; or b. On a secure network; or c. On a password protected removable drive; or d. On a local drive on password protected PC or laptop. 13. The Data Storage requirements outlined in the Protocols must be adhered to at all times. 14. At the point of downloading data files the Authorised User s IP address will be captured as a point of verification of location. Authorised Users in some locations, or unspecified locations, will not be permitted to download data files without further verification. 15. For the purposes of data access, or to facilitate ongoing user support, including responding to user queries, Authorised Users addresses may be provided to DSS study partners: a. Melbourne Institute of Applied Economic and Social Research (HILDA). b. Australian Institute of Family Studies (LSAC). c. Australian Bureau of Statistics (BNLA). Supporting legislation 16. The Authorised User acknowledges that unauthorised disclosure of information owned by the Australian Government is subject to the sanction of criminal law under section 79 of the Crimes Act The Authorised User agrees to comply with the law in force in the Australian Capital Territory (Australia), including but not limited to: a. Social Security Act 1991; b. Social Security (Administration) Act 1999; c. Criminal Code Act 1995; and d. Privacy Act 1988 (Cth) (the Privacy Act). 8

10 18. The Authorised User agrees to have regard to the provisions of the Privacy Act, including the Australian Privacy Principles. 19. The Australian Government and the ADA shall not be held responsible for the accuracy and completeness of the material supplied, including any Research Materials and any Replication Materials. 20. The Authorised User agrees that the Australian Government owns all Intellectual Property rights in the Dataset. Research and Replication Materials 21. The Authorised User must upload to the NCLD Research Materials Dataverse, and make publicly accessible under permissive copyright (CC BY 3.0 AU license), any Research Materials produced by the Authorised User using the Dataset within 30 days of being publicly available (noting exceptions in Clauses 23 and 29). 22. The Authorised User agrees to upload to the NCLD Research Materials Dataverse, and make publicly accessible, any Replication Materials as specified in the DSS replication materials protocol described in the Protocols within 30 days of research findings being publicly available (noting exceptions in Clauses 23 and 29). 23. It is acknowledged that research conducted for the purpose of internal administration of Australian Government agencies or for confidential business purposes of the Australian Government is not always made public, and in such instances would be exempt from clauses 21 and 22. Authorised Training Activities 24. Instructors can only deliver Authorised Training Activities on the written agreement of DSS. An Instructor must be an Authorised User. 25. An Instructor may copy or reproduce a Dataset to create a Training Dataset for Authorised Training Activities, but may not copy or reproduce the source data for any other reasons (e.g. provide a copy of the source Dataset to an unauthorised person). 26. Instructors may provide a copy of the Training Dataset to Students undertaking Authorised Training Activities. A Student must be an Authorised User. 27. Students undertaking Authorised Training Activities must only access and use the Training Dataset at the venue at which the training is being conducted and will not in any circumstances copy or transcribe the Training Dataset, or allow the Training Dataset to be copied or transcribed. 28. Students must not, without appropriate oversight from an Instructor, and with the written agreement of DSS: a. Perform any matching, sharing, merging or linkage of any Dataset with any other dataset; or b. Retain any copy of the Unit Record Data at the conclusion of the course. 29. Instructors and Students must not: a. Attempt to identify any individuals in a Dataset; or b. Publish in any form any part of the source Dataset or any training datasets; or c. Publish any research or analysis based on the source Dataset, except on the written agreement of DSS for inclusion in training materials only. Definitions and interpretation ADA means the Australian Data Archive, a department of the Australian National University, the entity which stores and manages access to the nominated Dataset on behalf of DSS. Authorised User means an individual who has undertaken to comply with these Terms and Conditions of Use and has been given permission by DSS to have access to, and sole use of, a nominated Dataset for the purpose specified in their application. 9

11 Authorised Training Activities means training modules that have been approved by DSS. Dataset means data and supporting materials relating to a longitudinal study that DSS authorises for publication on Dataverse, with a singular Digital Object Identifier (DOI). Dataverse means the online data access platform managed by the ADA. Instructor means any person who is responsible for delivering Authorised Training Activities that use any Dataset (or sub-set thereof). Position of Trust means an Authorised User who at all times abides by the clauses set out in these Terms and Conditions of Use. Research Material means any publicly available research output, including non-traditional research output (such as conference presenations), that utilises a Dataset. Please refer to the Protocols for full details. Replication Material means all material required to execute the statistical analyses or simulations that constitute the research results, specifically the code and supporting documentation that computes the publicly available results. Please refer to the Protocols for full details. Student means any person attending Authorised Training Activities that uses any Dataset (or sub-set thereof). Training Dataset means a modified Dataset in order to demonstrate data analysis, such as creating new derived data items, aggregating or manipulating data to create a Training Dataset. Unit Record Data means individual data records in a dataset including individual responses to questions, observations on an individual or linked personal records from another dataset. 10

12 Appendix 2 - Longitudinal Study of Indigenous Children data protocols In addition to the requirements specified in the Terms and Conditions of Use, all Authorised Users of the LSIC dataset should be guided by the National Health and Medical Research Council (NHMRC): Values and Ethics: Guidelines for Ethical Conduct in Aboriginal and Torres Strait Islander Health Research. A summary of these values appear in the table below. Spirit and Integrity Reciprocity Respect Equality Responsibility Survival and Protection That the research is approached with respect for the richness and integrity of cultural inheritance and that research exhibits credibility in intent and process. That the research is inclusive, demonstrates an equitable and respectful engagement with peoples, values and cultures and advances the interests of Australian Indigenous people in ways that are valued. That the research acknowledges individual and collective contributions, interests and aspirations and acknowledges the right to have different values, norms and aspirations at all stages, including the consequences of research. That the research recognizes the equality and value of Aboriginal Torres Strait Islander knowledge and wisdom; that all partners are equal and there is an equal distribution of benefit. That the research does no harm to Indigenous individuals/communities or things they value and is accountable to individuals, families and communities especially in relation to cultural and social dimensions. That the research recognises and values Indigenous people; the importance of the personal and collective bond, and cultural distinctiveness and does not diminish the right to assert or enjoy that distinctiveness. Three key principles of working with the LSIC data are discussed below. These principles have been developed in consultation with a subcommittee of Aboriginal members from the LSIC Steering Committee. Prospective applicants and Authorised Users are encouraged to contact the DSS LSIC team for advice about any aspect of these protocols or for support or ideas about enhancing their cultural competency in interpreting and reporting the data. LSIC staff can be contacted at NCLD@dss.gov.au DSS, in partnership with the LSIC Steering Committee, may review LSIC data outputs (post-publication) for adherence to culturally sensitive practices in the analysis, interpretation and reporting of data. Principle 1 Acknowledge Standpoint when applying for and reporting LSIC data Applicants and Authorised Users must openly acknowledge their Standpoint in the application and in the reporting of data outputs in reports or publications. This is a declaration of the context in which the data analysis is being generated, including institutional context and personal context. Professor Maggie Walter 2 writes about Standpoint in social science research as follows: How we see the world is not a neutral, objective understanding, but is inevitably influenced by the filters and frames of our life experiences and circumstances and our social, cultural, economic, and personal identity location... Our Standpoint who we are socially, economically, culturally, even politically underpins the questions we see, the answers we seek, the way we go about seeking those answers, and the interpretation we make, the theoretical paradigms that make sense to us (p.11) 2 Walter, M. (ed.) (2009). Social Research Methods: An Australian perspective, Oxford University Press, Melbourne. 11

13 Declaring openly one s Standpoint requires a researcher to become conscious of who they are and their embedded ways of making sense of the world around them. By acknowledging their standpoint, the researcher also allows others to understand the way the researcher has approached, analysed and interpreted the LSIC data. Indigenous Authorised Users may have a different worldview on many topics from their non-indigenous colleagues; people in different academic disciplines are likely to view the dataset from different perspectives, as might government researchers compared to community-based ones. In summary, this principle states that the LSIC Authorised User needs to acknowledge their institutional context (such as university, government department, community organisation or cross-sector partnership), as well as the personal context, such as cultural background, work background, depth of experience liaising with Aboriginal and Torres Strait Islander people and prior research/publications in the area. Principle 2 Cultural competency In addition to having social research method competency and self-reflective capacity, LSIC Authorised Users should strive to be culturally competent. Cultural competency refers to the need to respect, understand and acknowledge the benefits, values and realities of Indigenous people and communities. This includes being mindful of Indigenous people s right to have different values, norms and aspirations to non-indigenous people. Analysts should recognise that Indigenous communities are diverse, with different languages, cultures, histories and perspectives, and acknowledge the diversity of individuals within these communities. This diversity should be understood and appreciated in the analysis, interpretation and reporting of the data. The findings derived from the LSIC data should not be extrapolated to all Indigenous people. Whilst the LSIC sample is reflective of a diverse range of Aboriginal and Torres Strait Islander people within the research sites, and covers remote, regional and urban areas, the study was not designed to be nationally representative of all Indigenous people in Australia. Rather, the study was intended to provide an in-depth understanding of the holistic nature of Indigenous children s pathways in growing up. Other data sources, such as the ABS National Aboriginal and Torres Strait Islander Social Survey (NATSISS) 2008, can be used to provide a nationally representative snapshot of Indigenous children s social circumstances. Associate Professor Karen Martin 3 (2008, p.133) offers some key parameters the researchers can use to selfregulate their behaviour and enhance their cultural accountability. Martin suggests that all researchers must show respect for land, laws, elders, culture, community, families and support Indigenous people s visions for their futures. Cultural respect is the important element emphasised by Martin and one that LSIC Authorised Users should demonstrate. The researchers need to demonstrate responsible and accountable behaviour in the way they manage their research projects which respects the Aboriginal and Torres Strait Islander families who have openly shared personal information that has allowed the building of the dataset. This can be a process of self-regulation where one actively takes the time to come alongside (a phrase suggested by Martin) the issue being researched. This means implicating oneself in understanding more deeply the Indigenous perspective on the topic at hand rather than treating the data purely as an external object of science that can be expertly known at a distance. Principle 3 Contributing knowledge to build better outcomes Sharing findings from the LSIC data is an essential component of being accountable to the Aboriginal and Torres Strait Islander people and communities who have given their time in the hope that LSIC would build better outcomes for their children and families. Greater accessibility of the final research material generated from the LSIC data (in association with the researcher s Standpoint) will improve the quality of the analysis and interpretation of the data. LSIC Authorised Users should work to meet the Research Materials requirements so that the Department can honour its commitment to give Aboriginal and Torres Strait Islander peoples and 3 Martin, K. (2008). Please knock before you enter: Aboriginal regulation of outsiders and the implications for researchers, Post Pressed, Teneriffe, Queensland. 12

14 communities (particularly those involved in the study) feedback on how the data are being used and a summary of research findings. Appendix 3 - Authorised Training Activities In addition to the Terms and Conditions of Use (clauses 24 through 29 Appendix 1) Instructors and Students are required to adhere to the following processes. Instructors Instructors wishing to conduct training using any of the DSS longitudinal datasets must first apply as an Authorised User via Dataverse. It is important that Instructors select Data User Training Instructor as the primary purpose when requesting access. Once the application has been approved Instructors may modify the dataset in order to undertake data analysis (e.g. create new derived data items, aggregate and manipulate the data to create the relevant training dataset). The Instructor can distribute the derived dataset to Students at the venue at which the training is being conducted, provided the Student is an Authorised User (see below for details). Students Students must apply as an Authorised User via Dataverse. It is important that students select Data User Training Participant as the primary purpose when requesting access. Students will receive the relevant training dataset from the Instructor. Under the Terms and Conditions of Use (which must be accepted when applying for a dataset), students must only access and use the relevant training dataset at the venue at which the training is being conducted, under the supervision of the Instructor. They must not in any circumstances copy or transcribe the dataset, or allow the dataset to be copied or transcribed. 13

15 Appendix 4 - LSAC Australian Early Development Census (AEDC) linked Data Use of the LSAC-AEDC linked data is subject to Authorised Users following guidelines on conduct and publication of research as outlined in the AEDC Data Guidelines. The guidelines require Authorised Users to notify the Department of Education and Training of their intent to publish material using AEDC data ( support@aedc.gov.au). 14

16 Appendix 5 - HILDA-CNEF Datasets The HILDA-CNEF dataset is a subset of HILDA data developed specifically for use as part of the Cross-National Equivalent File (CNEF). The CNEF contains equivalently defined variables for the following panel studies: Panel Study of Income Dynamics (USA), German Socio-Economic Panel, British Household Panel Study, Canadian Survey of Labour and Income Dynamics, The Household, Income and Labour Dynamics in Australia (HILDA) Survey, Swiss Household Panel, Korea Labour and Income Panel Study, The Russia Longitudinal Monitoring Survey-Higher School of Economics. The datasets are designed to allow cross-national researchers, not experienced in panel data analysis, to have access to a simplified version of these panel data, while providing experienced panel data users with guidelines for formulating equivalent variables across countries. Most importantly, the CNEF provides a set of constructed variables (for example pre-and post-government income and international household equivalence weights) that are not directly available in the original datasets. Access policies for the datasets within the CNEF vary depending upon the administrative requirements of the individual surveys from which the datasets are taken. DSS is only responsible for approving access to the HILDA- CNEF. Details on how to order the CNEF data for other surveys can be viewed on the Ohio State University CNEF website: < Access to the HILDA-CNEF data is obtained by applying via the HILDA-CNEF Dataverse. If the application is approved DSS will provide the Authorised User s details to the CNEF team at Ohio State University; however, it is the responsibility of the Authorised User to contact the CNEF team at Ohio State University to organise shipment of the CNEF datasets <CNEF@osu.edu> or Tel: Columbus, Ohio USA. The cost for obtaining the set of CDs with all of the CNEF datasets is US$125 at the time of publication, but it is advisable to check this at the time of ordering the CDs. This fee is payable to the CNEF team at Ohio State University. This cost may change at any time. 15