There are many benefits to sharing model code and data in open access repositories. These benefits include helping to: demonstrate study reproducibility; improve model transparency; elicit feedback; identify errors; increase impact; and reduce duplication of effort across the mental health modelling field. However, there are also practical barriers to sharing model code and data in an appropriate manner. These barriers can include: concerns about data confidentiality and privacy; confusion about licensing; the need to identify appropriate storage and dissemination platforms; the time and effort required to prepare, document and curate content for public release; and lack of technical knowledge.
1. Objectives On completion of this tutorial you should be able to: Understand basic concepts relating to the Australian Mental Health Systems Models Dataverse Collection; and Have the ability to search for, download and ingest files contained in Dataverse Datasets that are linked to by the Australian Mental Health Systems Models Dataverse Collection using two alternative approaches; Using a web based interface; and Using R commands. 2. Prerequisites You can complete most of this tutorial without any specialist skills or software other than having a web-browser connected to the Internet.
To facilitate the sharing of model data by the Australian mental health modelling community, Acumen curates an open access data repository. The data repository is the Australian Mental Health Systems Models Dataverse. If you have data from a mental health modelling project that you would like to share via this repository, check out this tutorial about how to do so.
To facilitate the sharing of model code by the Australian mental health modelling community, Acumen curates an open access code repository. The code repository is the Australian Mental Health Systems Models Zenodo Community. Linked to this repository is Acumen’s GitHub organisation. Currently our GitHub organisation is just used to host the source code for this website, but over time we aim to use it to share brief code snippets that may not be appropriate for archiving in our Zenodo repository.
A mental health systems model is a mathematical representation of the systems (economic, environmental, service, social and technical) that shape population mental health. These mathematical representations can be succinct (a brief mathematical formula) or highly detailed (complex networks of linked equations expressed as large bodies of computer code). When applied to relevant data, these models can produce insights to help planners and policy makers address a range of decision problems.