Snippet #2 - Supporting the Ethical Management of Research Data
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Stringer, Glynn
Healey, Angelica
Presenters Glynn Stringer and Angelica Healey discuss the systems in use (or in development) at UniSA to support the management and use of research data ethically. Please note that the research project shown during the webinar is artificial and no actual research data sets or information is displayed. Ethical clearance is a critical step in the research data life-cycle to ensure that data collected and used during the course of research meets the expected ethical standard under the terms of the Australian Code for the Responsible Conduct of Research and the National Statement on Ethical Conduct in Human Research. Systems that support ethical clearance and continual monitoring of data management and usage are thus critical to maintaining the ethical standard and integrity of research within an institution. Moreover, some research data can have long lasting social, cultural, or scientific value well beyond the completion of a research project. Keeping accurate records of the ethical and legal constraints as well as the permissions around research data are thus necessary steps to ensure that the value of data is preserved.
 Angelica and I are going to talk through research data and how it best be managed and we're going to talk a bit about more about our systems. So what we're going to cover is the principles and approach we've taken at UniSA. I'll go into a bit how that fits into the research life cycle and then we'll show a demonstration of how we bring together legal and ethical information so we can effectively manage research data throughout that life cycle. And then finally I'll go through where we're going next with this capability. So the first thing with the principles and approach is that wherever possible we've tried to minimise administrative overhead. The way that research and research data are moving means that more will be asked of researchers to support the sharing of research data. So wherever we can we should try and reuse information and reduce those overheads for the researcher. We're also trying to do that for the support staff that support them. The other principle is that we are trying to maximise flexibility. So we use dynamic content wherever we can. An example of that is that we have an online human ethics application form which our research is used to apply for ethics approval. We also support both physical and digital data. So the systems we've created aren't just about digital data, they're about physical objects and also about primary materials, whether that be an artwork or blood samples, etc. we can point to where they are as well as pointing to the locations for digital data. The other important point with the digital data is that we allow for different versions of the same data. I'll give you an example. So if we have data that's non-identifiable data, that will have different conditions attached to it to the identifiable data. So I've stolen an earlier version of Anne's life cycle diagram and that maps with our approach to managing research data. But we collect information throughout that life cycle so at the end we can dispose of it, archived it, etc. Our system, we have a research data management framework which sits in the centre of all this. The one exception that it doesn't touch is the reporting to funders because that is managed through our research administration systems. But everywhere else it touches each element of the cycle, I should say. So what does it look like? Research master is our research administration system and that's where we have, for example, online human ethics applications and manage the research activities. Research details are passed through to our data management planning system and then metadata is passed to our research metadata system which in turn puts information up to research data Australia. But importantly we only pass that metadata that is releasable. So for various reasons researchers may have information they don't want to share until they've completed their research project. So that's why I put the caveat on there that it has to be releasable. Below we have a data access portal and again the research metadata that's releasable is passed to the data access portal and there's a link from ANS back to our data access portal when data can be made open. So I wanted to show you what our data management planning system actually looks like. So this first screen is a project details screen. Normally this would be pre-populated from Research Master but for the purposes of this webinar we've pre-populated a project. We've allowed the flexibility for information to be entered as a project before it gets into Research Master and also for data to come across from Research Master. So in here we can enter all the standard sort of information about the research project. Importantly down the bottom here there's a confidentiality setting so that if for whatever reason the project has to be confidential either for contractual or because of some other condition that the researcher wants to manage. We then have information about the legal aspects of the activity which is in our IP storage and security. So in here we can put in what conditions are in the project contract and that may be a funding agreement, contract or other legal document. So here we can summarise the information that we get from that. So we get the ownership of the data in this case so I've clicked that it's solely owned by the university but we can add other parties to this as well. So we could say jointly owned by the university and add other organisations. We can also say that the data created by the project is subject to particular intellectual property conditions and that includes both the project IP but also importantly in my view background and third party IP in that it provides a record of those aspects related to the research project. We then have the rights and restrictions and this is where we can set licensing conditions relating to that research project. So for example up here I've put a conditional access with access to the data requires and ethics approval. So this particular project we're assuming requires, includes some participant surveys or something along those lines. We then have the ability to add embargoes and we can add multiple embargoes. What we do as a default is we set the embargo to be completion of a project plus one year and that's just to allow enough time for the researchers to complete their publication activity and to basically do any housekeeping they need to do on the data before they share it. Now the embargo can be just because we've set it to the length of project plus a year, if the researcher has a need we can actually change that embargo period so that the metadata for example can be released. And finally related to ethics we have a retention tab and in this retention area we can identify how long as a minimum the data must be held. So for example by default it's set to five years and I should say that these conditions are driven by both the Australian Code and also the legislative requirements of the State of South Australia. So the record keeping requirements of the State of South Australia are taken into account in here. If for example I select a clinical trial then the retention period is set to 15 years. However if I set that it also contains gene therapy for example then the retention period is set to permanent. In this way we're trying to keep it as simple as possible but for example this retention period information is used by our IT department to make sure that the records are retained. And then just below that this is where we can record where the data created by the project is stored. So in this case firstly there's a physical location which for example I've chosen the three drawer filing cabinet which happens to be in a particular building, on a particular floor, in a particular room. Similarly we can have a URL for this example I've chosen a SharePoint site. So just to remind you this shows you again the framework that we've created and where we're going from here is that we want to make the relationship between online ethics and the data management planning system more integrated. So to do this we intend to create a cross link which will allow for example if there's a data management plan that can be, the information from the data management plan can be used to populate the human ethics application so that the researcher doesn't have to reenter that information. Conversely if they've entered the information in the human ethics application we want to import that into the data management planning system so that we don't have to double enter that. We have held off on this cross link because of the changes that have been made at the NHMRC with the human research ethics application form. Thank you.
 Angelica and I are going to talk through research data and how it best be managed and we're going to talk a bit about more about our systems.  So what we're going to cover is the principles and approach we've taken at UniSA.  I'll go into a bit how that fits into the research life cycle and then we'll show a demonstration of how we bring together legal and ethical information  so we can effectively manage research data throughout that life cycle.  And then finally I'll go through where we're going next with this capability.  So the first thing with the principles and approach is that wherever possible we've tried to minimise administrative overhead.  The way that research and research data are moving means that more will be asked of researchers to support the sharing of research data.  So wherever we can we should try and reuse information and reduce those overheads for the researcher.  We're also trying to do that for the support staff that support them.  The other principle is that we are trying to maximise flexibility.  So we use dynamic content wherever we can.  An example of that is that we have an online human ethics application form which our research is used to apply for ethics approval.  We also support both physical and digital data.  So the systems we've created aren't just about digital data, they're about physical objects and also about primary materials,  whether that be an artwork or blood samples, etc. we can point to where they are as well as pointing to the locations for digital data.  The other important point with the digital data is that we allow for different versions of the same data.  I'll give you an example.  So if we have data that's non-identifiable data, that will have different conditions attached to it to the identifiable data.  So I've stolen an earlier version of Anne's life cycle diagram and that maps with our approach to managing research data.  But we collect information throughout that life cycle so at the end we can dispose of it, archived it, etc.  Our system, we have a research data management framework which sits in the centre of all this.  The one exception that it doesn't touch is the reporting to funders because that is managed through our research administration systems.  But everywhere else it touches each element of the cycle, I should say.  So what does it look like?  Research master is our research administration system and that's where we have, for example, online human ethics applications and manage the research activities.  Research details are passed through to our data management planning system and then metadata is passed to our research metadata system  which in turn puts information up to research data Australia.  But importantly we only pass that metadata that is releasable.  So for various reasons researchers may have information they don't want to share until they've completed their research project.  So that's why I put the caveat on there that it has to be releasable.  Below we have a data access portal and again the research metadata that's releasable is passed to the data access portal  and there's a link from ANS back to our data access portal when data can be made open.  So I wanted to show you what our data management planning system actually looks like.  So this first screen is a project details screen.  Normally this would be pre-populated from Research Master but for the purposes of this webinar we've pre-populated a project.  We've allowed the flexibility for information to be entered as a project before it gets into Research Master  and also for data to come across from Research Master.  So in here we can enter all the standard sort of information about the research project.  Importantly down the bottom here there's a confidentiality setting so that if for whatever reason the project has to be confidential  either for contractual or because of some other condition that the researcher wants to manage.  We then have information about the legal aspects of the activity which is in our IP storage and security.  So in here we can put in what conditions are in the project contract and that may be a funding agreement,  contract or other legal document.  So here we can summarise the information that we get from that.  So we get the ownership of the data in this case so I've clicked that it's solely owned by the university  but we can add other parties to this as well.  So we could say jointly owned by the university and add other organisations.  We can also say that the data created by the project is subject to particular intellectual property conditions  and that includes both the project IP but also importantly in my view background and third party IP  in that it provides a record of those aspects related to the research project.  We then have the rights and restrictions and this is where we can set licensing conditions relating to that research project.  So for example up here I've put a conditional access with access to the data requires and ethics approval.  So this particular project we're assuming requires, includes some participant surveys or something along those lines.  We then have the ability to add embargoes and we can add multiple embargoes.  What we do as a default is we set the embargo to be completion of a project plus one year  and that's just to allow enough time for the researchers to complete their publication activity  and to basically do any housekeeping they need to do on the data before they share it.  Now the embargo can be just because we've set it to the length of project plus a year,  if the researcher has a need we can actually change that embargo period so that the metadata for example can be released.  And finally related to ethics we have a retention tab and in this retention area we can identify how long as a minimum the data must be held.  So for example by default it's set to five years and I should say that these conditions are driven by both the Australian Code  and also the legislative requirements of the State of South Australia.  So the record keeping requirements of the State of South Australia are taken into account in here.  If for example I select a clinical trial then the retention period is set to 15 years.  However if I set that it also contains gene therapy for example then the retention period is set to permanent.  In this way we're trying to keep it as simple as possible but for example this retention period information is used by our IT department  to make sure that the records are retained.  And then just below that this is where we can record where the data created by the project is stored.  So in this case firstly there's a physical location which for example I've chosen the three drawer filing cabinet which happens to be in a particular building,  on a particular floor, in a particular room.  Similarly we can have a URL for this example I've chosen a SharePoint site.  So just to remind you this shows you again the framework that we've created and where we're going from here is that we want to make the relationship  between online ethics and the data management planning system more integrated.  So to do this we intend to create a cross link which will allow for example if there's a data management plan that can be,  the information from the data management plan can be used to populate the human ethics application so that the researcher doesn't have to reenter that information.  Conversely if they've entered the information in the human ethics application we want to import that into the data management planning system so that we don't have to double enter that.  We have held off on this cross link because of the changes that have been made at the NHMRC with the human research ethics application form.  Thank you.
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