The important characteristics of this project were a strong pre-existing technical capacity and focus on communicating and supporting a very specific stakeholder. While data sharing was an area of interest it was secondary. This led to an interesting challenge. When the project team sought to identify an appropriate host for data they considered both domain specificity and technical appropriateness. In examining this they identified a gap in local provision for Open Data within Vietnam.

• The main intended audience for the outputs of a data-focussed project influence data collection and choices in Data Management and Sharing Processes.
• In developing and transitional contexts there is a tension between sharing data through international platforms for discoverability globally and provision of local platforms to enhance national and regional discoverability and capabilities.
• Technical capacity of a research group can be associated with the use of proprietary platforms that complicate the resource allocations for sharing data openly.

The Centre for Analysis and Forecasting is technically well equipped, using a variety of sophisticated tools for data gathering and management. They have in place a range of tools for managing and collecting data from surveys (rtSmartSurvey) which include capabilities for real time analytics as well as enabling follow up by phone.

The data was collected into internal MySQL database of the survey system from where it could be exported. The level of detail collected was very high including personally identifiable information on businesses and survey respondents. The project team was aware of the importance of recording information on codebooks and design of the survey (cite DMP). At the beginning of the Pilot Project there was less evidence of having considered issues of anonymisation of data. This is not surprising given that the focus of the project was on generating summary reports for the ECNA.

Overall the project team showed significant technical capacity in data analysis and handling. Concepts of data management were implicit rather than being developed explicitly as part of the project planning process.

The process of Data Management Planning was relatively slow. The final DMP (available in the project data package, Neylon 2017) largely recorded existing practice, which was reasonably robust. The DMP showed evidence of working through the issues of anonymisation and more broadly the implications of data sharing. The contributing team member noted (DMP interview) that dissemination processes had not previously been part of the planning for data collection.

The DMP was prepared using a Word Document generated from the DMP Assistant platform. This was more for convenience than due to network bandwidth issues. However it illustrates the preference that many groups have for preparing such documents offline rather than online.

The main system challenge related to the availability of a data sharing platform perceived as being appropriate for sharing the project’s data. Within economics there are large scale data resources (such as the World Bank) but few platforms for small scale data. While many economics research journals require data sharing on request this is generally in the form of spreadsheets or files and is not highly organised.

In addition the project team’s focus on supporting local policy making lead them to the view that setting up their own data sharing platform would be preferable. This raises the issue of local provision and capacity building and its potential tension with maximising the benefit of global investments in data sharing platforms.

The issue of appropriate sharing platforms has been raised above. An intriguing aspect of the challenges for the project team was related to their technical facility and the sophistication of their existing data handling procedures. There was good evidence of high quality practice with regard to documentation of process and of management of data resources and collection systems.

Nonetheless it appeared that in some ways the sophistication of the existing processes – the focus on delivering automated reports and efficient analysis – meant that when the focus shifted to data sharing in general there were challenges in modifying the existing workflows. Specifically the shift towards data sharing with unknown users for unknown purposes was a challenge. The project noted that “Open Data is a mindset – it is important to be nurtured” (final workshop presentation) and the importance of planning being embedded in the development of a research proposal.

The project was receptive throughout to the concept of data sharing and motivated to be effective in achieving this. As noted above the technical facility of the group and the existing workflows made the shift towards Open Data sharing challenging. The contributing project noted as its main challenge that resources were a limitation. In part this is likely due to the degree to which a reconsideration of workflows and documentation would become necessary.

This project demonstrates the importance of a careful balance between the signalling role of policy and implementation details. The aspirational aspects of a data sharing policy aligned with the goals of the contributing project well. However the details of implementation requirements could be expected to come into conflict with existing practice and workflows. In particular a shift in mindset from delivering reports and information to a specific stakeholder, and the systems put in place to facilitate that, towards more general availability creates specific challenges.

Similar situations would require significant support, guidance and flexibility in terms of implementation. The project exemplifies the risk that alignment with the overall agenda for change could be neutralised or even made antagonistic if detailed requirements were viewed as impractical or inappropriate. Providing both sufficient support throughout the project life cycle, from inception and planning through to evaluation, while also supporting flexible implementation is crucial if the overall policy goal of culture change is to be achieved.

Exploring the opportunities and challenges of implementing open research strategies within development institutions (Neylon and Chan 2016).