Direct support phase I
Our story so far…
Our story so far…
In July 2015, the DataShift team announced its first call for applications for direct support in the three pilot areas – Argentina, Nepal and Kenya+Tanzania. This marked the beginning of DataShift direct support phase I. Here’s our story of what we did, what we learned, and where we’re headed.
DataShift provides direct support to organisations so they can upgrade, supercharge or complete their projects, by strengthening their capacity to produce citizen-generated data. Through our direct support, we are also building a global community of peers and champions of citizen-generated data (CGD). For the first phase, our goals were both practical and strategic.
Practically, we wanted to provide meaningful, useful support on citizen-generated data projects by matchmaking experts and organisations, developing CGD strategies, understanding organisational needs, and bringing in external expertise to complement existing capacity where needed.
This included providing a wide range of things that organisations told us they needed – from tools (mobile phones, survey platforms), to technical assistance (programmers, UX experts), and from strategic assistance (data and privacy policies) to domain expertise (data visualisation, data-driven journalism). We also aimed to plant the first seeds of a DataShift-coordinated global community of citizen-generated data initiatives that crossed borders, cultures and languages.
Strategically, we wanted to test our assumptions about what type of support would be most beneficial for CGD initiatives. The first phase of direct support was purposefully broad and demand-driven to help us answer some crucial questions about how DataShift could best provide direct support to civil society organisations using CGD:
It’s important to mention that the direct support budget was very limited: the average budget for each direct support project was around 5000 USD. With limited resources and a large, and largely unknown playing field, it would have been safest to provide in-depth, long-term support for a small handful of projects. However, that would have limited our ability to learn and test our assumptions. In the long term, it would have given us a much more limited understanding of how CGD could grow on a global scale.
So, we decided to spread out DataShift support as widely as we could, covering as much geographic and substantive ground as possible. We used DataShift’s internal expertise and capacity to make our available resources as useful as possible, and prioritised planning and needs assessments to the DataShift direct support partners, to make sure our limited support would be as beneficial as possible. We published a condensed version of our approach in a post called “Walking the Walk: the DataShift direct support activities”.
The three areas selected for DataShift activities are Argentina, Kenya+Tanzania, and Nepal. The main dimensions we took into consideration when selecting the areas were:
For Argentina in particular, we could count on DataShift partners, Wingu, to take the lead in identifying direct support partners and integrating direct support work in existing regional support processes – Wingu combined Desarrollando America Latina (DAL) with DataShift direct support, in order to reach a wide variety of CGD organisations. For Kenya+Tanzania and Nepal, the DataShift direct support team took the lead.
We had two separate calls for applications: one for Argentina, and one for the other pilot areas. Wingu took the lead in Argentina, and selected a group of candidates that followed the DAL process to develop or improve their projects. You can read more about the Argentina direct support on the Wingu website.
For Kenya+Tanzania and Nepal, we received more than thirty applications. We shortlisted organisations, then arranged meetings with each one. With projects that had sent a proposal we knew was a good fit, our meeting focused on identifying what support would be most useful, considering time and budget constraints. For other shortlisted organisations, we started with an exploratory meeting to better understand if and how our support would be beneficial. Then, if both the organisation and Datashift felt there was potential in partnering, we would move on to the needs assessment phase.
In the end, we selected nine organisations to support in Phase I:
Dimensiones de Derechos Umanos – Collecting data to promote public health in Argentina
Directorio Legislativo – Using diagnosis timelines to strengthen primary care facility training
Fundacion Conocimiento Abierto Argentina – Usable and reusable knowledge on Argentine public officials
La Nacion Data – Engaging users on an open-source crowdscraping platform
Africa’s Voices – Protecting and humanising data
HelpAge Kenya – Using longitudinal data to improve aid disbursement in Kenya
Ma3Route – Designing a data-driven user experience for a mobile traffic app
Shivyawatta/UDPK – Designing a mobile data collection system on public disability services in East Africa
Local Interventions Group – Verifying governmental resource allocation during post-earthquake recovery
And we’re off! The support projects were selected to fit two main criteria: how meaningful our support would be for them, and how much we could learn about the questions listed at the beginning of this blog post.
We gave a wide range of types of support to the projects, from user experience (UX) research and project management to advanced data analysis and mobile survey analysis. The extent of our support also varied considerably. Sometimes providing financial assistance to processes already in place, as with Local Interventions Group in Nepal, which had already identified appropriate people for the job, but lacked the resources to complete the project. Sometimes we identified and implemented the entire technological pipeline of a project, as with a disability perception survey in Kenya and Tanzania where we identified domain experts for methodology definition and project management, as well as service providers for providing survey platforms, mobile devices, training and customisation.
The implementation wasn’t without problems. Unsurprisingly; coordinating multiple projects across four continents and timezones, with different processes and goals, was a strain on internal DataShift capacity, and various contingencies (getting state approval for surveys in Kenya and Tanzania, or identifying experts with both time and capacity to transfer knowledge, besides doing a great job) meant that the initial six-month timeline was often stretched beyond – and in one or two cases even doubled – the original estimate.
To read in detail how the implementation phase went, please visit the Direct Support section of the DataShift website, where each support partner has its dedicated page. Our thanks go to the wonderful experts that helped us and our support partners:
The second goal of direct support was fostering and planting seeds for a DataShift community around citizen-generated data. For this reason, we decided to invite our project partners, together with experts who worked on the projects, to join us in a two-day event in Bogota, Colombia, preceding CIVICUS’ International Civil Society Week.
The direct support partners had the chance to present their work and DataShift support, as well as to participate in expert trainings from experts on data visualisation, campaigning strategies, and the Sustainable Development Goals. The main aspect of the event was connecting and sharing: we were very glad to see participants develop connections that outlasted the event itself, and are still going strong through the DataShift mailing list, the newsletter, and online webinars (as well as a very curious WhatsApp group that shares images of Buenos Aires sunsets and Nairobi traffic in the same breath).
If you want to know more about the event, DataShift partners The Engine Room wrote a blog post about the event and summarised key findings:
We think that running a series of successful support projects and planting seeds for the DataShift community is undoubtedly an achievement in and of itself. But how does the first phase of direct support translate into a strategic DataShift vision moving forward?
After analysing the learnings from Phase I of direct support, we identified the CGD area we want to support; we have decided to focus on a specific Sustainable Development Goal, SDG5, to start addressing meaningful ways of comparing and aggregating results. For the next phase, direct support will focus on supporting organisations to collect, manage, analyse and disseminate citizen-generated data with the goal of creating effective gender-related campaigns in four priority countries: Argentina, Kenya, Nepal and Tanzania. The direct support will be a combination of online and in-person cohort training that will be coordinated across all four priority countries, but led and conducted locally.
Our experience within pilot areas, as well as Wingu’s work on the ground, helped DataShift to define a model for scalability and sustainability that focuses on enabling country maturity and independence according to a sequence of programmatic steps: we envisage moving from the first step of central support to coordinating autonomous, self-organising regions by growing the capacity of interested and able in-country partners.
DataShift and its partners are committed to openly sharing and distributing as much information and software developed, collected and produced as possible, following principles of open source and open data, with the following limitations:
DataShift is currently finalising its open source and responsible data policy, and looks forward to sharing it soon.
We are more committed than ever to continue our work in enabling citizen-generated data across the world to meaningfully monitor and complement SDG implementation. Stay tuned for more information about direct support Phase II: