Logic models are a well-defined means to help people plan impactful projects and can help in the design of data access initiatives.
In our Data infrastructure for common challenges project, we have been exploring the activities of ‘data access initiatives’. Data access initiatives are programmes of work that aim to address a specific challenge by increasing access to data. You can read more about them here.
But how can these initiatives identify the data infrastructure required to address a range of social, environment or economic challenges? To understand these initiatives, we’ve been exploring several different design tools and frameworks.
This blog post is part of a short series that shares how a range of tools and frameworks might help us to design impactful initiatives.
In this post, we look at logic models.
What are logic models?
Logic models are tools designed to help people plan impact projects and communicate those plans to others. They provide a structured way of thinking about how to build a programme of activities that will help to address a specific problem or challenge – essential for designing a good data access initiative.
Logic models are sometimes presented in different ways, for example as tables or illustrations, but they always consist of the same key elements.
- Inputs. The resources that are necessary for an initiative to carry out its planned work, such as funding, access to existing datasets or use of specific platforms and technologies.
- Activities. The specific tasks that those working in the initiative will undertake which will help to create the design outcomes and impacts. These might be creating new data infrastructure by harmonising and standardising different datasets; supporting the use of data and identifying data user needs; or engaging with communities of publishers and data users.
- Outputs. The tools, knowledge, products or services that are produced by those activities, such as new data standards, aggregated datasets, or new tools and algorithms.
- Outcomes. The expected results of the initiative. These are often expressed in terms of changes in knowledge, attitudes or practices of a group of individuals. For example, increasing data sharing by specific stakeholders, or the development of new products and services using data.
- Impact. The intended long-term results from the initiative. For example better informed decisions around climate policies, increased efficiency in the energy system, or improved health and wellbeing.
Logic models help us to think through and plan how our resources and activities can create impact. Along the way, we can document our assumptions and help to identify where to collect metrics to measure progress. Articulating the assumptions that each step depends on will help initiatives reflect, iterate and adapt to external changes.
How are logic models being used?
At the Open Data Institute (ODI), we have often applied logic models to our own programmes and projects, including OpenActive – a community-led initiative to help people get active using open data. Here’s an example of some of the activities, outputs and outcomes we’ve planned in that programme:
- Our activities have included things like:
- Developing open standards to support publication of open ‘opportunity data’ – data about the various services activity and leisure providers have available
- Developing a booking standard, to allow new products and services to book classes and places for people in existing standards
- Supporting data providers and platforms in understanding how to publish data and implement the standards
- Building tools to support data users in finding and using data
- Running an open-data-champions programme to advocate for more open data
- Offering training around open data and standards
- Running an innovation programme to encourage the creation of new products and services
- Those activities have produced outputs, which includes:
- Openly licensed standards and specifications
- Open-source software and freely available tools
- Case studies that describe successful use of data
- The outcomes from the programme are described in our recent evaluation and case study for the programme
- And ultimately, the intended impact is to address the problem of inactivity in England by helping people get active
Based on our experience, logic models are a useful technique for helping to design new data initiatives. In our research we’ve also found them to be a helpful tool for documenting existing initiatives, helping us gain insight into the initiatives’ activities and outputs.
Logic models should ideally be developed as collaboratively as possible to ensure that there is a well-rounded set of activities that will collectively support communities and organisations in addressing common challenges.
Guides and templates
If you are looking to create a logic model for your data initiative, there are numerous guides and templates available.
- We like Nesta’s DIY Theory of Change Toolkit, and have used it when designing our Data Challenge Prizes for Health Playbook.
- For a more complex and detailed guide the Logic Model Development Guide by the W.K. Kellogg Foundation provides an exhaustive and foundational guide of how logic models can help design, implement and evaluate programmes.
Have you used logic models?
If you’ve used logic models to help design your data access initiative, then let us know where you’ve found them to be useful or have insights about how to ensure they’re well designed.
One of our next activities is identifying a range of common activities used across initiatives when they are building data infrastructure, to help others to plan and prioritise similar activities.
We’d also be interested to talk to you about how using logic models or other frameworks might help you improve an initiative you’ve already engaged with. Get in touch.