360Giving’s vision is for UK grantmaking to become more evidence-based, impactful and strategic. Their mission is to support UK grantmakers to publish information on who, where and what they fund in an open, standardised format to build a better picture of the funding landscape and boost its impact. They have created the 360Giving Standard so funders can share and compare this information.
Data Visualisation: truth or interpretation? (full version)
Data, and open data in particular, is supposed to represent the truth and objectivity, as well as introduce the facts in an unbiased way. However, the question of what ‘truth’ really means in the age of knowledge, information, and the Internet is debatable. How can a dataset be objective if someone created it with certain ideas in mind, having chosen a specific set of variables? Methodological choices in data collection and analysis are often crucial to determining the outcome and it is significant to acknowledge that perhaps objectivity in data is not as straightforward as it initially seems. Labelling anything as ‘unbiased’, ‘objective’ or ‘true’ is risky even with quantitative data or data visualisations - the limitations of the data selection and interpretation process can lead to different results depending on the person who performs it.
The issues of ‘truth’ have been discussed even hundreds of years before the emergence of the knowledge economy. For Nietzsche, there is no such thing as truth. There are only perspective and interpretation, motivated by a person’s interests or ‘will to power’. According to him, even the statement that everything is subjective is in itself an interpretation - the ‘subject’ is invented, which provokes a different set of questions such as whether it is necessary to identify the ‘interpreter’ behind the interpretation. Within the open data movement advocating for transparency and accountability, the ‘will to power’ is replaced by the will to expose the wrongdoings or promote a greater equality in the access to information. Yet, there are still various stakeholders pursuing different objectives that might differ despite the overarching ideas of openness and transparency. With this in mind, we believe that revealing the reasoning behind the interpretation of the data is important and this is what we advocate for in our Digging the Data Visualisation Challenge.
In the challenge, through giving the participants freedom of analysis, we encourage a variety of perspectives and interpretations of our data. We invite the participants to tailor and shape the questions according to their creative vision. It is the format of data visualizations in particular that facilitates this crowdsourcing of creative ideas and unique analysis of the wealth of our grant data. For instance, they can categorise grants using their own criteria, as long as a logical explanation of their reasoning is provided alongside the submission. We believe that in order to overcome biases that could be hidden in the data and receive feedback that will improve the future data use, it is crucial to include different interpretations coming from people from diverse backgrounds.
We would like Digging the Data to promote responsible use of data and be a positive influence on the sector. We advocate for data protection, privacy and conscientious data sharing. In this competition, it is particularly important to reflect on how to support and create visualisations that are well-researched, credible and contain non-sensitive data. Visualisations are so visually appealing, that it is rare to question their credibility or analyse the underlying data. We believe that researching, cleaning and interpreting the data prior to visualising it is crucial. While doing it, we must be mindful of how we change the data and whether our work results in any potential biases. Similarly, what is excluded from the dataset is often as important as what the final visualisation contains. In our challenge, we call for well-justified and inclusive work. With the creative freedom the participants are offered comes the responsibility to justify their choices and thoroughly document the process. The diversity of thought is always welcome - a multitude of perspectives encourages a variety of conclusions that have the potential to develop answers to inform better-targeted grantmaking.
Data visualisation is a great medium and we appreciate its aesthetic value and accessibility. Interacting with data locked in spreadsheets or complex databases can be daunting; exploring it in a visual form makes it easier to comprehend for anyone, including the less tech-savvy audiences. The use of colours, visuals and graphs can convey the most complex messages and facilitate faster understanding of a dataset. One quick look at a visualisation enables us to grasp the most important aspects of the data fast and immediately identify any patterns that might have been overlooked otherwise. A well-made data visualisation combines depth and clarity, presenting the data in a format that facilitates identification of new patterns. It also deconstructs complex interdependencies and increases overall understanding of the dataset. Interactive visualisations take it even further. They enable the viewer to explore the data in a greater detail and shape the results in accordance with the changing variables.
Thoughtful and well-designed data visualisations are modern-day works of art and through Digging the Data challenge we are giving you a reason to create one.