Data Stories: Producing stories about and with property and planning data

Introduction

Planning and property data are the key evidence base for how cities are understood, planned, and developed. They inform public perception, guide investments, and shape policy. Yet, little critical attention has been paid to planning and property data and their lifecycles, circulation, politics, power, and use in policy and stakeholder decision-making.

Challenges

This lacuna raises two important challenges that require redress if the validity of analysis, interpretation, and decision-making is to be improved:

1. Transforming the ontological and epistemological understanding of planning and property data amongst those that utilize them.
2. Fostering a reflexive approach to data politics and power in organizations that produce, share, and use planning and property data.

Project Overview

DATASTORIES will tackle these challenges by conducting research in a creative, highly engaged way with key stakeholders across three domains: state, business, and NGOs/civil society.

Methodological Approach

It will develop an innovative methodological approach that blends social science and research-creation methods, working with creative writers and artists. The project aims to:

• Map an entire data ecosystem (Dublin, Ireland).
• Unpack data assemblages.
• Produce a variety of data stories.

Case Studies

Twelve in-depth case studies will produce 36 data stories about and with planning and property data.

Key Advances

The project will produce four key advances:

1. New knowledge about the evidence base for planning and property and its use.
2. Critical insight into the politics and praxes of data.
3. Novel research-creation methods and an assessment of their efficacy.
4. An extended conception of data stories and an understanding of their production and utility for different audiences.

Impacts

DATASTORIES will produce three ground-breaking impacts:

• Conceptual: Transforming the epistemology of planning and property research.
• Applied: Positively influencing the data processes and practices of key stakeholders.
• Methodological: Validating research-creation and data stories as social science methods.