It seems like a simple enough of a question, but sometimes it’s worth revisiting things we think we know, to re-examine them and to dive a bit deeper. The things we think are simple often reveal hidden depths… And that’s certainly true of property data.
First things first; to define what property data is we need to define what ‘property’ is.
When you think about it, that covers a lot of ground. By definition, a property can be almost anything you can imagine — from any item on the supermarket shelf, to a car, a house, or even just a theory.
In this article, we’re referring to the concept of a building or buildings and the land belonging to it or them. Schema.org covers some of these types of definitions such as Place or perhaps House but their definition is not suited for the majority of use cases, as they are simply trying to define a thing, but property is more than just a thing.
How we define property data
Property data comprises a collection of information concerning a physical place or real-world location. At its core, fundamental data points about a property include its geographical location and the timestamp of its creation. These are typically represented by an address (serving as a proxy for location) and the time of establishment. Subsequently, any additional details pertaining to the property can be viewed as metadata.
Information regarding individual properties is frequently aggregated into datasets containing multiple properties, which are then made accessible and navigable through geospatial navigation systems. These systems utilize various identifiers such as postcodes, coordinates, or area boundaries to facilitate efficient data exploration and analysis.
How to approach a data-driven definition
To effectively manage and analyze data, it’s crucial to categorize properties based on high-level distinctions such as residential or non-residential and property data API tools can streamline this process. Here’s a standardized schema that all properties should adhere to at a minimum:
Residential Property Data
- Address
- Property type
- Property characteristics (Energy Performance Certificate – EPC)
- Sale price
- Tenure
- Commercial owner
- Company registrations
Commercial Property Data
- Rateable value
- Usage category
- Internals: Gross Internal Area (GIA), Net Internal Area (NIA)
- Commercial occupant
- Company name
- Company Number (facilitating linkage to Company data)
- Link to other properties
- Compliance information: Hygiene, Department for Environment, Food & Rural Affairs (Defra) compliance, Food Standards, EPC, Care Quality Commission (CQC), Gambling
Commercial Ownership
By structuring data in this manner, it enables a multitude of applications and connections to other datasets, facilitating comprehensive analysis and utilization.
Endless Usecases of Property Data
Understanding property data encompasses a vast array of applications across various sectors, ranging from insurance assessments to urban planning and social welfare initiatives. Here’s an exploration of its diverse significance:
When considering property data, one must recognize its wide-ranging implications for individuals, businesses, and governments. For instance:
- Insurance Purposes: Insurers require comprehensive property information to assess risks accurately. Details such as location, age, value, and trends in property value over time are crucial. Additionally, knowledge about neighboring properties, such as proximity to potential hazards like petrol stations or hygiene ratings, enhances risk assessment.
- Marketing Insights: Marketing companies benefit from knowing addresses where new businesses have emerged, enabling targeted marketing efforts.
- Urban Planning: City planners utilize property data to create visualizations depicting property types and their proximity to amenities, aiding in urban development strategies.
- Social Welfare Initiatives: Social workers utilize property data to identify areas with high levels of poverty or children at risk, enabling targeted intervention efforts.
- Logistics and Delivery Services: Companies providing services like flower delivery rely on property data, utilizing GPS systems to locate addresses accurately for efficient service delivery.
- Investment Analysis: Investors analyze property markets and trends using comprehensive property data to make informed decisions.
- Journalistic Investigations: Data journalists leverage property data to uncover inequalities and trends within markets, contributing to investigative journalism efforts.
- Demographic Analysis: Demographers utilize property data to create area models and understand population demographics effectively.
- Government Services: Third-party apps facilitate citizen access to government services by leveraging property data for streamlined processes.
- Law Enforcement: Police headquarters use property data to allocate resources effectively, determining where to focus efforts based on crime statistics and problem areas.
- Charitable Endeavors: Charities use property data to identify areas in need of anti-poverty aid, guiding the deployment of resources for maximum impact.
- Business Expansion: Retailers utilize property data to decide where to open new stores, considering factors such as market demand and demographic profiles.
In essence, the definition of property data extends far beyond mere information about physical structures; it underpins a multitude of critical decisions and initiatives across various sectors, highlighting its profound importance in today’s interconnected world.
What is the most useful data about a property?
The most valuable approach to property data involves collecting and linking an extensive range of primary information about each property, then further enhancing its utility by connecting it to additional datasets. Our strategy aims to provide comprehensive insights into every property, irrespective of type, by incorporating a wide array of data points and facilitating linkages to various other datasets.
Key elements of our approach include:
- Demographic Data Linkages: Connecting property data with demographic information enables a deeper understanding of the communities surrounding each property.
- Company and Director Data Linkages: By linking property data to company and director information, users gain insights into the business landscape associated with each property.
- Public Procurement and Regulatory Data Integration: Incorporating public procurement and regulatory data provides users with insights into compliance and regulatory matters related to each property.
- Local Area Information Inclusion: Integrating local area data, such as school locations, healthcare facilities, transportation options, housing prices, flood risks, crime rates, and local businesses, enriches the context surrounding each property.
- Local Population Information Integration: Including data on the local population, including health indicators, socioeconomic status, educational attainment, and welfare support, offers a comprehensive view of the communities surrounding each property.
- Ownership and Company Associations: Providing information on property ownership, particularly for commercial or public-sector properties, and linking it to associated companies enhances understanding of property ownership structures.
By offering this extensive dataset through a federated API or hosted database, we empower users to explore a multitude of use cases without restricting their creativity. The versatility of the data allows users to tailor their analyses and applications according to their specific needs and objectives, ensuring maximum utility and flexibility.
Wrap Up
In conclusion, while property data may seem straightforward at first glance — simply information about a property — its significance extends far beyond mere physical attributes. Property data serves as a cornerstone of our societal and economic infrastructure, offering insights into the interconnected web of people, places, and entities.
In many ways, property data forms a fundamental part of our collective identity, revealing essential aspects of individuals, communities, and assets. It plays a pivotal role in facilitating the smooth operation of various systems, serving as the glue that binds together government agencies, businesses, and individuals.
Property data is a multifaceted and dynamic resource, continuously evolving as it becomes more accessible and intertwined with other datasets. Its applications are diverse and wide-ranging, spanning from government policy-making to commercial decision-making and beyond.
Ultimately, property data represents a rich tapestry of information with virtually limitless potential applications, both beneficial and detrimental. As it continues to grow and integrate with other sources of data, its influence on our society and economy will only continue to expand.