MisoData

With over 30 years' experience, MisoData is a recognised expert in delivering geospatial solutions that make organisations more successful.

MisoData believes that the way each organisation works is unique and evolving constantly, and therefore data solutions need to too. It works with its customers to find flexible, innovative ways to make working with data easier. By connecting systems, automating day-to-day processes or applying machine learning, the company helps organisations get the most out of the information they already have. 

MisoData has developed a range of solutions to help make working with maps easier. Its automated services make it simple, fast and secure, to source, prepare or share data. While its core focus is architecture, engineering and construction (AEC), utilities and Local Government, it has over 1,200 customers in a wide range of public and private sectors.

MisoData is committed to helping its customers achieve trouble-free data transformation. Its DataOptimiser Service allows organisations to request their datasets, formats, coverage and refresh rate. Customers can also outsource the process of styling and prepping its data, so MisoData provides a download link with all the data prepped and ready to use.

MisoData can also enrich legacy data to maximise its value by building out an automated transformation process that the customer can see, understand and adjust. It builds the customer’s requirements into a robust workflow using FME technology. The technology can sit on desktop, on server racks or in the Cloud.

MisoData can also source and optimise 3rd party data where required. MisoData has enjoyed a strong partnership with Ordnance Survey (OS) since 1995, supplying a range of geospatial data products that can be used to enrich a variety of projects. These products are provided as standalone downloads and as part of wider consultancy engagements. These clients span a range of industries including Local Government, emergency services, transport authorities and energy suppliers.

MisoData takes its understanding from a project and shares this with customer teams through interactive workshops – enabling organisations to replicate these capabilities in future projects.

On-Street Charging Research project – Field Dynamics

Field Dynamics, has analysed the footprint of the 27 million households in Britain to determine their ability to accommodate off-street parking. The approach leverages the intelligence contained within Ordnance Survey’s highly detailed MasterMap Topographic Layer and AddressBase Layer, combined with MisoData’s advanced algorithm to survey and interpret all the spaces surrounding every residential property in Britain. This creates a parking propensity that then can be combined to create a score per property, which has been validated in the field by numerous site surveys.

Jumpstart – Worcester

Building on the On-Street Charging project, MisoData created Jumpstart. JumpStart is a structured, proven approach that will build an evidence foundation specific for a local authority but based on all the key national data sets and processed through a series of objective analysis sessions. It will provide all the information needed to deliver on these electric vehicle challenges to the point of operational hand-off. It will act as a constant resource of objective, data based, accurate evidence.

Scottish Power Energy Network (SPEN)

MisoData was central to the electric vehicle adoption methodology and platform model to simulate residential electric vehicle demand uptake across low-voltage network infrastructure. Nominated for Data Project of the Year at UK Network Awards, the project was extended to model decarbonisation of heat assessing technology and legislative scenarios.

MisoData also completed modelling work to profile a number of future energy scenarios and the impact on SPEN’s network of primary substations. This included a number of low carbon technology options to consider electric vehicles and heat pumps which involved the creation of a number of spatial proxies to differentiate demand across the network geographies.