Project context

EPSRC funded 22 projects over two calls in 2010 and 2012 to investigate `Transforming Energy Demand through Digital Innovation' (TEDDI) as a means to find how and how people use energy in homes and what can be done reduce energy consumption. As a result a lot of data is being collected at different levels of detail in a variety of housing up and down the UK, but the mode, detail and quantity are largely defined by the needs of each individual project. At the same time, the research councils (RCUK) are defining guidelines for what happens to data generated by projects they fund, for which universities are then defining policies and finally researchers are then taking concrete actions to store, preserve and document data for future reference.

The data legacy problem

The problem at this current time is that there is relatively little awareness, limited experience and only emerging practice of how to incorporate data management into much of (physical) science research. This is in stark contrast to established procedures for data formats and sharing in the biosciences, stemming from international collaboration on the Human Genome Project, and in the social sciences, where data from national surveys, including census data, have been centrally archived for many years. Consequently, current solutions adopted by (Build)TEDDI projects may be able to meet a minimal interpretation of the requirements, but not effectively deliver the desired data legacy, such as (for example) the means to execute trans-project queries, or being able to cite the results of such queries for the sake of reproducibility.


ARCC/DM4T webinar

DM4T is joining up with the ARCC network for a webinar on 2017-05-12 at 13:00-14:00. Sign up via Eventbrite

MetaMaker Video

A video of the MetaMaker tool prototype is available via the Outputs drop-down. This shows how to construct a "shim" ontology to enable ontology-based data access.

Aims and objectives

The challenges described above, which we address in DM4(B)T in the microcosm of the TEDDI projects, are tackled in three ways:

Objective 1

Raising awareness with those who are directly responsible for data management – principal investigators – CoIs and research staff

Objective 2

Developing a framework to guide the process of making the choices for how to go about implementing data management

Objective 3

Demonstrating example tools that will enable researchers to bring together and re-analyse data from different projects more easily

Key activities and outputs


To gather information about current practice, present data management problems and outline analysis and solutions and to disseminate knowledge of tools and (new) practices to support effective data management

Tools and techniques

To allow researchers to harness both the variety and volume of data being collected specifically within the (Build)TEDDI projects. The tools will be made available open-source for access by other researchers to expand and adapt.


These will take the form of an online report to identify routes to facilitate a sustainable data legacy (management, curation and citation) for projects in the science and engineering domain.

Applications and benefits

TEDDI projects

(Build)TEDDI projects will benefit directly from the above activities and outputs to meet institutional and research council requirements

Secondary researchers

Other researchers will benefit from being able to access (Build)TEDDI data

RCUK community

The outputs will benefit the wider research community in science and engineering through the provision of an easy-to-adopt (and adapt) data management methodology

What next?