We pull together, combine and re-present physically dispersed datasets in order to place humanities resources in their wider context and create different perspectives

Linked data, which is sometimes called a ‘mash-up’, is the process of retrieving different sets of data from different locations on the World Wide Web, such as data presented on other websites or data held within repositories, and combining it in order to either enhance the value of a core dataset or create an entirely new dataset or service.

Perhaps the most common example of a linked data process is the use of Google’s map data within the web pages of other websites: a map is retrieved from Google’s server and embedded within a website which is not owned or controlled by Google.

A key advantage of linked data within the arts and humanities is that it enables us to create new perspectives which benefit research by combining and presenting content in new ways. For example, projects such as London Lives and Connected Histories enable users to trace the lives of individuals across multiple document sources whilst our Locating London project enables users to plot different datasets onto eighteenth-century maps of London, revealing spatial relationships between datasets which are normally separate.

A further advantage of linked data is that it facilitates data re-use, which is often an objective of research funding councils and a measure of impact. Linked data services are heavily reliant on research data being created and hosted in the right way, using appropriate data standards.

Federated searching is our most frequent implementation of data linking techniques, whereby data held in physically separate digital archives or third-party services is pulled together to create a new, thematically related resource for use by researchers. The advantage of federated search using linked data techniques is that researchers are able to explore authoritative, subject-specific resources from a wide range of organisations and locations in a single place without the ‘noise’ of other data, whilst the ability to view one resource within the context of another will often encourage new types of analysis and reveal new perspectives.