Primary sources of data
Data compilation and cleaning
Data checking
Externally validating data
Primary sources of data
Data compilation and cleaning
In order to analyse the development of the UK museum sector, we first needed to compile a dataset of all the museums that had been open at any point between 1960 and 2020, and a list of their main attributes: accreditation status, location (both postal address and administrative location), governance, size, subject matter, year of opening and year of closing (if applicable). We drew on a wide range of sources to do so.
In the first instance, the team focused on the Digest of Museum Statistics (DOMUS), a major survey of accredited museums that was conducted between 1994 and 1999. Unfortunately, the data needed considerable work before it could be used. The archived survey consists of hundreds of encoded spreadsheets that all contain information about the museums in question, but addresses are on one sheet, the names of the museum on another, visitor numbers on a third and so on. In addition, all the information is in code. We translated the numerical codes into words and reassembled the DOMUS data from its constituent parts. We then removed entities that did not refer to a single museum (e.g. references to overarching bodies such as the Science Museum Group), dummy entries, and redundant information such as fax numbers and company numbers.
Having manually reassembled and cleaned the DOMUS data, we then began to add data from the other contemporary and historical datasets. In the first instance we used data from official government surveys, such as the 1963 Standing Commission Survey of Provincial Museums, and the current ACE accreditation data, and then we began to add membership data from the Association of Independent Museums and the Museum Association. Thereafter we used a range of sources, adding information from historic and specialist guidebooks and gazetteers, from tourist boards, and from web searches. Digital resources such as the BBC’s 1986 Domesday project, were useful and the discovery of an unpublished survey of members and non-members conducted by the Association of Independent Museums in 1983 was particularly important in developing a substantial body of information on small independent museums of that period.
As we collected new data, we added new museums to the dataset and new information on the museums we had already listed. For example, we might have a record of the Museum of X from DOMUS. However, the record of the Museum of X in the Museums Association Find-A-Museum Service would have more recent information on visitor numbers, which we would then enter into our database.
In many instances, it was extremely difficult to find detailed information about specific museums. We might know that a museum had been open at some point in the 1980s but not know exactly when it opened or closed, or what subject it had covered. Appeals for information were repeatedly put out on social media but personal contact proved the most effective means of finding missing information. In the last few months of the data collection, the team made hundreds of telephone calls and sent hundreds of emails to museum staff, local history societies, tourist boards, town clerks, and other relevant organisations to find and establish the missing details. We continue to update the dataset with new information, as it becomes known
Data checking
The gradual accumulation of information in our database helped us check the validity of the source material. As various museum databases were incorporated into our main datasheet, the existing data was either corroborated or contested. For example, if the Museum Y was listed in DOMUS as existing at 1 High Street, Anytown, and then the Arts Council England accreditation data also showed the same address, etc., then we had a high degree of confidence that:
a) The DOMUS museum is a legitimate museum (understood to be a museum by more than one survey)
b) That between 1999 and 2017 the conditions of the museum stayed the same.
Where the opposite is true – if the ACE accreditation data listed Museum Y as existing at 10 Nonsense Avenue, then we knew that within those 18 years something substantial has happened to the museum and that this warranted further investigation. Where we found disjuncture in the data, we contacted the museums or cross checked with other sources as was required.
When our data source was old or where the date of the source was uncertain we checked if the museum was still open. In some cases museums that have closed still have an extant website so we looked to see if news and events pages had been updated. TripAdvisor was also useful as it records when visitors went to particular sites, and hence indicates whether it is open or has possibly closed. This approach was also used, to a lesser extent, with smaller, specialised web-forums where contributors occasionally posted questions or reminiscences about particular museums.
Externally validating data
The Museum Development Network provided the most robust external review of our data. We took regional data to each of the nine Museum Development groups in England, and they conducted a line-by-line scrutiny of our database. They were able to provide a local knowledge of both recent developments in their area (openings or closure) and to check our classifications. Staff at the national offices for museums in Northern Ireland, Scotland, and Wales similarly scrutinised the data, as did some specialist and subject groups. We provided our full dataset on regimental museums to the Regimental Museums liaison officers at the National Army Museums who provided comparative information, which allowed us to re-check that sector, and our dataset on transport museums to the Transport Museums Trust who further edited and refined data on museums from that category.
Further reading:
Mapping Museums blog: 'Picking the brains of the Museum Development Network'