Tag: data

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Lab News

Two Years On: An Update

2 years spelled out in children's blocks

The Mapping Museums project is coming to the end of its second year. To mark the half way point of the research, this blog provides a brief update on some of the work so far.

Finalising the data
Early this year, Dr Jamie Larkin, the researcher, completed the main phase of data collection. We are continuing to make changes to the dataset as new museums open and existing museums close, and we’re still trying to hunt down some missing opening and closing dates, so it remains work in progress. Nonetheless, we now have information on almost 4,000 museums that have been open at some point between 1960 and the present day.

Evaluating the knowledge base

Alongside data gathering, we have designed a knowledge base that allows users to browse, search, and visualise the data in nuanced and precise ways, and which we described in our last blog (See: Managing Patchy Data). As part of the design process, Professor Alex Poulovassilis, the co-investigator on the project, and Nick Larsson, the Computer Science researcher and developer of the knowledge base, organised a series of trials to evaluate the knowledge base. These provided us with valuable feedback and we responded by making changes to how the material is presented and navigated.

We got enormously positive responses at the most recent user trial in Manchester in July. Having lived and breathed the research for the last two years it was very encouraging to hear Emma Chaplin, director of the Association for Independent Museums, call it the “museums equivalent to YouTube” and say that she could while away hours browsing the material; to know that staff from Arts Council England thought that it was “intuitive  to use”; and generally that the trial participants assessed it as a being a useful resource for them in their roles and for others in the sector.

Analysing and publishing the findings

Having finished the data collection and the main phase of developing the knowledge base, we have been able to start analysing the data. These initial analyses will be the basis of a series of articles, and over the summer, the team has been working on four publications:

  • ‘Mapping Museums and managing patchy data’ examines the reasons why data on the museum sector is so incoherent, how the project sought to remedy that situation, in part by building a system that acknowledges uncertain information.
  • ‘Where was the Museum Boom?’ looks at the massive expansion of museums in the late twentieth century and asks whether or not the boom took place across the UK, or if there were regional variations.
  • ‘Creating a Knowledge Base to research the history of UK independent museums: a Rapid Prototyping approach’, covers the computer science research that underpins the conceptualisation and construction of the knowledge base.
  • ‘Missing Museums’ deals with the recent history of museum surveys, considers the focus on professionalised museums, and asks what the sector looks like when we factor in unaccredited museums.

Brief versions of the first and second of these papers were also presented at conferences: Digital Humanities Congress at Sheffield University and Spatial Humanities at Lancaster University, both of which took place in September, and we hope that the full versions of all four articles will be published within the next academic year. We’ll let you know when that happens.

The process of analysing data has been greatly helped by having Dr Andrea Ballatore join the team early in 2018. Andrea is a Lecturer in GIS and Big Data Analytics in the Department of Geography at Birkbeck and he is leading the statistical analysis within the project. He has also made invaluable contribution to developing the knowledge base, particularly with respect to mapping the data.

The Mapping Museums Team

Categories
Research Process

Modelling Patchy Data

Repairs anchor thread

How do researchers manage when they have missing data? One of the initial aims of the Mapping Museums project was to establish an authoritative dataset of all the museums open between 1960 and 2020, and to record information on their location, governance, accreditation status, subject matter, opening and closing dates, and visitor numbers. Having this material would provide the first step in constructing a nuanced, evidence-based history of the development of the museum sector during the period, and so the research team began to compile information from numerous sources: surveys conducted by government bodies, by the Association of Independent Museums, and the Museums Association; lists of museums held by the national organisations for the arts; guidebooks; and websites. The researchers also got in touch with dozens of tourist boards and local history groups, and hundreds of curators and volunteers to follow up leads or information. All this material was cross-checked within the team, and then reviewed by experts from the Museum Development Network.

We now have a rigorously researched list of museums in the UK from 1960-2020. Even so, there is still a considerable amount of missing data. When the first phase of data collection was finished we had identified almost 4,000 museums and had established the following coverage of their key attributes:

  • Museum opening dates: 88%
  • Museum closing dates: 6%
  • Governance: 92%
  • Visitor numbers: 67%

The question then was, how were we to represent and model the missing dates, governance, and visitor numbers within our analysis?

At the same time as collecting data, we started to build a knowledge base that allows users to explore. The system is designed so that users can browse in a structured way through the categories of accreditation, governance, location, size, subject classification, year of opening and year of closing, and see the results on a map or in a list view. Alternatively, they can submit a detailed search that allows them to filter results by combinations of the categories above, or they can generate visualisations of how the different types of museums have emerged over time and create tables showing how the various categories inter-relate. At any point, it is possible to scrutinise the details of individual venues.

One option for dealing with missing information was to exclude museums with missing data from the relevant searches. The problem with that approach is that incomplete data tends to be associated with small, unaccredited museums or with museums that have since closed and so excluding them on this basis would bias our analysis in favour of extant established museums., which would be counter to the purposes of the project as a whole. Thus, when we could not identify a museum’s governance, we assigned it a value of Unknown. The advantage of an explicit Unknown category is that the missing data is made apparent, and the problem of data patchiness is exposed rather than hidden.

We took a different approach to opening and closing dates because we often had rough information about these rather than no information at all – for example, we might know that a museum had closed at some point in the 1990s. This approximate information would be lost if we just categorised a date as ‘unknown’. Therefore, we decided to use a date range of the form (earliest possible year, latest possible year) to capture imprecise knowledge about museum opening/closing dates. These date ranges are used in different ways across the different facilities provided by our system:

  • In the Browse facility, we take museums’ opening/closing dates to be the mid point of the specified date range.
  • In the Visualise facility, event occurrences are ‘spread’ equally over a date range. For example, if a museum is known to have opened between 1965 and 1969, then the count of one museum opening is spread over that time period (i.e. a count of 0.2 is assigned to each of the five years 1965, 1966, 1967, 1968, 1969).
  • In the Search facility, the user has the option of searching by definite dates so that the results exclude all the museums with date ranges attached, or by possible dates, in which case the results include museums where the date range intersects with the specified period. This allows for a much more nuanced analysis.

Looking in more detail at how Search works, opening and closing dates are stored as a pair of years (f,t) in our database, where f and t may be the same year if we know the year of opening/closing for certain.  So, for example, the pair (1965,1969) would be stored for a museum known to have opened between 1965 and 1969; and the pair (2011,2011) would be stored for a museum known to have closed in 2011. Modal Logic operators are supported by our system’s Search facility that allow the user to query whether a particular museum definitely or possibly opened/closed in a given year.  In particular, suppose a given museum ‘m’ is recorded as having opened in year ‘f’ at the earliest and year ‘t’ at the latest.  Suppose a researcher wishes to find out whether museum m opened before, on, or after a specified year ‘d’.  Then the following comparison operators are supported by our system to allow the researcher to determine whether this is definitely the case:

Comparison operator Implementation logic
(f,t) = d  DEFINITELY ON A SPECIFIC YEAR f = d  and t = d
(f,t) < d  DEFINITELY BEFORE t < d
(f,t) <= d DEFINITELY BEFORE OR INCLUDING t <= d
(f,t) > d  DEFINITELY AFTER f > d
(f,t) >= d DEFINITELY AFTER OR INCLUDING f >= d
(f,t) != d DEFINITELY APART FROM t < d OR f > d

 

And the following comparison operators are supported to allow the researcher to determine whether this is possibly the case:

 

Comparison operator Implementation logic
(f,t) = d POSSIBLY ON A SPECIFIC YEAR f <= d AND d <= t
(f,t) < d  POSSIBLY BEFORE f < d
(f,t) <= d POSSIBLY BEFORE OR INCLUDING f <= d
(f,t) > d POSSIBLY AFTER t > d
(f,t) >= d POSSIBLY AFTER OR INCLUDING t >= d
(f,t) != d POSSIBLY APART FROM not (f=d and t=d)

 

The same comparison operators are available for interrogating closing dates.

We employed a further strategy for visitor numbers, which is the least complete category and has discontinuities that make it difficult to compare like with like.  Our primary objective was to use visitor number data to provide an indication of the size of the museum and, given the patchiness of the information, we decided to have a category of Unknown and also to gross numbers into size categories of Large, Medium and Small, where large and small also have sub-categories. This approach enabled us to include data from the Association of Independent Museums and Arts Council England who generally provide visitor number ranges rather than precise figures, and to use predicative analysis to establish broad size ranges. It also allowed us to circumvent some of the methodological problems of having figures collected by different means and from across the decades. Users can browse or search according to these size categories, and in addition, they can search according to precise date-stamped visitor numbers where available.

In conclusion, in the Mapping Museums project we have managed data patchiness in a variety of ways: designing a flexible knowledge base that can be modified and added to as required; representing absence rather than ignoring unknown information; using date ranges and providing users with the option of searching by definite or possible dates; and apportioning the probability of an opening/closing event occurrence over the estimated time interval for statistical analysis. Rather than implying that all visitor numbers data are of equal reliability, we created size categories for a large number of museums, and provided the means to search the definite but incomplete data that was available.

Fiona Candlin, Alex Poulovassilis
September 2018

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Events

Participate in our web application evaluation sessions!

Can you help us to evaluate the Mapping Museums web application?

Mapping Museums is a large-scale research project that is based at Birkbeck, University of London. It aims at documenting at analysing the development of the museum sector between 1960 and 2020. So far, the team has collected a rich range of data on approximately 4000 UK museums, and we have developed a web application that enables users to browse, search, and visualise that information.

The evaluation session is an important means for us to gain feedback about the usefulness of the web application. With your input we can further improve the system before it is made publicly available.

We’d like a wide variety of people to participate in the evaluation trial especially those that are involved in the museum and archive sectors, in academia, or in digital media

The trial session will be based on three activities:

  • A hands-on introduction to the web application.
  • Using the application to undertake a small number of information searches. This will allow us to gauge how easy the system is to use.
  • Group discussion about your experience of using the system and the ways that it could be improved and extended.

The session will take no more than two hours.

There is more information about the project available at http://mappingmuseums.wpengine.com/about/.

Locations and dates:

2 – 4.30pm | October 3rd 2018 | Room 407, Birkbeck Main Building, Malet Street, London WC1E 7HX (the entrance is on Torrington Square)

We would be very grateful for your assistance. If you would like to participate, please email the project director at f.candlin@bbk.ac.uk briefly explaining why you would like to attend. We can cover travel expenses up to £20.

Researchers involved in the trial session

Researchers and contact details:

  1. Professor Fiona Candlin (candlin@bbk.ac.uk)
  2. Professor Alex Poulovassilis (ap@dcs.bbk.ac.uk)
  3. Nick Larsson (nick@dcs.bbk.ac.uk)

How the data will be handled in the study

Information obtained from you through the session will be used to inform the research work of the project and subsequent research publications. All personal data collected from this study including your name and contact details will be kept confidential. No reference will be made in oral or written form that could link any participant to information they have provided to us as part of this the study.

Your participation in this study is voluntary, and you may withdraw from the study at any time.

Categories
Research Process

Surveying museums: What’s in and what’s out?

We began the Mapping Museum research by investigating the numerous surveys and reviews of UK museums that have been compiled since the 1960s. Our intention was to use that material as the basis for our own dataset, but it gradually became clear that the various government and charitable bodies who had conducted the surveys or collated the lists did not always include or exclude the same venues. They all had subtly different ideas of what a museum was.

Clearly, the motivations for surveying museums vary depending upon the remit of the association or body that is conducting the survey. If a review is focused on state support then there is little reason in spending time and money investigating independent museums, art galleries without collections, and examining regimental collections would be pointless if the survey is meant to look at the role of university museums. It is not that the surveys have been inaccurate, or that we should advocate for a more perfect overview, rather that they are designed for particular purposes within specific contexts. Even so, the selectivity of a survey does matter, especially when they concern museums in general. In adopting one set of terms over another, or in deciding that a particular category of venues do or do not fall within their purview, surveys diverge in how they constitute museums. They have each understood museums to be slightly different entities, and this has an impact on how they portray the sector as a whole.

In this and the next two posts I will consider some of the types of venues that have been included or excluded from surveys, and as they are the main focus of our study, I will begin with independent museums.

 

Independent museums: In or Out?

In 1963, the Standing Commission stressed that they had considered ‘museums run by every sort of authority’. They listed local authority museums, those run by the Ministry of Public Buildings and works (which later became Historic Buildings Commission, then English Heritage), military, school and university museums and finally ‘privately-run museums’ of which a few belong to commercial firms, some to local learned societies, and almost all the rest …. are administered by trusts’. At this stage, who ran the museums, under what governance, and with what degree of professionalism, was less important than the fact they were a museum, and what constituted a museum was not raised as a question. Surveys conducted in the 1970s and 1980s were similarly inclusive but that situation had changed by the 1990s.

The shift in approach was motivated by an increasing emphasis on professionalization and specifically accreditation. In 1971 the Museums Association proposed a voluntary accreditation scheme, which would set basic standards in the sector. In order to be accredited, museums had to comply with the association’s benchmarks and with their definition of a museum. Responding to the plan, which was presented at the Museums Association Annual General Meeting, one speaker observed that many small independent museums would find it difficult to meet the first essential minimum requirement, namely, that they had sufficient income to ‘carry out and develop the work of the museum to satisfactory professional standards’. More than that, the accreditation process introduced a definition of a museum for the first time, and as the speaker also commented, it referred to museums as institutions, which the small independent venues were not.

Initially accreditation was voluntary and was run in a relatively ad-hoc way, but in 1984 it was taken over by the Museums Libraries Archives Council and became more closely connected to funding. Museums had to be accredited in order to qualify for public support and so membership of the scheme became increasingly ubiquitous. It also began to be used as the basis for surveys and lists. DOMUS, which was the most comprehensive survey of museums in the UK, only included accredited institutions and omitted an estimated 700 non-accredited museums. At one point the DOMUS team did consider the possibility of including non-accredited museums and of generating a more comprehensive view of the sector but it came to nothing, not least because the survey data was gathered in tandem with the annual accreditation returns, and so there was no process for collecting information on these additional museums.

The situation, wherein small independent museums did not meet the requisite standards and therefore were largely absent from official data, was exacerbated when the definition of museums changed in 1998. The new definition added a legal stipulation, which was that museums had to keep their collections ‘in trust for society’. Again, this concerned the contract between museums and the public because establishing museums as trusts helps ensure that collections are not sold or used for private gain, which is especially important when funding is involved. The result was that from this point onwards any museums that were run on an ad-hoc basis with little official governance, were constituted as commercial enterprises, or were owned by families, individuals, or businesses, ceased to appear in official data. Likewise, museums that did meet the terms set by the Museums Association definition, but had decided not to seek accreditation fell off the official lists.

The Museums Association definition works well as an aspirational target or a guide for professional practice, but it does not describe museums in the world at large. Similarly, accreditation is a useful means of ensuring some accountability with respect to public funding, as is the stipulation that museums should have particular modes of governance. National funding bodies do need to keep track of the museums that have been accredited and are eligible for state support. Nonetheless, using accreditation as a mechanism for collecting information about museums has resulted in a skewed view of the sector. Surveys are structured in such a way that they can only encompass museums that have achieved a particular level of professionalization.

To draw an analogy, imagine that a professional association of musicians declared that music needed to be made within a certain legal context and to be of a certain standard in order for it to count as such. The outputs of community choirs, folk musicians, pub bands, would no longer qualify as music unless they had established themselves as trusts. Yet, in the case of museums, such a definition has been widely adopted and implemented. The museum equivalents of pub bands do not appear in official surveys. In consequence, they do not figure in accounts of the sector or to a large extent in academic histories of museums. It is, as if museums only operate within the sphere of official culture.

Interestingly, some unaccredited museums appear in the Museum Association Yearbooks and more recently on their online Find-a-Museum Service. Although the Museums Association has been one of the main drivers in setting standards and establishing definitions of museums, they are also reliant on membership fees for income. Anyone who pays to join can submit their details, and the Association do not police entries according to their own criteria, since that would result in a drop in revenue. There is some irony in this situation. The Museums Association’s work on establishing definitions has resulted in smaller museums being excluded from official consideration but nonetheless its publications and website are among the few places where non-accredited museums are listed. The Mapping Museums team has used and is greatly extending that data on unaccredited museums, and will be publishing lists of museums in general, not just those that meet professional criteria.

 

© Fiona Candlin November 2017

Categories
Research Process

Picking the Brains of the Museum Development Network

There is a limit to how much information can be unearthed online or from an archive. Over the last year, the Mapping Museums research team has compiled a mammoth list of museums that were open in the UK between 1960 and 2020. We have used various sources to cross check their details, but there are some particulars that can be hard to find or verify. And so, we asked the Museum Development Network for their assistance.

The Museum Development Network consists of twelve groups, one apiece in Northern Ireland, Wales, and Scotland, and one in each of the nine regions of England. Although the groups all function slightly differently, they all support accredited museums, advise on the accreditation process, and provide relevant information to Arts Council England and other national organisations. They also allocate their own grants, run projects, and help improve services and their members’ skills. In doing so, the museum development officers quickly acquire a fine-grained knowledge of their local museums. We wanted to refine our data by tapping their expertise.

With the support of Claire Browne, the network chair, we arranged to visit staff in each country or region. On each occasion, we arrived with a list of the museums of that area and slowly worked our way through the data, line by line. We had asked the museum development officers to look out for any information that we may have missed and they pointed to a number of instances where the local authority had transferred responsibility for a museum to an independent trust. They also noticed some duplicate entries that had resulted when a museum’s name had been changed, and spotted instances when museums had moved premises, amalgamated with neighbouring venues, or had recently closed. We deleted or edited the entries as appropriate.

The Museum Development Network helped us fine-tune our data and they also contributed to our research by helping us classify museums according to their subject. In most cases, the main topic of a museum is fairly obvious: as one might expect, the Lapworth Museum of Geology concentrates on rocks of varying types, while the Bakelite Museum has a collections of plastic, but the theme of a museum is not always so self-evident. For example, Carnforth Station provided the set for Brief Encounter, and its Heritage Centre focuses on the film, not on railways or trains, while the Deaf Museum and Archive in Warrington is more concerned with the community than with health or medicine. Being familiar with these venues, the museum development officers could make a nuanced judgement as to their overarching subject matter, whereas the research team would have to spend a considerable length of time checking webpages, catalogues, and other sources to make a judgement. Their input saved us weeks of work. It was also good to establish that our new classification system worked smoothly, although the absence of a ‘social history’ category did cause some consternation. For us, the problem with ‘social history’ is that it applies to such a large number of venues that it lacks nuance. In the DOMUS survey, conducted in the 1990s, almost a third of museums were listed under this category, which makes it almost unusable for research purposes.

Holding the meetings served to further refine our data, and it also had benefits for the museum development network. Many of the officers said that they rarely got an opportunity to discuss the museums in their region, and that it was useful to do so. Others thought that going through the list was akin to a quiz on their museums, and had been fun. Almost everyone commented that the Mapping Museums team had identified numerous museums that they had never encountered, and that our data would inform their work, particularly with respect to unaccredited museums.

Ultimately, the experience was incredibly productive. It was a pleasure to meet such a dedicated and knowledgeable group of people. We are very much looking forward to the point when we can provide them, and others, with the completed data.

© Fiona Candlin October 2017

 

 

 

 

Categories
Research Process

One Year On: The Principal Investigator’s View

The Mapping Museums project has just reached its first birthday. One year in, and Dr Jamie Larkin, the researcher, has almost completed the data collection. We now have an extremely long list of museums that are or were open in the UK at some point in the last sixty years. My co-investigator Professor Alex Poulovassilis and the Computer Science researcher Nick Larson have made good inroads on designing a database that will allow us search and visualise that information in complex ways. For me, it has been a pleasure to collaborate with other academics rather than to work as a solitary scholar as is usually the case for those working within the arts and humanities, and the process of conducting the research has been both fascinating and demanding. In this post I’m going to outline the three issues that have most preoccupied me over the last twelve months. They concern the definition of museums, their classification, and the structure of the database.

 Challenge No. 1: Defining a museum

One of the central aims of the Mapping Museums project is to analyse the emergence of independent museums in the UK from 1960 until 2020. In order to accomplish this task, we have had to compile the list mentioned above, and to do that we have had to decide what counts as a museum. This has not been straightforward. While the Museum Association and the International Council for Museums both publish definitions of museums, there have been seven different definitions in use during the time period covered by our study. If we were going to use a definition, we would have to decide which one.

More importantly, the use of definitions of museums only became common in the early 1990s and was closely connected to the accreditation process. In consequence, professional definitions of museums are usually aspirational and prescriptive, and they set standards that cannot be matched by many small amateur and community museums. The Mapping Museum project has a strong focus on such grass roots museums, and if we used established definitions, then we would exclude the less professionalised venues from the outset. We needed to find a different way of deciding which venues would be included in our dataset, and thus my first challenge was: how could we identify a museum as such?

Challenge No. 2 Classification

One of our research questions concerns the possible correlations between the date on which a museum opens, its location, and its subject matter. I want to know whether there are historical trends in subject matter: whether museums of rural life tended to open in the 1970s, military museums in the 1980s, and food museums in the twenty-first century. Similarly, I want to consider the relationship between subject matter and place: it’s likely that fishing museums will be located on the coast, but are there other, less obvious, regional differences? Do local history museums cluster in parts of the UK that have been subject to gentrification, or the opposite – are they predominately found in areas of low economic growth? Do transport museums prevail in the West Midlands and personality museums in the East of Scotland? Or are there no noticeable trends?

In order to answer these questions, we need to categorise each museum according to its subject matter. The last time this happened was in the DOMUS survey that ran between 1994 and 1998. They used a relatively traditional classification system that was suitable for documenting conventional public-sector museums, but was much less useful with respect to small independent venues. Many museums, such as those of Witchcraft, Bakelite, Fairground Organs or Romany life, take non-academic subjects as their focus and they do not neatly fit into academic categories. DOMUS did have the category of ‘social history’, but if we used that for all small non-academic museums, it would be so extensive as to be meaningless, and besides, social history is a methodology rather than subject matter. My second challenge, then, has been to write a classification system that could encompass the diverse subject matter of small independent museums alongside that of the more traditional institutions.

Challenge No. 3: Designing a database

While it was undoubtedly a challenge to find criteria for identifying museums and to devise a new system for classifying them, both these tasks related to my areas of expertise, namely museums. The third major challenge was a long way outside of my comfort zone and concerned the database design. This task was utterly anxiety inducing because it is something I’d never done before and, admittedly, never even thought about, and yet, despite my inexperience, I recognised that it is an extremely important part of the project. Although Dr Larkin has been collecting data on museums, and I have been working on definitions and classifications, that labour will be of little use unless we can search and model it in such a way that it produces information. The design of the database has a direct impact on the possibility of my answering the research questions and on the production of knowledge more generally. It has therefore been imperative that I learn to think about and help develop its structure.

How I responded to these three challenges, and worked with other members of the research team to resolve them will be an ongoing theme in this blog and the subject of scholarly publications. Do keep a look out for more posts.

©Fiona Candlin October 2017

Categories
Research Process

Mapping Museums: Why bother?

Readers who have followed our blogs to date may have realised how much work, time, and money is involved in mapping museums across the UK. The team currently comprises of two professors, and two full time researchers, one in computer science and one collecting and analysing data. By the end of its four-year life span, the project will have cost over a million pounds. On a more personal note, I spent well over a year planning the project and writing a proposal and it now dominates a good part of my waking life, all of which begs the question: why bother? Why does this subject merit such personal, economic, and intellectual investment?

There are pragmatic reasons for the research. The lack of data and of historical research means that museum professionals and policy makers do not have a clear idea of when or where the independent museum sector emerged in the UK, or how it has changed. There is no long-term information on patterns of museums opening and closing, or of their subject matter. Museum professionals who have spent their working lives in a particular region, have been involved with the Area Museums Councils, or with a special interest group, may have a good grasp of the museums in their locale or remit, but their knowledge is not always documented or relayed. In consequence, younger staff charged with supporting museums or staff who are responsible for making decisions about funding may not always have a clear overview of the sector. By compiling a dataset of museums, and modelling trends, this project has the potential to inform museum policy and funding at a national level.

There are also historical reasons for mapping museums in the UK. The museums boom of the 1970s and 1980s (or possibly 1990s) is generally considered to be one of the most significant cultural phenomena of the late twentieth century and yet we know very little about it. Commentators of the time generally linked the rising number of museums to the conservative administration led by Margaret Thatcher, to the economic policy of the time, and to consequent de-industrialisation. This led to the wave of new museums being characterised as entrepreneurial, nostalgic, and often as politically reactionary, but there is very little evidence to substantiate those claims. It might be that many of the new museums were dedicated to rural life and were coterminous with the industrialisation of farming, or they may have focused on religion, or writers, or teddy bears. The Mapping Museums research will enable researchers to revisit the museums boom, and potentially to recast the museums of that period.

For me, though, the main point of the project is linked to who established independent museums and to the people still running them. Museums are generally discussed in relation to the national or public sector, while curation and other forms of museum work are understood to be specialised professional roles. And yet, in 1983 the Museums and Libraries Council commented that most of these new, small enterprises had ‘been set up in an initial wave of enthusiasm and volunteer effort’, and my initial research suggested that the vast majority were founded by private individuals, families, businesses, special interest and community groups. It is likely that amateurs drove the expansion of the museum sector. In identifying these venues and in documenting the work of the founders and volunteers, the Mapping Museums project will show how the recent history of museums was a grass-roots endeavour, or as Raphael Samuels put it, ‘the work of a thousand hands’.

©Fiona Candlin September 2017

 

 

Categories
Research Process

Building the Database

The Mapping Museums project is an interdisciplinary one between Arts and Computer Science and as such a challenge in many ways as discussed in the earlier blog on “Interdisciplinarity“. The project is being run using an iterative and collaborative methodology, as the data collection often leads to new knowledge that needs to be modelled and retained. This incremental accumulation of data and knowledge means that flexibility is important so as to be able to respond to frequent changes.

We, therefore, use a Semantic Database to store and describe our data: semantic databases are also known as Triple Stores and they store pieces of information in triplets of the form Subject-Predicate-Object. For example, the fact that the Science Museum is located in London would be stored as the triplet Science Museum-hasLocation-London. The data model that describes entities (such as museums and locations) and the relationships between them (such as hasLocation) is sometimes called an Ontology.

This kind of data model can easily be extended with new triplets as new data and knowledge accrue. It can also easily be integrated with other already existing ontologies, for example relating to geographical regions and types of museums. Equally important, it allows us to describe in fine detail the different relationships between entities.

In our project, the data is first recorded within Excel spreadsheets. It is then converted into a triplets format to load into our database.  We encode the metadata, e.g. the data types and relationships, directly within the spreadsheets as additional header rows, so as to keep the model and the data “in sync”.

In more detail, the processing of the Excel spreadsheets comprises several steps:

  1. The spreadsheet is converted into a CSV (comma separated values) file.
  2. The metadata is converted into a graph, defined in the Graffoo language.
  3. This graph is processed into a number of templates, to be used for converting the data into RDF (Resource Description Framework) and RDFS (RDF Schema).
  4. These templates are used to convert each row of the CSV file into a set of triplets to be loaded into the database (which is stored using Virtuoso).

Once the database has been created, we use it to support a web-based user interface allowing users to explore the data:

 

By using semantic technologies to describe and store the data, we can support a flexible user interface that will allow users to explore spatial and temporal relationships in the data in order to begin to answer the research questions around independent museum development in the UK.

© Nick Larsson, August 2017

Categories
Research Process

Interdisciplinarity

When Fiona Candlin and I first met up in 2015 to discuss the possibility of a research project that would create a database and visualisations relating to the UK’s independent museums sector, I was immediately intrigued. I knew from my previous experiences working on interdisciplinary projects to build specialist knowledge bases that this would be a challenging endeavour – and so far the Mapping Museums project has not disappointed!

The challenges faced in these kinds of interdisciplinary research projects are numerous:

  • the research programme cannot be tackled through expertise and methodologies arising from one discipline, but require multi-, cross- and interdisciplinary approaches;
  • gradual development of a common language of discourse is needed between researchers from the different disciplines: often a term has different meanings in different disciplines, e.g. words such as “design”, “Implementation”, “testing”, “ontology”;
  • from the point of view of the computer scientist, there is typically a lack of well-defined “requirements” at the outset of the research project; identifying a commonly agreed initial set of requirements is a necessary first step, on the basis of which we can then begin to research and design initial prototype software;
  • the production of initial prototypes typically leads to the elicitation of additional and more precise requirements, which often contradict the initial requirements!
  • because the very nature of research is open-ended and non-predictable, the research project progresses in this iterative and collaborative way, comprising successive cycles of
    • requirements elicitation
    • research
    • design
    • implementation
    • trialling

All stages involve the whole project team, as well as possibly additional domain experts and stakeholders.

In the case of the Mapping Museums project, it was evident from the outset that the gradual collection of diverse data and the gradual development of understanding about the required functionality of the database and visualisations would require this kind of iterative and “agile” methodology to be adopted by the research team.

This also pointed to the need to adopt “semantic” technologies in order to develop the database and visualisations, which are better suited to incremental data gathering and knowledge creation than more traditional relational database approaches.

Developing graphical conceptual models of the museums data from the outset of the project has also allowed us to develop a common understanding of the information that the database will contain:

 

The first 9 months of the project have resulted in a first version of the database, and in the conversion of our conceptual models into a formal ontology. We have also started to experiment with some initial data visualisations:

 

© Alexandra Poulovassilis

Categories
Events

AIM! I’m going to map forever…

Last week the Mapping Museums team attended the Association of Independent Museums (AIM) annual conference hosted at Chatham Historic Dockyard. This year marks the 40th anniversary of the foundation of AIM, which itself gives a good indication as to the moment when the growth of independent museums began to gather pace. As our project is working to map historical trends within the independent museums sector, the conference gave us the perfect opportunity to talk to colleagues with a long and deep involvement with independent museums and to meet those who had recently joined the organisation.

More specifically, we attended the conference for two reasons. The first was to create greater awareness of our project, which we hoped would help forge connections among both professionals and those responsible for running individual sites. The second was more prosaic; we aimed to actively gather data from delegates over the course of the two-day event and put more museums on the map!

Publicising the project

The main method of communicating Mapping Museums was a lecture as part of a session on partnerships between universities and museums. The project’s Principal Investigator, Professor Fiona Candlin, provided an overview of our project, emphasising that the museums sector currently lacks comprehensive data, and that our research would chart the growth of independent museums in relation to a host of cultural, political and economic factors.

Professor Fiona Candlin addressing attendees of the AIM conference

 

The lecture was well attended and this exposure led to both  conversations with sector staff who approached the project team later in the day and a significant increase in activity on our Twitter feed (@museumsmapping). These interactions were helpful for a few reasons. On the one hand we were able to discuss forms of practical help for the project and establish new contacts. But for the most part it was reassuring to exchange stories about the difficulties we face with issues like defining museums and knowing that these are shared problems (and frustrations!) across the sector.

It was also useful to talk to subject specialists about issues particular to their museums. Chatting to a delegate responsible for historic windmills about whether they should be counted as museums, she offered her insight that they should so long as their primary operating revenue came from visitors, rather than auxiliary uses such as producing artisanal flour. Meanwhile, delegates from a historic ship talked to us about whether it should be referred to as a museum or as a visitor attraction, and the difficulties of mapping some vessels that could be moored in different locations.

A highlight of the conference was the opportunity to meet Rob Shorland-Ball, a long-time AIM member and museum consultant who was responsible for depositing the AIM archive at the University of Leicester. By doing so he has been instrumental in helping us to record around 200 (often closed) museums that we have found looking through this material, and which we may not have located otherwise. It was great to inform him about the project and thank him for his efforts. Such interactions, particularly with historical data collection, have helped to humanise the research.

 

Delegates helping with the data collection

In terms of the practical matter of collecting data at the conference, we did this by manning a stall in the exhibition hall. Here delegates could come and talk to the project team, check to see if their museum was in our database and add (or amend) their entry if not. In particular we were eager for delegates to tell us if museums were open or closed, and to give us an idea of their subject matter. The benefit of this was that experts – people ‘on the ground’ working at these museums– could corroborate, and add to, our data.

To make the process as easy as possible we created A3 paper catalogues of our database with entries listed in alphabetical order. This meant that delegates could easily browse entries and had enough space to make additions We also had our computer database on hand in case of any problems in finding museums (for example, if the Barnstaple Museum was recorded as the Museum of Barnstaple).

AIM delegates helping with our data collection

 

In addition to this, we also had on show a prototype of our computer mapping model, demonstrated by Nick Larsson, the project’s computer science researcher. The benefit of bringing the model (and we needed to a substantially reconfigure a laptop to do so!) was that visitors could experience the whole of the research process; once they had checked their entry they were able to see how the data would be visualised and its functionality, and thus think about how they could use such a resource once it is finalised.

The vast majority of the delegates that we spoke to were very enthusiastic about the project and some returned to the stall with their friends to encourage them to participate. As a result, delegates made additions to data over 60 entries and offered suggestions of museums were hadn’t heard of. As a result, we are now aware of the John Lewis Heritage Centre, the Christchurch Tricycle Museum (1984-1999), and the Wigston Folk Museum (1981-1990)! We were also given names of regional experts and offers of help to map museums at a local level. Indeed, despite the cutting-edge technological aspect of the project, our ability to collect (often obscure) information is still largely reliant on traditional forms of networked knowledge; an old fashioned form of crowdsourcing.

New data!

 

Overall, the conference was a success on a number of fronts. Our project is much more visible as a result and we have a trove of data and helpful regional contacts. Beyond these tangible outcomes, the most encouraging aspect of the exercise was to be realise that we are working as part of a sector of professionals who have a great deal of enthusiasm for a project detailing museum history, and who are willing to do as much as they can to help add to this knowledge.

 

© Jamie Larkin          June 2017