The Epiphany Project: Discovering the Intrinsic Value of Museums by Analysing Social Media
David Gerrard, Loughborough University, UK, Thomas Jackson, Loughborough University, UK, Ann O'Brien, Loughborough University, UK
There has been plenty of discussion about how museums may potentially offer more value to visitors than is easily accounted for using instrumental measurements such as attendance figures. Open-ended questionnaires or interviews may provide deeper insight into the impact of museum activities, but they can be intrusive and hard work, and they only provide snapshots of visitor disposition at fixed points in time. The Epiphany Project investigates the feasibility of using computational social science techniques to find evidence of the inspiration caused by museums from within visitors’ social media. This paper introduces the Epiphany Project, the problems it will address, and the potential for it to find relevant, valuable data within social media. The initial steps towards defining “inspiration” in a manner applicable to the work of museums are discussed, and the stakeholders who might benefit from Epiphany, their requirements, and the vision for the system’s architecture are described. The issues involved with integrating two ‘heavyweight’ formal stakeholder and requirements management methods into the project’s Agile methodology are also considered.
Keywords: intrinsic value, social media analysis, systems architecture, stakeholder management, requirements analysis, Agile
Museums exist to inspire the public (Museums Association, 2014), but because inspiration is a difficult concept to recognise and account for, they may not receive full credit for the value they provide. Such ‘hard to measure’ benefits of museums—the aspects of their social contribution, which museum staff and visitors know exist, but which are difficult to define and analyse—are often referred to as ‘intrinsic value’ (Selwood, 2010; Graham, 2009; Scott, 2009; Holden, 2004; McCarthy et al., 2004).
The aim of the Epiphany Project is to investigate how museums inspire their visitors by analysing visitors’ social media. The uptake of social media by the public has been dramatic, with between 65 percent and 75 percent of Internet users estimated to have joined a social network in 2011, compared to 8 percent in 2005 (Stein, 2012; Korschun & Du, 2013). Social media uptake has also been seen in the museum sector where, according to figures from Museum Analytics (INTK, 2013), the totals of Twitter followers and Facebook “Likes” for the top ten socially connected museums have both increased by over one million in the last six months (7,855,866 to 9,064,848 Twitter followers; 7,634,751 to 8,868,417 Facebook Likes, between August 2013 and February 2014). Data from social media is now a significant part of the emerging discipline of computational social science (see below).
The Epiphany Project’s objectives include:
- Developing a model of inspiration and a related computer system
- Using the model to capture relevant data from museum visitors’ social media to use as evidence of inspiration
- Producing research that museums find valuable
This paper describes the lead-in to the Epiphany Project, during which:
- The definition of ‘inspiration’ was explored with a variety of museum professionals
- Practical applications for the proposed system were uncovered, high-level requirements defined, and opportunities to work in partnership with museums found
- Potential architecture and software components for the system were considered
- The work of delivering major system functions was scheduled using an Agile planning methodology
The paper concludes by considering potential ways to measure the advantages the system could bring to museums.
2. Theoretical background
Inspiration is central to the purpose of museums, but the term is hard to define. The Epiphany Project’s initial definition, based mostly upon museum studies, psychology, and politics literature, was: “. . . an experience consisting of a combination of rational thoughts and emotion.”
- Experience recognises how tangible, physical objects and places may inspire people, and comes from literature relating to the effects of arts and culture (e.g., Selwood, 2010; Eisner, 1985; Dewey, 1934), and the material culture of museums (e.g., Soren, 2009; Csikzentmihalyi & Hermanson, 1995).
- Rational thoughts emphasises the importance of intellectual ideas and factual content to museums, and the impact disseminating such ideas has upon society (Gerrard et al., 2013, Barrett, 2011; Johnson, 2010; Dahlberg, 2001; Calhoun, 1992; Duncan, 1991; Žižek, 1989).
- Emotion recognises that inspiration has an emotional “kick.” Indeed, the Cartesian separation of rationality and emotion is now considered unrealistic (Pinker, 1998; Damasio, 1994). Instead, human experience consists of the constant, subtle interplay of emotion and rationality (Gross, 1998), bringing a bewildering degree of complexity to the relationship between culture and the individual (Melchionne, 2010; Connolly, 2002).
An academic term for researching human activity using Internet data is computational social science (also computational sociology or digital social research). It is an interdisciplinary approach involving the social sciences, computing, mathematics, and physics (Lazer et al., 2009). Social media provides a significant and fast-growing source of data for such computational social science studies (Edwards et al., 2013; Boyd & Crawford, 2012; Giglietto et al., 2012), enabling near real-time, longitudinal analyses that were previously only analysable using ‘snapshots’ of small populations (Karpf, 2012).
The Project’s research activity has been divided into five phases: an initial ‘lead-in’ and four case studies. This paper describes the lead-in, which had the following objectives:
- Further define inspiration
- Find opportunities for collaboration with museums for the case studies
- Discover valuable uses for a model of inspiration
The core activity undertaken during the lead-in was a consultation with museum professionals. Relationships with these professionals were managed using a stakeholder management framework, and requirements for the Epiphany system that emerged from the discussions were captured using a requirements management process. Experiments with potential tools were conducted, a candidate architecture for the system emerged, and a schedule for the Project’s development tasks was produced.
To help produce research that museums value, an Agile Systems Development (or simply Agile) methodology was chosen. Agile prioritises customer satisfaction by centralising stakeholders and their requirements, with the intention of delivering a system that most benefits stakeholders in the shortest time, then adding further valuable features, for as long as investment in system development is justified by the value returned (Beck et al., 2001). At first glance, the lead-in’s activities may seem to be incompatible with Agile: this apparent contradiction is discussed further below.
3.1 Consultation with museum professionals
A consultation with eleven museum professionals (listed in Table 1) took place during meetings at six museums in the United Kingdom between October and December 2013.
|Professional’s Role||Museum Type||Museum Focus|
|Curator 1||History and art||Global / multicultural history|
|Curator 2||History and art||UK history|
|House Manager||Heritage site||Society and politics|
|Learning and Engagement Officer 1||Heritage site||Society and politics|
|Director (retired)||History||Society and politics|
|Marketing Manager||History||Society and politics|
|Learning and Engagement Officer 2||Heritage site||Industrial and social history|
|Public Relations Volunteer||Heritage site||Industrial and social history|
|Digital Manager||Central museum services||Various|
|Visitor Studies Curator||Central museum services||Various|
|Policy Research Officer||Central cultural services||Various|
Table 1: Museum professionals consulted
The list of professionals grew organically: initial opportunities arose from participation in the Museum Development East Midlands “Digital Strategies” programme (http://mdem.org.uk/support-grants/development-programmes/digital-strategies/); others came from the researcher’s personal network, while some sourced using desk research. The definition of inspiration was also discussed with delegates at the Let’s Get Real conference in September 2013 (Culture 24, 2014).
Interviewees were asked for their definition of inspiration first, before ideas from the project’s literature review were discussed. After each meeting, the definition was revisited and altered, and the new definition carried forward. The topic of emotion in museums was focused upon, with particular reference to the role of museums in tackling controversial subjects (e.g., Ashley, 2014; Russo, 2011). Participants were encouraged to consider and refer to their day-to-day work activities in the context of the theoretical aspects of the discussion in order to ground the conversation in more practical concerns.
3.2 Integrating formal management processes into Agile
Managing stakeholders and their requirements is crucial if valuable work is to be delivered, so two frameworks for stakeholder and requirements management were chosen: Bourne’s Stakeholder Circle (Bourne, 2009) and Robertson and Robertson’s Volere requirements methodology (Robertson & Robertson, 2013). Adopting such formal frameworks may appear “non-Agile,” but in fact, Agile mandates plenty of attention to planning, requirements management, architecture, and design, but suggests doing so mostly when development is underway, rather than “up front.” To quote Cohn:
Because we acknowledge that we cannot totally define a project at its outset, it is important that we do not perform all of a project’s planning at the outset. Agile planning is spread more or less evenly across the duration of a project (Cohn, 2005:10 – emphasis applied).
Agile projects are divided into short, regular work cycles, and time is set aside within these for planning, design, and process improvement (Crispin & Gregory, 2009; Schwaber, 2004). In this spirit, both the Stakeholder Circle and Volere were chosen after a brief review of available frameworks, and then reviewed and adapted throughout.
3.3 Stakeholder management: the Stakeholder Circle
Identifying stakeholders is a vital to project success. Stakeholders are: “…those individuals, groups, and other organizations who have an interest in the actions of an organisation and who have the ability to influence it” (Savage et al., 1991: 61). Their “stakes” may be general interests in, ownership of, or legal or moral rights over things that the project affects (Buchholtz & Carroll, 2012; Bourne, 2009). Of course, stakeholders and their stakes also change over the project’s duration (Mitchell et al., 1997).
The Stakeholder Circle manages all these aspects and also tracks the influence each stakeholder has over other stakeholders, and their attitudes towards the project. Four criteria are used to assess each stakeholder’s potential impact:
- Power to change the project. Out of four: four indicates those that can stop progress.
- Proximity to the work. Out of four: four indicates those who work on the project daily.
- Value of the project to the stakeholder. Out of five: five indicates those with a major personal stake (e.g., their future career depends upon the project).
- Action: the likelihood that the stakeholder will do something. Out of five: five indicates those who would go to any length to affect the project
The result is a “big-picture” view of all stakeholders that allows consistent assessment and prioritisation, indicates when relationships with stakeholders change, and aids communication (Bourne, 2009).
3.4 Requirements analysis and system architecture
Another purpose of the initial consultation was to discover practical uses for this research. The Volere requirements methodology was therefore chosen, as it contains a “project blast-off” phase to investigate the potential project value. This blast-off considers the context of the work that the project affects, constraints upon the project, and the risks involved. It also determines a concise but measurable project vision (Robertson & Robertson, 2013). As before, some might suggest that such upfront analysis is not “Agile,” but three Agile planning texts referred to (Leffingwell, 2010; Cohn, 2005; Schwaber, 2004) also stress that scoping and feasibility assessment take place before work commences. One key difference with Agile is that a project’s “go/no-go” decision should be revisited throughout, rather than being a one-off hurdle before commencing.
Another key activity of project blast-off is to define the work area affected by the proposed system, and activities around the project’s boundaries. This contextualisation results in a list of high-level requirements for the project.
As with stakeholder management and requirements analysis, designing system architecture is another task that is often considered “non-Agile.” The same idea applies as before, however: Agile projects should have as much attention paid to architecture and design, but attention should be spread across the project, rather than be applied up front (Leffingwell, 2010). Furthermore, Agile also recommends that developers undertake short experiments (or ‘spikes’), lasting no more than one working day, into potential technological solutions. Accordingly, experiments with Twitter API libraries, a graph database application (Neo4J), a text indexing and search application (Apache Solr), and a Web crawler (Apache Nutch) were all conducted during this phase and fed into the architectural vision.
The key findings of the lead-in phase are summarised below:
- The definition of inspiration derived from the literature was broadly acceptable to those consulted, but lacked two key aspects of inspiration relevant to museums:
- Inspiration may grow incrementally as the result of a set of related experiences (e.g., regular visits).
- Inspiration results in output or change of some sort (e.g., fresh ideas or the motivation to try new activities).
- Exactly how a museum inspires its visitors will be tightly coupled to its collection; each museum will inspire in different ways.
- There had already been a previous attempt to model something like ‘inspiration’ that the literature review had missed (Morris Hargreaves McIntyre, 2006).
- A clear practical application for the Epiphany Project would be providing evidence for event and exhibition evaluation reports.
- The Apache Solr application (for text indexing and search) is powerful and easy to set up, configure, and integrate. It is therefore likely to play a much larger role in the architecture than first thought.
Confirmation that an extended definition of inspiration might be more accurate came from the final interview, where a curator provided the following description of inspiration:
I think probably you do have an emotional reaction. And usually there’s a connection with something of interest in your life or your research. You’ve got that emotional and intellectual connection at the same time, which makes you want to go on and do something in response to it. So it’s an active thing – it makes you want to respond in some way (Interview with Curator 2).
4.1 Detailed findings concerning the definition of emotion
With regard to the definition of inspiration, the consultation exercise found that:
- Museum professionals agree that inspiration is at the core of museum activity and hence worth accounting for in some way:
- Some of those consulted indicated that it might be hard to convince senior managers and strategic planners of this, however.
- Some of those consulted referred to an alternative model of inspiration involving a hierarchy of “motivational drivers” for museum visits, starting with “social,” moving onto “intellectual,” then sometimes onto “emotional,” and occasionally reaching a “spiritual” level (Morris Hargreaves McIntyre, 2006: 27).
- Inspiration is both defined and constrained by museum collections:
- The Curators in particular thought about their collections first, then about potential themes and audiences.
- One Curator described a “unique quality” of material objects: their ability to focus abstract ideas (such as democracy or religion) upon concrete reality, allowing visitors to consider the everyday, social implications of abstract ideas in ways that may counteract dogmatic teaching, or even indoctrination.
- Emotion was considered vital to inspiration:
- The House Manager recounted instances of fainting due to the stories from her museum.
- Both the Curators discussed appealing to visitors’ emotions to make exhibitions more inspiring.
- Deliberate play upon “negative” emotion (e.g., fear, anger, sadness) was more problematic, however. One Curator cited a UK Museums Association survey which indicates that the public dislikes controversy in museums (BritainThinks, 2013). The House Manager seemed more open to the idea of exploring “difficult” topics. However, both concurred that objects should “speak for themselves” when provocative ideas arose.
- Inspiration results in an output or change of some sort:
- A delegate at Let’s Get Real suggested that purely internalised thought and emotion might be “admiration” not “inspiration.”
- Other participants suggested inspiration leads to “a desire to explore things further,” or changes in behaviour or even in personality.
- Inspiration can build, subtly, over a series of experiences: it need not result in a major revelation. This in turn links it to the personal experience of the viewer and supports assertions made by Johnson (2010) and Graham (2012, 2009).
4.2 Findings regarding stakeholders
Table 2 illustrates how the Stakeholder Circle can be used to prioritise stakeholders in terms of the impact they might have, using the Power, Proximity, Value, and Action criteria described earlier:
|Name (Ordered by impact index)||Power||Proximity||Value||Action||Index|
|Ph.D. Supervisor 1||4||4||4||4||16|
|Ph.D. Supervisor 2||4||4||3||4||15|
|Museum Manager 1||4||3||4||4||15|
|Communications Volunteer 1||2||3||4||4||13|
|Museum Director 1||3||3||3||4||13|
|Communications Manager 1||3||3||3||3||12|
|Learning and Engagement Officer 2||2||2||3||3||10|
|University Ethics Committee 1||4||2||1||3||10|
|Research Funder 1||4||2||2||2||10|
|Museum Strategist 1||2||2||3||2||9|
|House Manager 1||1||1||2||3||7|
|Digital Manager 1||1||2||2||2||7|
|Policy Research Officer 1||1||2||2||2||7|
|Project Manager 1||2||1||2||1||6|
|Learning and Engagement Officer 1||1||1||2||2||6|
|Visitor Studies Curator 1||1||2||1||2||6|
Table 2: Stakeholder impact
The stakeholders that scored high for Power all have the ability to stop the project. In the case of the supervisors and the research funders, this seems obvious, but viewing all the stakeholders comparatively in this fashion also emphasised other information that might have been in danger of being overlooked; in this case, the power of the University Ethics Committee to halt work. The importance of communicating clearly with them and acting quickly to address any of their concerns was therefore emphasised.
Another vital piece of information that surfaced from organising stakeholder information in this way concerned two museums that might provide case studies for the project. The staff from those particular museums all registered high scores for Value and Action, indicating that the project could potentially provide valuable outcomes for them, and that they were enthusiastic to find out more about the project and potentially get more involved.
4.3 Findings related to work context
Figure 1 contains the work context diagram for the Epiphany Project. The flow of data between the work area and adjacent systems indicates where the project’s boundaries lie. Note: at this stage in an IT project in particular, it is important to think of the area affected by the project as a “work area” rather than “the project’s system,” as thinking about the project in systemic terms before properly defining the work involved can cause opportunities to think laterally and creatively about the work being undertaken to be missed, and de-emphasises the role that people will take in delivering the project’s benefits (Robertson & Roberston, 2013: http://bit.ly/1iP9Nno).
https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig1_-1024x687.png 1024w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig1_-446x300.png 446w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig1_.png 1060w" sizes="(max-width: 300px) 100vw, 300px" />
Figure 1: Work context of the Epiphany Project
The surrounding systems that input information into the project’s “work area” as shown by the diagram are (working clockwise from the bottom):
- Visitor’s social media content, which is the main source of data for the project.
- Information about museums’ events (such as exhibitions).
- Museums’ promotional activities (e.g., marketing messages).
- Individuals and organisations in key positions to provide valuable support for museums on the social network: for instance, active Twitter users or popular bloggers who regularly discuss topics relevant to museums’ themes. (Such individuals are often described in marketing terms as ‘influencers’)
- Information about museums’ collections (potentially stored in digital collection management systems).
- An “emotion ontology” used to search for content and group it by the emotions described (Sykora et al., 2013)
Opportunities for delivering business value to museums were discovered by tracking the arrows that flow from the central work area, which show potential information outputs, their users, and what such information might be used for. For example:
- Information about audiences could flow into the audience-development component of a funding application.
- Information from social media indicating the impact of a specific event upon existing or new audiences could be used in an evaluation report for funders, such as the UK Department for Culture Media and Sport, or the Heritage Lottery Fund. All such funders require evidence of the impact their funding has had upon the public.
- Information about the visitor community could be used operationally by museum staff (e.g., in marketing or planning future activity).
- Information about influential experts and enthusiasts that are active on social media could be used to find collaboration partners, sources of knowledge, sources of support, etc.
4.4 Architectural vision
Figure 2 shows a high-level candidate architecture for the Epiphany system. It is based upon both research into the technologies used in computational social science and the short technical experiments (‘spikes’) conducted during the lead-in. The diagram shows the system boundary, with museums, visitors, and their social media outside. Inside are seven components arranged in a pipeline:
- An API client for interfacing with social network platforms (e.g., Twitter or Facebook):
- Spikes of Twitter API client software (for harvesting data from Twitter) indicated that there was potential for creating a longitudinal analysis of Twitter activity around a museum by tracking the changes in the Twitter network. Evidence of inspiration might potentially be found at the heart of such changes.
- A focused Web crawler for following links to websites and blogs of followers of museums, found in their social media posts.
- An initial ‘spike’ with a Web crawler, using URLs harvested from museum followers’ Twitter ‘biographies’ (i.e., the short descriptions linked to Twitter accounts) found several websites that, according to the Marketing Manager interviewed, could be used to produce “personae” of museum users.
- This indicated that the architecture should indeed include some method of harvesting “richer” content than that found in Tweets or Facebook comments.
- A content analyser (i.e., a Natural Language Processor (Marmanis & Babenko, 2009)) for assessing the meaning and relevancy of content found by the Web crawler.
- Experiments with Apache Solr indicated that it has a Natural Language Processor (Apache Tikka) built in. However, there are also C# and Python NLP libraries that could be used.
- Two data stores:
- A business intelligence database for summarising data and displaying demographic and trend analyses.
- A graph database for storing data about relationships between museums, visitors and content (Robinson et al., 2013).
- A logic/rule base for structuring relevancy, language processing, and categorisation knowledge. This could be used by the Web crawler, content analyser, and data stores:
- The logic/rule base will be the core of the Epiphany Project’s model, as it would store the rules about the balance between “ideas” and “concepts” (potentially including lexicons of vocabulary about and taxonomies of relationships between objects from museum collection systems) and “emotions” (from an emotion ontology).
- This could potentially allow content harvested from social media to be clustered around both “concepts” and “emotions” in ways that might highlight the “inspired” content.
- A visualisation system to display the collected data in usable formats:
- Data stores often come with visualisation systems built-in: the graph database that was experimented with during the lead in (Neo4J) is distributed with an HTML5-based visual graph analysis and query tool, while Microsoft provide a suite of tools that allow Excel to be integrated with data from both SQL Server Reporting and Analysis services to produce graphs and charts, for example.
https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig2_-1024x541.png 1024w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig2_-500x264.png 500w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig2_.png 1271w" sizes="(max-width: 300px) 100vw, 300px" />
Figure 2: Architecture of the Epiphany system
4.5 Structuring the High-Level Work Schedule
Using the architectural vision to define key sub-components of the system also helped organise the project schedule. In keeping with the Agile method, the aim is not to deliver all parts of the system as a fait accompli more than a year down the line, but instead to produce smaller chunks of system functionality in a much shorter time frame, and hence provide data and information of potential value to museums sooner.
Figure 3 shows the main tasks (or Epic Stories) of the Epiphany Project spread across four three-month phases (or Releases), using a free online project and task management tool called Trello (https://trello.com). The Epic Stories in each release are ordered by business value; in the first release, “addition of audience analysis to funding application” is considered most valuable, as it could result in funding for the collaborating museum. Focusing upon the main aim of the release is the ultimate purpose of this stage of planning. As an example of how the project aims to deliver the overall system incrementally, the first release can potentially be delivered using only a Twitter API client integrated with a graph database (i.e., parts 1 and 2a of the overall architecture).
https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig3_-1024x663.png 1024w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig3_-463x300.png 463w, https://mw2014.museumsandtheweb.com/wp-content/uploads/2013/09/gerrard.fig3_.png 1119w" sizes="(max-width: 300px) 100vw, 300px" />
Figure 3: Epiphany Project product backlog in Trello
The releases also contain information about the key non-functional requirements that constrain the work, marked with a red tag. For instance, release one is constrained by the specific funder’s audience planning guidance. This is all the scheduling required (or indeed, realistically possible) at this stage: it is only worth examining the work in more detail once development commences.
Perhaps the most important result of this phase was the alteration of the definition of inspiration to:
An experience, or set of experiences, combining rational thoughts and emotions, resulting in the expression or enactment of fresh ideas.
Adding a section about “fresh ideas” supports the notion that inspiration needs to result in an output of some sort, and in turn indicates some potential for social media as a source of evidence, as visitors will at least need to be motivated enough to post comments or blog about their ideas.
Another key (if unsurprising) conclusion was that, despite a degree of consensus from participants regarding inspiration “in the abstract,” every museum’s “mechanism” for inspiration is rooted in its collection, and thus will potentially be quite different. The model of inspiration must be flexible enough to cope with this.
Other conclusions related to the research aims and methods are:
- The formal (and potentially non-Agile) frameworks used thus far have integrated well with an Agile approach to planning: the structured approaches promoted by the Stakeholder Circle and formal risk management seem to fit with the regular review and process-improvement activities mandated by Agile. This is perhaps the most important conclusion for a project manager considering using an Agile approach—Agile should not be considered shorthand for a lack of formality or discipline, but instead be thought of more as an encouragement to spread formal and disciplined project management, stakeholder management, and business systems analysis techniques throughout the lifespan of the project, in parallel with development, instead of “doing it all up front.”
- The Stakeholder Circle encourages fair consideration and comparison of stakeholders, hence reducing the risk of prioritising those that “shout loudest” over those that really matter.
- While it has proved useful for a research project of this nature, it would perhaps be even more effective in a business or organisational project, for two reasons:
- Stakeholders are likely to be “closer” to such projects—PhD research is by nature rather a solitary activity.
- It would encourage a shared “team view” of the stakeholders.
- While it has proved useful for a research project of this nature, it would perhaps be even more effective in a business or organisational project, for two reasons:
- Volere’s project blast-off and the vision of the research it produced have indicated potentially valuable, measurable advantages for museums.
- Techniques (such as data graphing and mining, NLP, etc.) exist to enable a thorough attempt to be made at ascertaining the feasibility of using social media data to help account for intrinsic value in museums.
The following more negative conclusions have also been drawn from the work so far:
- While the importance of accounting for intrinsic value appears broadly supported at “ground level” in the museum profession, some of those consulted indicated that it may be harder to sell the concept to those at a higher, more strategic level.
- While social media may provide a compelling opportunity for this research, it does not necessarily provide a representative demographic of society at large (Giles, 2012). This research intends, therefore, to augment existing visitor studies techniques, not replace them.
- Some open ethical questions exist about the use of the public’s social media for research such as this, particularly related to informed consent (Boyd & Crawford, 2012).
- The chosen methodologies have been developed primarily for business use and must be adapted for academic work. Hence the research risks being drawn towards related business objectives, with potential detriment to academic objectives.
- Many other aspects of Agile (e.g., Test Driven Development) have yet to be applied to the research: incompatibilities between Agile and more formal processes may yet arise.
5.1 Next steps
To successfully deliver its vision and bring valuable advantages to the museum sector, this research will contribute to or result in the following outcomes:
- At least one audience development plan produced for a museum funding bid
- At least one piece of evaluation used to prove the impact of funding
- At least one improvement to promotional activity conducted by a museum
- At least one piece of collaborative activity between a member of museum staff and an inspired visitor
Evidence for outcomes 1 and 2 will be acquired via analysis of documents produced by museums. Evidence for outcomes 3 and 4 will be gained via testimonials from museum staff.
Ashley, S. L. T. (2014). “Engage the world: Examining conflicts of engagement in public museums.” International Journal of Cultural Policy, 20(3), 1–20.
Barrett, J. (2011). Museums and the public sphere. Malden, MA: Wiley-Blackwell.
Beck, K., M. Beedle, A. van Bennekum, A. Cockburn, W. Cunningham, M. Fowler . . . & D. Thomas. (2001). Principles behind the agile manifesto. Consulted August 23, 2013. http://agilemanifesto.org/principles.html
Bourne, L. (2009). Stakeholder relationship management : A maturity model for organisational implementation. Farnham, Surrey: Gower; Burlington, VT: Ashgate.
Boyd, D., & K. Crawford. (2012). “Critical questions for big data.” Information, Communication & Society, 15(5), 662–679.
BritainThinks. (2013). Public perceptions of—and attitudes to—the purposes of museums in society. London: Museums Association. Consulted May 7, 2013. http://www.museumsassociation.org/download?id=954916
Buchholtz, A. K., & A. B. Carroll. (2012). Business and society: Ethics and stakeholder management. Independence, Kentucky: South-Western Cengage Learning.
Calhoun, C. J. (1992). Habermas and the public sphere. Cambridge, MA; London: MIT Press.
Cohn, M. (2005). Agile estimating and planning. Upper Saddle River, NJ: Pearson Education.
Connolly, W. E. (2002). Neuropolitics: Thinking, culture, speed. Minneapolis, MN: University of Minnesota Press.
Crispin, L., & J. Gregory. (2009). Agile testing: a practical guide for testers and agile teams. Pearson Education.
Csikzentmihalyi, M., & K. Hermanson. (1995). “Intrinsic motivation in museums: Why does one want to learn?” In J. H. Falk and L. D. Dierkling (eds.), Public institutions for personal learning: establishing a research agenda (1st ed.). Washington, D.C.: American Association of Museums. pp. 67–77.
Culture 24. (2014). Let’s get real. Consulted February 19, 2014. http://weareculture24.org.uk/projects/action-research/
Dahlberg, L. (2001). “Computer-mediated communication and the public sphere: A critical analysis.” Journal of Computer-Mediated Communication, 7(1). Consulted April 25, 2013. http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2001.tb00137.x/full
Damasio, A. R. (1994). “Descartes’ error and the future of human life.” Scientific American, 271(4), 144–145.
Dewey, J. (1934). Art as experience. New York: Perigee.
Duncan, C. (1991). “Art museums and the ritual of citizenship.” In I. Karp and S. D. Lavine (eds.), Exhibiting cultures: The poetics and politics of museum display (1st ed.). Washington; London: Smithsonian Institution Press. pp. 88–103.
Edwards, A., W. Housley, M. Williams, L. Sloan, & M. Williams. (2013). “Digital social research, social media and the sociological imagination: Surrogacy, augmentation and re-orientation.” International Journal of Social Research Methodology, 16(3), 245–260.
Eisner, E. W. (1985). The art of educational evaluation: a personal view. London: Falmer.
Gerrard, D., A. O’Brien, & T. W. Jackson. (2013). “Controversy and debate within social media: Can museums improve 21st century democracy?” Proceedings of the International Conference 2013 of the Design Research Society Special Interest Group on Experiential Knowledge, 319–331. Consulted November 20, 2013. http://www.experientialknowledge.org.uk/proceedings_2013_files/EKSIG%202013%20Conference%20Proceedings.pdf
Giglietto, F., L. Rossi, & D. Bennato. (2012). “The open laboratory: Limits and possibilities of using Facebook, Twitter, and YouTube as a research data source.” Journal of Technology in Human Services, 30(3–4), 145–159.
Giles, J. (2012). “Computational social science: Making the links.” Nature, 488(7412), 448–450.
Graham, H. (2009). “Department of culture, media and sport’s peer review pilot.” Cultural Trends, 18(4), 323–331.
Graham, H. (2012). “Scaling governmentality.” Cultural Studies, 26(4), 565–592.
Gross, J. J. (1998). “The emerging field of emotion regulation: An integrative review.” Review of General Psychology, 2(3), 271–299.
Holden, J. (2004). Capturing cultural value: How culture has become a tool of government policy. London: Demos. Consulted July 6, 2013. http://www.demos.co.uk/files/CapturingCulturalValue.pdf
INTK. (2013). Museum analytics. Consulted February 19, 2014. http://www.museum-analytics.org
Johnson, S. (2010). Where good ideas come from: The natural history of innovation. London: Penguin.
Karpf, D. (2012). “Social science research methods in internet time.” Information, Communication & Society, 15(5), 639–661.
Korschun, D., & S. Du. (2013). “How virtual corporate social responsibility dialogs generate value: A framework and propositions.” Journal of Business Research, 66(9), 1494–1504.
Lazer, D., A. Pentland, L. Adamic, S. Aral, A. Barabási, D. Brewer . . . & M. Van Alstyne. (2009). “Computational social science.” Science, 323(5915), 721–723.
Leffingwell, D. (2010). Agile software requirements: Lean requirements practices for teams, programs, and the enterprise. Boston: Addison-Wesley Professional.
Marmanis, H., & D. Babenko. (2009). Algorithms of the intelligent web. Manning: Greenwich.
McCarthy, K. F., E. H. Ondaatje, L. Zakaras, & A. Brooks. (2004). Gifts of the muse: Reframing the debate about the benefits of the arts. Santa Monica: RAND Corporation. Consulted July 4, 2013. http://www.rand.org/content/dam/rand/pubs/monographs/2005/RAND_MG218.pdf
Melchionne, K. (2010). “On the old saw ‘I know nothing about art but I know what I like.’” Journal of Aesthetics and Art Criticism, 68(2), 131–141.
Mitchell, R. K., B. R. Agle, & D. J. Wood. (1997). “Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts.” The Academy of Management Review, 22(4), 853–886.
Morris Hargreaves McIntyre. (2006). Audience knowledge digest: Why people visit museums and what can be done to attract them. Manchester, UK: Morris Hargreaves McIntyre. Consulted November 26, 2013. http://culturehive.co.uk/wp-content/uploads/2013/04/audience-knowledge-digest1.pdf
Museums Association. (2014). Museums Association FAQs. Consulted April 10, 2013. http://www.museumsassociation.org/about/frequently-asked-questions
Pinker, S. (1998). How the mind works. London: Allen Lane.
Robertson, S., & J. Robertson. (2013). Mastering the requirements process (3rd ed.). Upper Saddle River, NJ; London: Addison Wesley Professional.
Robinson, I., J. Webber, & E. Eifrem. (2013). Graph databases. Sebastopol, CA: O’Reilly Media.
Russo, A. (2011). “Transformations in cultural communication: Social media, cultural exchange, and creative connections.” Curator: The Museum Journal, 54(3), 327–346.
Savage, G. T., T. W. Nix, C. J. Whitehead, & J. D. Blair. (1991). “Strategies for assessing and managing organizational stakeholders.” Executive (19389779), 5(2), 61–75.
Schwaber, K. (2004). Agile project management with Scrum. Sebastopol, CA: O’Reilly Media, Inc.
Scott, C. A. (2009). “Exploring the evidence base for museum value.” Museum Management and Curatorship, 24(3), 195–212.
Selwood, S. (2010). Making a difference: The cultural impact of museums; an essay for NMDC. London: National Museum Directors’ Council. Consulted July 1, 2013. http://www.nationalmuseums.org.uk/media/documents/publications/cultural_impact_final.pdf
Soren, B. J. (2009). “Museum experiences that change visitors.” Museum Management and Curatorship, 24(3), 233–251.
Stein, R. (2012). “Chiming in on museums and participatory culture.” Curator: The Museum Journal, 55(2), 215–226.
Sykora, M. D., T. W. Jackson, A. O’Brien, & S. Elayan. (2013). “National security and social media monitoring: A presentation of the EMOTIVE and related systems.” Intelligence and Security Informatics Conference (EISIC), 2013 European, 172–175.
Žižek, S. (1989). The sublime object of ideology. London: Verso.
. "The Epiphany Project: Discovering the Intrinsic Value of Museums by Analysing Social Media." MW2014: Museums and the Web 2014. Published January 16, 2014. Consulted .