Socially reconstructing history: The Social History Timestream application.

Tim Fawnsa*, Sian Bayneb, Jen Rossb, Stuart Nicolc, Ethel Quayled, Hamish Macleodb

and Karen Howiee

aCentre for Medical Education, University of Edinburgh, Edinburgh, UK; bMoray

House School of Education, University of Edinburgh, Edinburgh, UK; cInformation

Services, University of Edinburgh, Edinburgh, UK; dSchool of Health in Social

Science, University of Edinburgh, Edinburgh, UK; eSchool of History, Classics and

Archaeology, University of Edinburgh, Edinburgh, UK

Abstract

For centuries, print media controlled by powerful gatekeepers have played a dominant

part in the recording and construction of history. Digital media open up new

opportunities for the social construction of historical narratives that reveal personal and

situated viewpoints. In January 2012, work began at the University of Edinburgh on the

design, development and distribution of a web-based Social History Timestream

application for social history research projects across a range of disciplines. The

application enables researchers to establish dynamically-generated timelines (divided

into days, months, years, decades, etc.), to which researchers and members of the public

can post photographs, textual descriptions and other media. With the addition of meta-

data such as tags and locations, the resulting timelines provide a way to compare

thematically-related events across time.

A primary aim of the application is to provide opportunities for researchers to discover

serendipitous time-based connections between topics and events that might not

* Email: tfawns@ed.ac.uk

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previously have been considered. Key to the project’s success will be an engaging

interface that allows visitors to see public imagery (e.g. items from the news) alongside

personal imagery (e.g. what a given person was doing on that day), organised by themes

(e.g. geography, health, politics or media). Among other things, the interface will allow

comparison of mainstream versions of particular themed histories with the personal

accounts of those who experienced them, or to visualise the development of ideas,

technologies, and social categorisations over time.

At the time of writing, the Timestream application is still in development and is being

piloted with three research projects. This paper will focus on one of these – a history of

photography practices – to describe emerging theoretical and methodological design

considerations, demonstrate the interface and offer insights into the process of using the

Timestream application.

Keywords: history; timeline; social research; dynamic; user-generated; social

construction

Introduction

Since the invention of the printing press, personal, oral, domestic and local histories

have been increasingly dominated in many societies by historical discourses

controlled by print media concerns (Lebvre and Martin 1976). Through selection of

the content and tone of their mass-produced and widely-distributed texts, groups such

as book and newspaper publishers have acted as gatekeepers of the information that

people come to think of as the important events of the past. This has been enacted in

extreme, systematic ways such as post-war textbook control in Germany and Japan

(Hein and Selden 2000), as well as in subtle ways such as disproportionate coverage

of blue and white-collar crime in the United States (Graber 1980). The replicability

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and precision of typography have given printed information the appearance of ‘cold,

non-human, facts’ (Ong 2002, 120) and ‘provided a vast new memory for past

writings that made a personal memory inadequate.’(McLuhan 2005, 189). Not only

have print media exerted significant influence over the perspectives of the members of

societies, they have resulted in increased homogeneity of collective memory across

large populations (McLuhan 2005).

The emergence of digital media has created an opportunity for a broader range of

perspectives to be included in new, socially-constructed historical narratives. What is

known as ‘participatory culture’ (Jenkins 1992) has come to be closely associated

with the capacity of read-write web technologies to enable social media, user-

generated content and a range of other participatory practices which were previously

difficult or impossible to produce or disseminate at scale: ‘One of the most exciting

elements of new media is that they allow us to communicate personally within what

used to be prohibitively large groups. This blurs the boundary between mass and

interpersonal communication in ways that disrupt both’ (Baym 2010, 4).

The implications for power dynamics between ‘producers’ and ‘consumers’ has

been best studied in a media context, and particularly in relation to political discourse

and activism (Shirky 2009). The argument goes that participatory culture

‘increasingly demands room for ordinary citizens to wield … technologies that were

once the privilege of capital intensive industries – to express themselves and distribute

those creations’ (van Dijck 2009, 42). As van Dijck goes on to argue, this stark

polarisation between citizen and industry is overly simplistic, and the utopic vision of

a democratising, empowering internet is matched by a dystopic one that sees

surveillance, control, and economic and social divisions, as equally likely effects of

technological change (Hand 2009). Alongside this are concerns that the scale of

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information produced through ‘citizen journalism’ creates challenges around

information literacy and source credibility (Carlson and Franklin 2011). In any case,

the shift of communicative resources from the few to the many is likely to have

profound implications for social history.

While there is precedent for user-generated accounts of social history – most

notably in the Mass Observation social research organisation of the 1940s and 50s in

Britain (Mass Observation 2012) – the web redefines what is meant by ‘mass’, and

radically decentralises the gaze of the observer. Social scientists, historians and other

researchers are still coming to terms with the implications of the explosion of personal

accounts now openly accessible, and able to be added to, by those with even quite

modest levels of technical skill and access (Wilson, Gosling and Graham 2012).

Recent years have seen a movement towards the privileging of so-called ‘big data’

(Boyd and Crawford 2012), and the large-scale quantitative analysis of digital content

and interactions. At the same time, there is scope within the social media ecology for

a more user-generated, emergent and small-scale approach to social science and social

history research. This paper describes the development of a pilot version of the Social

History Timestream Application (‘Timestream’) as an example of how researchers

and developers can work together to produce environments conducive to such

emergent, user-generated methods for social research. Designed as a free-to-use

research tool, Timestream displays dynamically-generated timelines to which research

teams and members of the public can post photographs, textual descriptions and other

media. Rather than report on an evaluation of the success or otherwise of project

outcomes, the purpose of this paper is to use the experience of designing, developing,

testing and evaluating this tool to reveal insights about the nature of such tools and

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their implication for social history construction and the methodological considerations

of related research.

The Social History Timestream application

Initially funded by the University of Edinburgh Challenge Investment Fund, the pilot

phase of this project (which began in January 2012) is designed to explore the

potential of the Timestream application. So far, the project has involved a four-month

design phase, followed by a period of development and testing. This has involved

building the application, populating the database with data for three research projects

(see Use cases below), and building a visualisation interface to display these data.

Currently, having consulted with members of the research project teams, some further

development work is being carried out in response to their feedback.

Among other things, Timestream allows visitors to see timelines of mainstream

imagery (e.g. items from the news) alongside personal imagery (e.g. what a given

person was doing on that day), and can be organised by themes (e.g. location, health

information, politics or media). In this way, established versions of particular themed

histories can be compared with the personal accounts of those who experienced them

and new social constructions of the development of ideas, technologies, and social

categorisations can be generated. Figure 1 shows an example of personal accounts of

photography practices placed alongside mainstream and commercial events.

Figure 1. about here

Once development is sufficiently advanced, Timestream will enable crowd-sourced

data to be collected via social media with the aim of drawing from a more extended

and diverse selection of historical events than is possible when data are collected from

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a smaller number of sources. This idea might be thought of as ‘Historical

lifestreaming’ – capturing the evolution of mundane or otherwise, personal and public

activities over long periods. Though much of the data collected from social media

may pertain to current events, we hope that the value of seeing themes develop over

longer periods will encourage people to submit accounts of events that occurred prior

to the Web2.0 era. With sufficient data, the combination of many different themes

will become possible and it is through this process that we hope to generate

unexpected discoveries.

There are a number of projects which relate to one or more aspects of the

Timestream application. As an example of social history research, the Mass

Observation projects involve the compilation of personal accounts to generate an

‘anthropology of ourselves’ (Mass Observation 2012). Rather than being a social

history research project, Timestream is a tool for use in research. Indeed, data from

the Mass Observation projects might be usefully entered into the Timestream database

for visualisation. As an application, Timestream is more directly comparable to other

timeline technologies such as Timeglider, Timekiwi, Memolane or Dipity see their

websites, respectively). These applications, however, construct timelines around

single themes rather than facilitate comparison across multiple themes. They are

typically designed for display rather than analysis and do not have customisable filters

for isolating data according to user-manipulated parameters.

To our knowledge, there is no other tool in existence designed for the sort of

comparative, time-based visualisation that Timestream enables. The visualisation

interface is being developed using the Simile Widgets Timeline Javascript library

(Massachusetts Institute of Technology 2009), an open source platform containing a

large number of required functions which can be adapted to Timestream’s needs. This

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library was created from the Semantic Interoperability of Metadata and Information in

unLike Environments (SIMILE) project at MIT which ‘focused on developing robust,

open source tools that empower users to access, manage, visualize and reuse digital

assets’ (Massachusetts Institute of Technology 2008). The use of open source

software aligns well with the inclusive philosophy of the Timestream project and we

plan to make our software open source if further funding is secured after the pilot

phase.

The Simile Widgets Timeline library is integrated with PHP and MySQL to allow

users to interact with a database of events that is designed to be compatible with

event-based data used in other online history projects. This should allow Timestream

to import data from accessible sources and to export data (where permission is given

by the appropriate party) to other platforms. Each research project within Timestream

may be open to the public or restricted to members of the research team. Within this,

events belonging to each project may be further restricted. This enables researchers to

protect information that is confidential while allowing non-confidential data to be

used in other projects.

Use cases

Engaging with real research projects during the pilot phase helped us to build our

design specifications around what is useful in practice. Due to time constraints, we

started by building data entry forms to allow researchers to contribute events while we

were developing the visual interface. This overlap allowed us to tweak our design as

and when unforeseen needs or challenges arose. Three research projects based at the

University of Edinburgh were used as test cases. The benefit to the projects was the

possibility that visualising many discrete events over time could inform further

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analysis by revealing insights and additional questions. Although data for all of these

projects have initially been entered by the research team, the eventual aim is for

members of the public to contribute their own experiences via social media interfaces.

The effect that this opening up of the data might have is considered under the

Methodological Implications section later in the article.

The projects included the Nighttime Dementia Care project, the Theology and

Therapy project (which explored connections between psychotherapy, Christianity

and the language of spirituality in post-war Scotland and England) and the History of

Photography Practices project. This last project, which explores how people have

captured, organised, reviewed and shared photographs over time, is the focus of the

remainder of this article. By adding events that relate to technological change or

adoption, personal accounts (taken from interviews and previously-published case

studies) are contrasted with mainstream documentation of technological advances.

Led by a member of the Timestream team, this work has provided particularly

illuminating experiences of engaging with both the development of the application

and with the process of using it in research. As such, it has been invaluable in

increasing our understanding of the likely requirements and challenges that other

researchers are likely to face when using Timestream. Taking the History of

Photography Practices project as a case study, an explanation is given below of the

sort of data Timestream holds and how it is visualised, followed by a discussion of

practical, conceptual and methodological issues that emerged during design,

development and testing of the application.

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Entering and viewing data

The Timestream database is comprised of event objects, each of which contains

attributes controlled by the event ‘owner’ (the researcher or member of the public

who enters it into the database) such as the date of the event, the interval level to

which the event can be specified (i.e. day, week, month, year, decade or century),

associated images and descriptions. Events are also assigned tags which are precise,

abbreviated analytic codings such as ‘privacy’ or ‘automation’. Sets of tags that

comprise a theme are used to create ‘categories’ which act as filters for determining

which events to display. An example of a category from the History of Photography

Practices project is ‘practices’ which consists of the tags ‘capturing’, ‘reviewing’,

‘organising’ and ‘sharing’. Multiple categories can be compared in parallel so that, for

example, a timeline of news broadcasts on technological developments could be

viewed beside personal accounts reminiscence. Figure 1 (above) demonstrates the

categories ‘personal’, ‘official’ and ‘commercial’.

Data are entered in the context of a particular research project such as those

outlined under Use Cases above. They may, however, be viewed in various different

contexts alongside data from other projects. This enables cross-fertilisation of ideas

where events pertaining to one theme can be associated or contrasted with those from

other, potentially diverse projects. For example, Muybridge’s (1957) ‘Horse in

Motion’, which shows sequential frames of the position of a horse’s legs while

galloping, might reveal an important cross-over between advances in photography and

video. For this reason, the Timestream viewing interface is configured according to

‘views’ rather than projects. A view consists of categories, each of which contains

data from a single project but which may be collated from different projects. Views

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also have parameters such as default display date, date interval level (e.g. day, month,

year, etc.), which tags are highlighted within the events associated with them, and

magnification level (the size at which events will be displayed and, therefore, how

many events can be displayed). Each user can save multiple views, meaning that it is

possible to return to precisely-specified visualisations and share them with other

users. See Figure 2 for an example display of a view and its configuration.

Figure 2 about here.

At the beginning of the pilot, it was difficult to imagine the details of the

Timestream visualisation interface. We did not know, for example, whether time

should scroll horizontally or vertically, or how to display the essence of an event

within a small space. It was not until we had built a simple prototype and begun to

enter data that we were able to make such decisions. Likewise, researchers needed to

see what visualisations might look like before they felt able to make decisions about

what data should be entered and how. Hence, design and data entry became iterative,

interdependent processes that informed each other’s development.

To increase the power and flexibility of visualisations, one researcher suggested

that alongside filtering by categories (i.e. displaying only those events that have been

assigned specified tags), tags could be highlighted within their associated events (see

Figure 2). This meant that we could show where tags were present across categories,

potentially revealing unexpected relationships. In hindsight, this seems like an

obvious requirement but it was not one that we had discussed prior to engaging with a

real research project.

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Through this feature, some Timestream visualisations showed patterns that aligned

with existing theories. For example, the majority of events tagged as ‘organising’

(sorting photos, editing, putting in albums, etc.) were also tagged as ‘sharing’. This

seemed to support the idea that social interaction is an important motivator for

engaging with photograph collections and that this remains consistent across digital

and pre-digital eras. The trouble is that the data were tagged by a researcher who

already held this theory. This means that he may have – intentionally or

unintentionally - been looking for this particular connection. As such, this result really

shows the potential of Timestream visualisations – given appropriate data - to support

such theories, rather than providing convincing evidence of this particular theory. To

carry any real weight, other researchers would need to check the tagging of data

against specified definitions.

Though it seems to have the potential to do so, Timestream is yet to yield any major

revelations. There are several factors that might account for this. Perhaps there are

insufficient data for clear patterns to be found. Perhaps the tagging of events has not

been sufficiently consistent or adequately structured to reveal similarities between

categories. Indeed, this may prove not to be feasible at all – if tagging is done by one

person, how will they know how data should be tagged such that discoveries they are

not expecting can be produced? If tagging is done by many people, how will they

come to agreement on which tags should be used under which circumstances? This

issue might be helped to an extent by allowing categories made up of collections of

synonyms or similar tags (e.g. ‘storing’, ‘organising’, ‘editing’ and ‘annotating’) to be

highlighted, since this could allow for some variation in tagging protocol. Even so, it

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will be difficult to predict how useful this will be until there is significantly more data

held in the system.

Fortunately, tagging is not the only avenue of discovery. Insights can be gained

simply through visual exploration of the unfolding of events over time. The huge

increase in the range of activities people engage in in relation to photography that has

followed the commercial release of affordable digital cameras was put into sharp

perspective by the layout of events within Timestream. At other times, this kind of

exploration was undermined by a lack of visual interest, such as when there were a

large number of events that did not contain images. This resulted in an unhelpful

display of numerous identical placeholder thumbnails. One suggestion was to use

different icons for different categories or sources, or to allocate thumbnails to

specified tags, allowing extra emphasis of particular aspects of the project. Visual

interest could be further enhanced for those themes where location is important by the

inclusion of a map feature that displays events according to both location and time.

Nick Rabinwitz has created TimeMap, a Javascript library to integrate Google Maps

with Simile Widget timelines, which should make this feature relatively simple to

implement. Before including it, however, we must make sure that our interface

performs well with large amounts of data since the map will require extra processing

power. This will be particularly important when the data entry interface is opened up

to the public, since it is difficult to estimate the quantities of data that might be fed

into the database. The pilot phase of this project has not yet provided a realistic test of

the conditions that we are eventually hoping for: many people accessing large

amounts of data simultaneously. The next stage of development will involve

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configuring the system to load data dynamically as it is required (e.g. when a user

scrolls far enough along the timeline).

Definitions

Before concerning ourselves with large numbers of events, some work remains to be

done on the definition of single events. For example, someone describing a concern

about losing photographs led to the question: is it the talking about the worry, the

worrying itself or the loss of photographs that should be recorded as an event? This

was particularly challenging for generic events (e.g. ‘I don’t tend to delete photos…’)

since Timestream relies on attributing a specific date to a discrete event, even if this is

only to within a year or decade. In fact, many of the events described by interview

participants are general, rather than specific. The following excerpt is a typical

example:

‘I kind of gave up ages ago taking lots of photos cos I get distracted from sort of being

present at the event by the fact of taking and framing photos..’

While this is relevant information, it does not clearly differentiate the temporality

of this phenomenon from others. When no specific date could be given for an event, it

was assigned a low specificity (e.g. ‘year’ rather than ‘month’ or ‘day’) which

resulted in many events appearing to occur at the same time (e.g. during the year

2011). Further, to preserve the integrity of the data, we decided not to show events

when the date interval level of the view is more precise than the date of the event (e.g.

when the view interface is set to ‘day’, those events specified to ‘month’ are not

displayed). Instead, a ‘zoom out’ icon is displayed next to those dates for which more

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data is available at greater interval levels. This means that these ‘general events’ can

only be seen alongside a great deal of competing information. Insufficient variation

and precision in the dates of events made it difficult for the project to take advantage

of the time-based visualisation since a sense of progress became more difficult to see.

For some historical accounts, it seems that Timestream’s current design attempts to

impose a particular chronological frame on elements that are not primarily structured

by the temporal. It may be necessary to allow Timestream to register other elements

(e.g. ‘moods’ or ‘trends’) alongside ‘events’ to permit alternative ways of describing

‘historical’ data.

A related issue that undermined the impact of visualisation was Timestream’s

allocation of equal space to all date ranges. Despite containing far more photographic

events that occurred between 2000 and 2010, equal screen space was given to the

period 1800 - 1810. It may be preferable, at least for some research projects, to

dynamically re-scale the space given to different intervals. Perhaps such flexibility

could even allow for alternative temporal perspectives such as the Greek notion of

Kairotic time which is non-linear and moves – subjectively - at different speeds

(Adam 2004). Despite its current structure, the ethos of Timestream allows for some

temporal ambiguity in that it enables multiple, simultaneous histories. In this light, it

seems appropriate that the invention of photography was proclaimed on four different

occasions between 1790 and 1840.

Engaging with these difficulties illustrated a tangential benefit that emerged from

the use of Timestream. It coerced researchers into reflecting on their own research and

research processes. As they entered data, certain qualities of their projects and

practices came to light. For example, the History of Photography Practices project had

originally been considered to begin in the 1820’s with Nicéphore Niépce’s heliograph.

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By visualising the progress of related events, the impact of events that occurred much

earlier became clearer. Various developments of chemical exposure and uses of the

camera obscura were added. Equally, when considering what to do with events that

could not be dated, researchers came to appreciate the usefulness of collecting date

information along with interview anecdotes, not just for Timestream’s visualisations

but for analysis in general. Hence, their engagement with Timestream may have

changed their future research practice even if they choose not to continue using the

application.

If defining events was problematic, consistent, meaningful tagging was also far

from simple. For example, it was unclear whether the ‘organisation’ tag should

represent reports of both organisational practices (e.g. sorting photos into albums) and

the lack of organisation (e.g. ‘I always mean to sort through my photos but never

do’)? In conventional, qualitative research this would generally make sense since a

theme of ‘organisation’ could usefully contain all aspects of the data relating to

approaches to organisation. Yet in a Timestream visualisation, it is important for these

oppositional events to be clearly differentiated to avoid a false impression of the

evolution of organisational events over time. Adding some interpretative description

from researchers to the event data was somewhat in explaining the event’s context

and how it related to other events within the project. From a visualisation point of

view, however, this proved to be a poor substitute for a clear tagging structure.

Methodological  implications

‘The value of visual methodologies lies in their ability to open up new and previously

unconsidered lines of inquiry’ (Banks 2007, 113).

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The dynamic nature of the form and content of new production platforms requires

researchers to devise new methods of investigation (van Dijck 2009). Tools like

Timestream open up new spheres (both public and private) for production and become

sites of exploration of the changing course of digital scholarship. However, they must

first be widely adopted or, as Shirky (2009) claims, they must become

‘technologically boring’ and, therefore, taken for granted before they become socially

interesting. For Timestream to be effective, substantial amounts of relevant media

must be posted (by members of the public, for example) that relate not only to current

times but to historical periods. To take full advantage of this tool, it must also be used

by researchers to explore a cross-fertilisation of ideas, including data that has been

entered by people outside their own teams.

Using the potentially rich data of others must be balanced by each research team in

relation to issues of reliability of information and source credibility. Using the

application in this way will challenge researchers’ sense of control and encourage

them to examine their position in relation to what counts as history. Given the

potential scale of information, accounts provided by members of the public may need

to be made available without any moderation by researchers, yet may lack credibility

in a traditional sense (Franklin and Carlson 2011). This raises important philosophical

questions that must be faced by researchers who wish to make use of these data. To

what extent should history be constructed only from information that can be verified

through traditional parameters? Which sources are valid in a particular context and

which are not? Which accounts have the right to contribute to history and which do

not?

Widespread social media adoption produces another potential implication – the role

of members of the public not just as contributors but as researchers. By using the

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interface to produce their own cross-themed visualisations, they may produce new

areas of enquiry and, if provided with a channel for communicating ideas to the

research community, contribute usefully to a field of knowledge. However, there are

ethical issues to consider since the public as participants are not bound by established

conventions around informed consent and other means of protection, nor must they

engage in peer review or any other process to establish the credibility of their

accounts.

Ong (2002, 95) wrote that, as a one-way medium, the printed word cannot be

challenged in the way that the oral word could be. Perhaps the digital word allows this

imbalance to be redressed, giving the public a voice with which to reply (as recently

exemplified in North Africa and the Middle East, see Cottle 2011). For Timestream,

this capacity for members of the public to build alternative histories is reliant on the

inclusion of personal and other non-mainstream accounts. At the same time, it is

important to realise that, just as software cannot perform analysis on behalf of

researchers, tools such as Timestream cannot construct history for us. Instead, we

must use them to help us do the work ourselves, in a critical and transparent fashion

and with an accompanying justification of our choices (Lewins and Silver 2007). It is

not the ethos of the Timestream simply to depriviledge historical ‘grand narratives’ in

favour of the local and the personal; rather, the aim is to place the two alongside each

other in new ways which allow us to ask new research questions.

New media and technologies can bring to the fore issues that have long existed but

that have become obscured. For example, the selective nature of historical accounts is

reflected in Timestream’s visualisations. Simply by including or excluding a tag from

its filters, we can see how easily a view of history can be constructed or dismantled.

Just as historical accounts are generally biased towards the elements that are most

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convenient to include, those data that fit neatly into the Timestream database structure

are likely to be privileged over those that do not. Information privileging within

Timestream extends to titles, image thumbnails and tags which are more prominently

displayed within the visualisation than are descriptions. Events that can be clearly

dated are privileged over those for which the date cannot be easily determined. The

exaggerated prominence of certain metadata is a danger for researchers and a

challenge for the design of the interface. For example, the order in which events are

displayed introduces a significant bias since it is inevitable that some information will

not fit on the screen – this must be accessed via a hyperlink that displays a popup

window with the rest of the events from that particular date. How should the

application decide which order to present information by default: at random, by date

of the event, by date that the event was entered in the database, or by whether or not it

has a thumbnail image? These decisions have implications for the visualisation and,

consequently, the interpretation of conclusions drawn from the data.

These issues are of general concern for social media research since the interfaces

into which we enter information encourage some forms of content and preclude others

(Lanier 2010). The outcome is a levelling and sharpening effect on our digital,

collective memory where some aspects are exaggerated while others fade (for a

description of this phenomenon in relation to individual, episodic memory, see Koriat,

Goldsmith and Pansky 2000). Within the social media sphere, fragmented narrative

elements are often preserved (consider Facebook status updates, for example) while

associated emotional and sensory information are removed due to incompatibility

with the conventions of the system. In contrast to Facebook’s timeline, however,

which forces a particular format onto individuals’ personal information (for a

description of this feature at time of writing, see Freeman 2012), Timestream allows

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personalisation of the format of shared, communal information. This allows an

ongoing reconstruction of histories, not just in terms of content but also of structure,

resulting in a fundamental shift in control from the software to the user. Here,

Timestream takes advantage of the fact that, while they are unable to contain certain

types or qualities of information, social media are uniquely configurable and can be

manipulated into various contexts (Bayne, Ross and Williamson 2009).

Conclusion

This article has described insights gained through the design and development of a

research tool aimed at helping researchers to make time-based connections between a

wide range of topics through flexible, thematic visualisation. Focusing on our

experience with a research project on the history of photography practices, it

describes the challenges of defining what constitutes ‘an event,’ how databases and

interfaces can be designed to maximise clarity and minimise distortion of data, and

the methodological implications of allowing multiple and conflicting voices to

contribute to a socially-constructed history.

Any subject area could make use of the alternative perspectives that Timestream

offers, although some may be more amenable to the interface due to factors such as

the number of clearly defined events, the detail of information available, and the

extent to which historical discourse has been controlled by key media players.

However it is used, Timestream cannot discover ‘the real history’. Rather, it enables

multiple versions of history to run alongside and connect with each other. Rather than

showing history as a sort of family tree (as one research team initially requested), the

Timestream interface might be described as generating a rhizomatic conceptualisation

(Deleuze and Guattari 1988) which encourages us to view mainstream accounts of the

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past with a critical eye, not by claiming that they are wrong, but by showing that there

are other valid accounts and that all accounts have the potential to relate to each other

in meaningful ways.

Acknowledgement

The authors would like to thank the University of Edinburgh’s College of Humanities

and Social Science Challenge Investment Fund for funding the Timestream project.

Note on Contributors

All authors are employed by the University of Edinburgh. Tim Fawns researches digital

photographs and memory and is Programme Coordinator of the MSc in Clinical

Education. Sian Bayne’s guiding idea is that ‘the digital’ opens up profound

challenges for the project and purpose of education. Sian is Personal Chair of Digital

Education. Jen Ross’s research focus is online distance learning, Massive Open

Online Courses (MOOCs), digital futures, reflective practices, and cultural and

educational institutions online. Jen is Programme Director of the MSc in Digital

Education. Stuart Nicol has worked on projects exploring geography and time and is

an eLearning Advisor for Information Services. Ethel Quayle’s research focuses on

Internet sex offending and the role of abuse images. Ethel is Senior Lecturer in

Clinical Psychology. Hamish Macleod’s primary focus is the uses of digital

communication technologies and games in higher education practice. Hamish is

Senior Lecturer on the MSc in Digital Education. Karen Howie is the IT Manager in

the School of History, Classics and Archaeology. She supports eLearning and

distance learning and is interested in the recording of historical timelines.

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