Analysing Urban Community Informatics from a Resilience Perspective

Richard Heeks & Angelica V. Ospina

Centre for Development Informatics, IDPM, SEED, University of Manchester, UK. Email:;


There is a long history of analysing community informatics from a variety of economic and social perspectives. Loader & Keeble (2004), for example, identify evaluative lenses around access, skills, regeneration, civic participation, and social exclusion. Other lenses have included livelihoods (e.g. Parkinson & Ramirez 2006) and gender (e.g. Gurumurthy 2009). But as yet, there have been few if any attempts to analyse community informatics through a resilience lens.

The purpose of this paper is to fill this gap: to develop a model of resilience and then use it to understand the relation between resilience and community informatics. It is timely to do this because of the rapid rise of resilience up the community development and local governance agendas in recent years. In particular, our focus here will be on urban communities given the growing number of activities such as:

  • In the global North e.g. Local Resilience Forums in the UK (Cabinet Office 2011), and the EU's Transitioning Towards Urban Resilience and Sustainability project (TURAS 2013).
  • In the global South e.g. the formation of the Asian Cities Climate Change Resilience Network (ACCCRN 2013), and UNISDR's Making Cities Resilient campaign (UNISDR 2013)
  • Globally e.g. Rockefeller Foundation's (2013) 100 Resilient Cities challenge.

While drawing from a variety of evidence, our main interest will be on low-income urban communities because these have been most prone to the shocks (such as those arising from climate change) which have prompted the interest in resilience (Rosenzweig et al. 2011, World Bank 2012). They have also, in recent years, been the sites of rapid diffusion of new information and communication technologies (ICTs) and so represent an appropriate focus in seeking to investigate the intersection of community informatics and resilience.

In the following section, we discuss the meaning of resilience within a community, building a systemic model from the literature on resilience but also from the literature on vulnerabilities, livelihoods and adaptation. Next, we use this model to analyse community informatics, looking at the ways in which ICTs may strengthen but also weaken aspects of resilience. Finally, the paper reviews the resilience perspective as a basis for understanding community informatics, and draws some conclusions for future practice.


Past Work on Resilience

Resilience means the ability to withstand and recover from short-terms shocks, and to adapt to long-term trends. It is those shocks which have triggered the literature on urban communities and resilience, including terrorism (Coaffee 2009), natural disasters such as earthquakes (Comfort 1994), and climate events (Whittle et al. 2010) including climate change in particular (Leichenko 2011). Given the non-specificity of resilience - it is of equal relevance to any type of external shock and looks neither at the causes nor effects of those shocks - much of the literature has dealt with generic threats to urban communities (Godschalk 2003, Ernstson et al. 2010).

However, resilience itself is not often conceptualised in any depth within this literature. In some cases, resilience is more written around than written about. This may include use without even definition (e.g. Crichton 2007) but more often resilience is used as a largely taken-for-granted catalyst or metaphor or stepping stone that leaves the focus of the literature mainly elsewhere. For example, Coaffee (2007) analyses not resilience itself but the urban governance responses that an interest in resilience trigger; while Prasad et al. (2009) and Ahern (2011) similarly identify strategies for building resilience via only a brief definition of the core term. Ernstson et al. (2010) take resilience based in systems theory and then use that as the basis for their investigation of urbanisation. Pickett et al. (2004) take this line to its conclusion by studying resilience not as a real property but as a metaphor that provides insights into the urban planning process.

Where resilience is engaged with more directly in the literature, then sometimes the depth of engagement may be restricted to defining the component parts of the definition (Whittle et al. 2010), identifying the socio-technical nature of resilience (Godschalk 2003), or broadening to explain categories of resilience: e.g. physical, social, economic, institutional and natural (Razafindrabe et al. 2009); or social, economic, institutional, infrastructural and community (Jha et al. 2013). These remain broad-brush approaches and may be contrasted with literature that offers a few specific factors that are seen as related to resilience, e.g. social capital (Simpson 2005); a diversified economy, planning, and people (Campanella 2006); or wealth, institutional stability, reliable public infrastructure, global interconnectivity, and natural resource dependence (Tanner et al. 2009). Even the relatively few examples of specificity are challenged by limited overlap and agreement, perhaps because urban resilience is being approached from different foundations including ecological, hazards/risk, economic, and governance/institutions (Leichenko 2011).

We therefore identify a knowledge gap; a requirement for a more thorough conceptualisation of resilience, particularly as applicable to urban communities. Only by understanding resilience properly can we effectively make use of it as a concept: for design of future community informatics initiatives, for implementation of current initiatives, and for evaluation of past initiatives.

Modelling Communities as Systems

Our starting point for understanding resilience is a systematic and systemic understanding of communities, based around the model shown in Figure 1. Full details of the derivation of this model can be found in Ospina & Heeks (2010) but, in brief, it was created from the following principles, which draw particularly from the sustainable livelihoods approach and from Sen's capabilities approach:

  • That communities face a number of acute shocks and chronic trends. Climate change may take prominence among these, particularly given its strong connection to resilience, but there will be others from environmental, social, and economic domains.
  • These shocks and trends interact with a set of key vulnerability dimensions such as livelihoods and finance, socio-political conditions, health, habitat and migration, food security, and water supply.
  • A community can be conceived as a "livelihood system". Actions within the community are determined by the assets available (human, natural, financial, physical, social and informational capitals), by the institutions that shape behaviour, and by the structures that organise those assets and institutions.
  • The adaptive capacity of the community to cope with (withstand, recover from, and change in the face of) external shocks and trends, represents a series of livelihood capabilities. However, only a sub-set of these are converted into actual strategies and actions ("functionings" in Senian terms).
  • The overall functionings of the community are diverse but a sub-set represent specific adaptations or adaptive actions that respond to the contextual shocks/trends. These actions, in turn, alter the determinants and capabilities of the community.
  • The overall actions also drive the outcomes of social, political and economic development seen within the community and beyond.
Figure 1: Communities as Adaptive Systems: Components and Processes (adapted from Ospina & Heeks 2010)

Systems can be understood through three main aspects: structure (e.g. components and relations), process (functions), and properties (Laszlo & Krippner 1998, Skyttner 2001, Fisher 2010). Figure 1 shows the structure and process of a community, but not its properties. It therefore says nothing directly about resilience since resilience is neither a systemic structure nor a systemic process, but a systemic property (Gallopin 2006). Adaptive capacity of systems such as communities derives not simply from the structural elements but also from the properties of those elements in systemic combination (Norris et al. 2008). To progress further, then, we need to understand more about what resilience - as system property - is.

We noted above the limitations of much of the literature dealing with resilience. But there is a fraction of more conceptual literature of relevance here that recognises resilience as a systemic property. Some of that literature, particularly early work, sought to treat resilience as a monolithic property but more recent work has broken it down into a set of sub-properties. A review of these latter sources suggests that resilience sub-properties can be grouped in two main categories, according to their foundational or enabling contribution to resilience.

Foundational Sub-Properties of Resilience

Analysis and synthesis of the conceptual resilience-as-property literature (Carpenter et al. 2001, Walker et al. 2004, Folke 2006, Nelson et al. 2007, Plummer & Armitage 2007, Resilience Alliance 2010, Miller et al. 2010, Osbahr et al. 2010) suggests that resilient systems have three core characteristics, referred to here as 'foundational sub-properties'.

The first of these sub-properties - robustness - relates mainly to the ability of the system to withstand; that is, to maintain its characteristics and performance in the face of environmental fluctuations, including shocks (developed from Carlson & Doyle 2002, Janssen & Anderies 2007, Tierney & Bruneau 2007). Generic features of robust systems include reinforcing connections between components and processes, which help spread the effects of any external disturbance, and strengthening individual structures (such as institutions) to avoid their collapse in the face of stressors (Gunderson 2000). For example, in relation to climate change such strengthening would encompass physical preparations such as levees, flood storage basins, greenspaces and tree planting (Gill et al. 2007).

The second foundational sub-property is self-organisation, which refers to the system's ability to independently re-arrange its functions and processes in the face of external disturbances, without being forced by the influence of other external drivers (Carpenter et al. 2001). Self-organisation is critical given both the uncertainty of reliance on external systems e.g. during a disaster, and the potential mismatch between external and local system interests. It enables local diagnosis of problems and mobilisation of resources to initiate solutions (Tierney & Bruneau 2007), and relies strongly on the capacity for cooperative decision-making and action within the community; a capacity that will be based significantly on the nature of social networks within the community (Fuchs 2004). The capacity for local collective action will also relate to the nature of local power over structures and resources (such as leadership within the community and representativeness and trust) and psycho-social dimensions (e.g. belief, motivation, hope, perceived self-efficacy) within the community (Brouwer et al. 2007).

The third foundational sub-property of resilience is learning: the capacity of the system to generate feedback with which to gain or create knowledge, and build the skills, attitudes and other competences required to innovate and adapt to change. Experimentation, discovery and innovation can all be seen as aspects of both short-term response to shocks and longer-term transformational change (Folke et al. 2010). These may be enhanced by the combination of local knowledge with that sourced from outside the community (Folke et al. 2003).

Enabling Sub-Properties of Resilience

Further review of conceptual literature suggests the existence of an additional set of sub-properties - redundancy, rapidity, scale, diversity, flexibility, and equality - that enable resilience, and that facilitate the operationalisation of the foundational attributes described above (Godschalk 2003, Folke et al. 2003, Seixas & Berkes 2003, Tompkins & Adger 2004, ADPC 2006, Marshall & Marshall 2007, Callaghan & Colton 2008, Magis 2009, Cuthill et al. 2010).

Redundancy is the extent to which components within a system are substitutable; for example, in the event of disruption or degradation. One part of this can be asset diversity, but this is not simply an issue of scale but the ability to access assets that are both in some sense 'surplus' and interchangeable. Redundancy may also involve the overlap of processes, capacities and response pathways that allow for partial failure within a system without complete collapse (Rockefeller Foundation 2009).

Rapidity means how quickly assets can be accessed or mobilised to achieve goals in an efficient manner (Norris et al. 2008), and is key to ensuring the system's ability to identify the emergence of problems and decide and implement a course of action in a timely manner. This will have a particular value in responding to acute disturbances such as disasters and will relate to a variety of assets but especially information and finance.

Scale refers to the breadth of assets and structures a system can access in order to effectively overcome or bounce back from or adapt to the effects of disturbances (Folke et al. 2010). It involves, for example, access to structures beyond the immediate community level which enable access to resources that may not otherwise be available. These structures may be informal social networks or formal institutions such as extended markets or state organisations, which are shown to be important in responding to external stressors (Few et al. 2006).

Diversityis the availability of a variety of assets, institutions and institutional functions that enable a range of response options (e.g. in terms of livelihoods, land use, adaptive infrastructure choices, etc) (Folke et al. 2005, Hopkins 2009). It also encompasses diversity of knowledge and reference frames (Galaz et al. 2008). This reduces the potential fragility of a 'monoculture' response to external stressors, helping the absorption of disturbance, spreading of risk, and stimulus of competitive reorganisation and renewal (Folke et al. 2003, Nelson et al. 2007, Rockefeller Foundation 2009, Ifejika Speranza 2010, Clements et al. 2010). Diversity of system elements also "provides the basis for innovation, learning and adaptation to slower, ongoing change" (Biggs et al. 2012: 425).

Closely linked to diversity and combined into a single sub-property for the purposes of what follows, flexibility refers to the ability of a system to undertake different sets of actions with the determinants at its disposal, better enabling it to address problems and utilise opportunities arising from external change (Folke 2006). Flexibility partly relates to the ability of system elements to be recombined in different ways, but also to the existence of knowledge (e.g. from wider networks) that can suggest those different combinations and courses of action; and to an adaptability of decision-making processes to allow alternatives to be considered.

Equality is the extent to which the system affords equal access to rights, resources and opportunities to its members, given evidence that more unequal systems are less resilient and less able to adapt (Adger 2001, Magis 2009). At one level, this is about the distribution of access to resources and institutions, but it is also about the nature of decision-making: whether this is able to produce shared goals by being participative and transparent (Tompkins & Adger 2004).

Conceptualising Community Resilience

Based on the review above, we can now summarise resilience as a series of foundational and enabling sub-properties with definitions and key markers as shown in Table 1 (Ospina 2013).

Table 1: Community Resilience Sub-Properties: Summary of Definitions and Key Markers (Ospina 2013)

These resilience sub-properties constitute dynamic, interrelated, and imbricated attributes that interact with available assets, institutions, structures and capabilities (system components) in a livelihood system, and ultimately enable adaptation as realised functionings (system processes). The realised adaptations contribute to the achievement of development outcomes, including feedback into the capacity of the system to withstand or adapt to future disturbances and uncertainties. These connections form the resilience model that is reflected in Figure 2.

Figure 2: Communities as Adaptive Systems: Resilience as a System Property (adapted from Ospina & Heeks 2010)

To summarise, the analysis of systemic adaptation is concerned with the relationships between components, properties, processes and outcomes in a given system (Nelson et al. 2007), as reflected in Figure 2. Here, external shocks or trends within a particular context act as a stimulus that requires a response. The capacity of the system - in this case a community - to respond through adaptation can be understood in two ways. First, as a set of structuro-functional components. Second, as a set of (sub-)properties. Together these interact to create the adaptive capacity of the system/community, which can be thought of as the system's capabilities - what it is able to be and to do - in making a response to acute or chronic external stressors. Therefore, resilience interacts with assets and other components to shape the trajectory of functioning and adaptation (Norris et al. 2008).

Having laid out the conceptual basis for community resilience, we will now use this framework to analyse the relationship to resilience within the context of community informatics.


This section takes the resilience framework and uses it as a lens for the analysis of urban community informatics; mainly drawing evidence from literature on specific projects or interventions. There are two ways this could be approached. Either, as here, analysing each of the sub-properties in turn to understand ways in which community informatics has affected them. Or, one could analyse community informatics interventions one-by-one to understand the specific impact they have had on community resilience: this will be the subject of future work (Ospina & Heeks 2014). Given space constraints, we acknowledge that what is achieved here can only be illustrative rather than comprehensive. As noted previously, our particular interest will be low-income urban communities given that they represent the intersection of a pressing need for greater resilience and a recently-grown availability of ICTs. However, the relatively limited evidence base means we will, at times, have to move beyond this boundary.

ICTs Strengthening Foundational Sub-Properties

ICTs and Robustness

ICTs can help strengthen the physical preparedness of communities by helping those communities optimise the location of physical defences. For example, in a number of cities, geographic information systems (GIS) have been used to plot flood plains and watercourses, enabling the improved planning of maintenance and installation of storm drains (Kluck et al. 2010). ICTs can also strengthen institutions needed for the system to withstand the occurrence of external shocks. This can occur by developing the capacity of individual institutions: for example of local government to deliver services or to make good decisions (Schuppan 2009). But it can also occur by drawing institutions together into networks and partnerships that expand urban governance capacity, creating so-called 'smart city' or 'e-city' governance models (Paskaleva 2009), or by placing local institutions as one actor within multi-level networks that are global in scale (Sun et al. 2010).

ICTs and Self-Organisation

Self-organisation of urban communities requires that they have internal, independent capacity to take decisions and actions, something conceivable in terms of the information chain (see Figure 3).

Figure 3: The Information Chain (adapted from Heeks & Kanashiro 2009)

A first step will be provision of appropriate data and information for decision-making processes. ICTs of course have a key role here. Most often, digital information about, say, climate events or climate change will come from outside the community (Ospina 2011, World Bank 2012). This does not per se install external drivers that may divert and undermine self-organisation, but of greater fit with self-organisation will be ICT use to generate data within communities themselves; an option which is increasing with greater availability of mobile phones. These have been used to report on-the-ground data during urban disasters or in relation to WaSH (water, sanitation, and hygiene) services, though as with all ICT systems there is still a reliance on external sources for hardware, software and telecommunications (Hutchings et al. 2012, World Bank 2012).

Digital tools such as public participatory GIS (in some cases with linked decision support systems) are increasingly used to help communities make decisions (Bugs 2012, Wallin & Horelli 2012). This support for self-organisation via ICTs increases dramatically if we extend the scope of 'self' to also cover local government. Although lagging behind the extent of use in the global North, use of ICTs in local governments in Latin America, Africa and Asia is expanding fast, and assisting with data gathering, processing and decision making of relevance to climate and other-related shocks (e.g. Revi et al. 2006, World Bank 2012).

The 'action' component of the information chain is less associated with ICTs but the capacity for all elements of the chain - creating information, making decisions, taking actions - can be impacted by new technology. Some of these capacities, such as learning or general provision of resources, will be discussed in relation to other sub-properties. However, Table 1 specifically identifies social networks, leadership and trust.

ICTs can be seen to foster robustness by supporting social relations and social networks that reach outside the urban community; for example links to relatives based in rural areas (Skuse & Cousins 2008, Morawczynski 2009). But mobile phones also strengthen the social networks within urban communities, enhancing their ability to self-organise responses to external disturbances within those communities. They do this by enhancing communication within these networks, and thus building trust and social capital within the individual bonds of the network (Duncombe 2006). Experience in urban communities of using other ICTs such as online discussion forums has been more mixed, but there are signs that it can increase the density of contact within these communities and enable forms of self-organisation that spill over from the virtual to the real world (Kotus & Hlawka 2010). As might be expected, ICTs have been highly effective in strengthening the capacities of community leaders (e.g. Ogbu & Mihyo 2000, Ben-Attar & Campbell 2013).

ICTs and Learning

The increasing mediation of learning via ICTs means that, necessarily, communities will increasingly be building their base of information, skills and knowledge through digital technologies (Bishop et al. 2006, Garrison 2011). The opportunities for learning are expanding as more online educational resources of relevance are developing (e.g. Wilson et al. 2011), though it will be some time before these filter down to engage low-income community members in developing countries.

More accessible have been digital tools such as Web 2.0/social media applications to support processes of collective learning, particularly among institutions working in or with low-income urban communities (GTZ 2008). This can be understood in terms of Kolb's (1984) learning cycle: the sharing of experiences such as changes in the urban environment, group reflection on this evidence, the development of understanding through conceptualisation, and then the translation of these frames into active experimentation within the local area. This has been seen, for example, in the intensive use of ICTs in the Learning and Action Alliances that have supported reflection and built collective knowledge around urban flood risk management (Manojlovic et al. 2013).

ICTs Strengthening Enabling Sub-Properties

ICTs and Redundancy

Redundancy refers to the potential of ICTs to increase availability of resources to such an extent that there is some spare, excess or possible substitutability of assets. One key way in which ICTs can contribute to redundancy is by supporting access to additional financial capital. ICTs - mobile phones especially - have been associated with an outflow of financial remittances from urban to rural areas, but they also enable inflows from richer urban and overseas diaspora social contacts into low-income urban communities (Skuse & Cousins 2008, Bowora & Chazovachii 2010). Although difficult to characterise this as creating 'spare' income, it does move communities in the direction of redundancy in terms of both financial capital and other assets purchased with the money. ICTs - e.g. mobile systems - also offer a channel for income flows that substitute for income that can no longer be produced locally during periods of acute shock, for example reversing standard urban-to-rural flows (Morawczynski & Pickens 2009)

Just as asset redundancy can improve the resilience of urban communities, so does redundancy in institutions and organisations (e.g. markets), which allows a community to continue to operate even in the event of partial failure of some of its components. One example is the broadening of urban job market channels through use of ICTs such as the Babajob system for informal sector employment in India (Heeks 2010a). This has functional overlaps with existing informal networks, thus providing a substitutable, redundant channel for job market operation. Another example is m-commerce - such as the CellBazaar system in Bangladesh - which provides redundancy in retail channels for urban communities, creating substitutable trading links (Zainudeen et al. 2011).

ICTs and Rapidity

A core functionality of ICTs is the increasing speed with which they process and communicate data. They are thus strongly associated with increases in systemic rapidity within urban communities for all information flows, transactions and services that they handle. For example, ICTs enable greater rapidity of access to, and mobilisation of, financial assets via m-finance applications (Duncombe & Boateng 2009). This, in turn, enables greater rapidity of mobilisation of the assets and services purchased with this money.

Similarly, by speeding up the accessibility of data, ICTs speed up the whole information chain (see Figure 3). So, for instance, mobile-based disaster management systems enable more rapid disaster early warning, response and recovery including coordinative decisions and actions (Yap 2011).

ICTs and Scale

By connecting low-income urban communities to distant and/or higher-level institutions, ICTs can improve the scale of assets and structures to which these communities have access. Telemedicine and related applications can provide access to the information, knowledge and other capabilities of the wider health system (Blaya et al. 2010, Gomez & Passerini 2010). Urban weather forecasting and early warning systems similarly provide connections to wider capitals (informational, human, social, etc) and systems (Shaw 2012). ICTs can also improve the breadth of access to economic structures: tapping poor urban producers into wider markets (see the CellBazaar example mentioned above), or into regional and global supply chains (Munoz & Choi 2010). Most directly, this can improve scale of access to financial assets. As well as linking urban communities to "higher-level" systems, ICTs can also assist by enabling community organisations and enterprises to scale, and by facilitating cross-community interactions and partnerships (Schaffers et al. 2011)

ICTs, Diversity and Flexibility

ICTs typically provide a supplement rather than substitute for pre-existing sub-systems of data processing, communication, transactions and services. As such, they necessarily increase the diversity of any system such as an urban community. But they also significantly increase the potential for diversity of decision-making and action within the community, because they increase the diversity of information flows into the decision-making process (Shachaf 2008, Hampton et al. 2011). This would include providing information on a more diverse range of actions than might otherwise be known, in part through the more diverse social connections that ICTs enable; as already described.

Initial generations of ICTs were associated with inflexibility and the idea that they set procedures and systems in "electronic concrete" (Heeks 1999). However, more recent ICTs are much more flexible - not only incorporating an ever-wider range of functionalities but also more-readily enabling users to themselves re-purpose the technology. This means that ICTs can facilitate greater flexibility within social and economic development components of urban communities (Forcheri & Molfino 2000, Ritchie & Brindley 2005). They can also form the foundation for new, collaborative forms of urban innovation, particularly social innovations (Deakin & Allwinkle 2007).

ICTs and Equality

The 21st century's "mobile revolution" has brought almost all members of low-income urban communities within reach of digital communications, with the majority of the population owning a mobile and with access to mobile telephony being close to ubiquitous (Ling & Horst 2011, Wesolowski et al. 2012). This has been a significant equaliser and its impact on equality will continue to expand as an increasing range of services becomes available via mobile phone. Alongside examples already cited around use of m-money, this extends to the development of skills via m-learning (e.g. Zolfo et al. 2010) and to the political sphere.

The spread of ICTs has seen improvements in access to government services provided online via PC and mobile (Scholl 2010), but the impact of ICTs has gone beyond this to foster greater inclusion in political processes. For example, in Uganda, mobile phones and social media (e.g. Facebook and Twitter) have been widely used for campaigning and civil activism that can draw low-income groups into political activity (CIPESA 2012). ICTs can also open up governance in other ways: improving "transparency and accountability in the delivery of social services" (World Bank 2004: 5) by allowing urban citizens to monitor public processes, and supporting the participation of citizens in urban planning decisions, for example through use of PPGIS (public participation geographic information systems) (Bugs et al. 2010). In this way, ICTs help level the playing field of political power, shifting power somewhat from traditional institutions to the community.

ICTs Weakening Resilience

It is, therefore, possible to identify many ways in which ICTs are strengthening resilience in urban areas. However, the ever-greater penetration of ICTs into the lives of low-income urban communities should not be read simply as positive in resilience terms, since ICTs may also weaken resilience sub-properties. We give two brief illustrations here.

ICTs form a global digital infrastructure which encourages and enables local communities to become part of global digital networks in economic, political, social and cultural spheres. As noted above, this strengthens robustness and scale and it is not necessarily at odds with self-organisation . . . but it can be if local capacities and systems atrophy in the face of external connections; where, for example, ICTs support global supply chains at the expense of local ones (Audirac 2005). This can create a dependency on wider connectivity that can undermine the ability to organise and act locally and independently.

All new technologies are almost inherently levers of inequality because of their uneven patterns of adoption and use: in other words those with initially higher resource endowments are in a position to make faster, better use of new technologies thus increasing the endowment gap in relation to those with initially lower endowments (Heeks & Kenny 2002). The picture with ICTs is not simple, with gaps closing over time: e.g. in terms of gender inequalities in access to ICTs (Brannstrom 2012). But gaps evolve - from a divide of access to an emerging gap of skills for effective use, and from a divide of older generation to an emerging gap of newer generation technologies (Heeks 2010b, van Deursen & van Dijk 2010). Thus ICTs are simultaneously strengthening and weakening aspects of equality.


Resilience is key to the future of urban communities and is particularly important for low-income communities that are most vulnerable to future shocks. If they are not resilient, they will increasingly fail in the face of the growth in external stressors, not least the expanding impact of climate change. Because this is widely-recognised, there has been ongoing interest in urban resilience for many years. Resilience-targeting actions have also been on the rise but both interest and actions are likely to have been held back by a conceptualisation of resilience to date that has simultaneously been too broad and too shallow. Debate has fragmented around multiple definitions, and has stuttered due to the lack of an all-embracing framework. In this paper, we have developed a fairly clear but also comprehensive framework for understanding resilience as a system property, with an urban community being one such system.

We have then shown how this resilience framework could be used to analyse community informatics. In this case we undertook an aggregated and cross-cutting evaluation of evidence from a variety of community informatics cases and projects, providing an overall sense of the impact on resilience. It was seen that ICTs can both increase and decrease community resilience and the framework thus helps understand both the pros and cons of community informatics. Of course there have been limitations given that this has been a post-hoc reinterpretation of evidence based on a relatively few cases. There is a consequential need for further work applying the model in greater depth and durante hoc. We hope, though, that this paper does provide at least a proof of concept for the resilience model as an analytical framework for community informatics; showing how ICTs can be linked to the rising resilience agenda.

There remains, though, the "so what?" question: the more difficult issue of what new, additional insights a resilience perspective on community informatics offers compared to others. The main value would appear to be the transcendent nature of resilience: whereas other lenses for understanding CI - gender, skills, economic regeneration, civic participation - are always partial, resilience offers a lens that is at the same time both fundamental and over-arching.

By investigating properties, a resilience approach to community informatics ensures that ICTs are understood in relation to foundations; to the core of what communities require in order to survive and prosper in the 21st century. So the - not yet fully-proven - potential of resilience is that it includes important aspects that other approaches may miss, and that it is better at targeting more important issues and priorities. It refocuses our attention on community informatics from the short-term to the long-term, and adds both breadth and depth to our planning, implementation and evaluation.

More evidence about that potential can emerge from conceptual work, undertaking further analysis with the model. But it may be more likely to arise from its application to practice, something which - as discussed next - will also require further work.

Developments for Practice

The resilience framework could be used in practice to evaluate community informatics projects pre-, durante- and post-hoc; not merely helping to understand them but also prompting revisions that will deepen the formation of community resilience. Further developments would be needed for this to be possible, including moving from general markers of each resilience sub-property, to specific indicators which could be measured either using rating scales or more objectively.

Urban resilience indexes of this type do already exist - for example the Disaster Resilience Index (Cutter et al. 2010) or the Resilience Capacity Index (BRR 2013) relying on conventional measures largely available within the public domain. However, these have only been applied to US cities. These indices touch on some aspects of some of the resilience sub-properties such as the human and institutional capacity markers of robustness and learning, the gap marker of equality, and perhaps some element of scale; however, the major part of resilience is left untouched as the focus is largely on components and functions rather than properties. UN-HABITAT's City Resilience Profiling Programme is under way at the time of writing and seeks to bring metrics to bear on the issue of urban resilience. Details of the underlying urban systems model are relatively sketchy but again it relates to components and functions of city systems, not to properties (Lewis 2013).

There thus remains a space to create a true resilience index which recognises resilience as a property of urban communities viewed as systems. Appendix A gives an example of an initial move in this direction, though clearly requiring further work which at the time of writing was being undertaken via piloting of RABIT - the Resilience Assessment Benchmarking and Impact Toolkit - to evaluate the impact on resilience of ICTs in low-income urban communities in Costa Rica (Ospina & Heeks 2014). Rather than attempting some form of cross-community benchmarking, this will use the framework on a community-specific basis, getting community representatives to discuss the connection of ICTs to the resilience sub-properties and their meaning, relevance, priority, etc. for their particular community. We hope this will prove a fruitful way forward in seeking to deepen the connection between community informatics and community resilience.


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Appendix A: Sample Survey Sheet for Assessing Impact of Community Informatics on Resilience


The Journal of Community Informatics. ISSN: 1712-4441