Encouraging a corporate open data culture


The Royal Society’s influential paper on the use and misuse of risk analysis asserts that “[a]ny corporation, public utility or government will react to criticism of its activities by seeking…new ways to further the acceptable image of their activities” (Pearce, Russell & Griffiths, 1981). In the past decade the timely availability of relevant data has become widely acknowledged as having “a huge potential benefit” to the practice of risk assessment and management (Hughes, Murray, & Royse, 2012). Partly in response to climate change concerns the importance of access to data is acknowledged at a local, national and international level. To enable and encourage the wider use of public environmental and health related data, initiatives like the European Union’s INSPIRE Directive are establishing standardised, legally enforceable data infrastructures (European Union, 2014), and many governments have adopted ‘open data’ strategies (e.g. UK Government, 2014; Google, 2011).

While the benefits of open data has been recognised and is being acted on in the public realm, despite the good intentions of some corporations (Ghafele & O’Brien, 2012, Alder, 2014) most commercial organisations have been slow to respond. The principle barriers to data sharing in the corporate sector have been identified as resulting from concerns over intellectual property, commercial confidentiality, and ‘cultural’ issues. While not offering any actionable recommendations to tackle these issues, the UK Government’s recent ‘Foresight’ Review asserts that “a more holistic approach to risk analysis…is undoubtedly needed” (Hughes et al, 2012).

Risk analysis and management of uncertainty demand an interdisciplinary approach (Rougier et al., 2010: 4) and the purpose of this essay is to follow this course and explore the social science disciplines of Anthropology and Economics in order to propose a combined approach that includes relevant methods from both fields. While the evolution of these disciplines has followed different trajectories, and underlying methodological differences can be identified, the increasingly blurred boundaries within science ensure that the identification of discrete ontologies is problematic. The move towards transdisciplinarity involving as it does the sharing of research tools and theoretical perspectives, and the emergence of new multidisciplinary fields (e.g. economic anthropology) provides a fertile field for developing ‘Mode 2’ research propositions (Nowotny, 2001).

Specifically, this essay explores the factors influencing data sharing in the hydrocarbon exploration industry (HEI) where potential exists for the timely publication of data gathered from monitoring hydraulic fracturing activity.


Hydraulic fracturing, more widely known as ‘fracking’, is a technique that has been used to release and collect methane gas from shale rock for more than 60 years. The fracking process employs explosive charges and specially formulated chemical fluids pumped under high pressure to help release gas for extraction. This process takes place more than 1,500m below ground level, at a significantly greater depth than typical coal mining activities (Mair et al, 2012; Wood, 2012). The British Geological Survey estimate that “resources of 1,800 to 13,000bcm [billion cubic metres]”, the equivalent of more than 23 years supply at current UK consumption rates, are “potentially recoverable” from sites in northern and southern England (POSTbox, 2013). However exploration is required in order to discover if this potential is realisable.

Public concerns about fracking focus on the possibility of increased seismic activity, leakage of chemical contaminants into the water table, air pollution caused by the leakage of methane, and the continuing reliance on carbon resources with potentially harmful effects on the world’s climate (Mair, et al, 2012; Kibble et al, 2013; Ricketts, 2013). These concerns have been expressed in public demonstrations against the process (The Guardian, 2013), and the introduction of moratoria on exploration in a number of countries. These public expressions of concern are viewed by the HEI as a significant additional risk to an already hazardous enterprise (Wood, 2012).

In the UK, all industrial activities are subject to health and safety audits and some involve continuous, around the clock monitoring. For example in the HEI, Cuadrilla Resources commission Ground Gas Solutions Ltd. to provide monitoring services (Cuadrilla, 2013) which aim to: “…provide confidence to regulators, local communities and interested third parties that no environmental damage has occurred.” (GGS Ltd., 2013). Some of this data are made public via reports to regulatory authorities which can be subject to significant delay, are written in formal, technical language, and are not easily accessed by the general public (Boholm, 2003: 172). This essay proposes a interdisciplinary research methodology to explore the potential for allowing open access to real time (or close to real time) monitoring data that could help to alleviate some public concerns.


Whether analysing large scale issues of national or global significance (macroeconomics) or focussing on the actions of individuals and local groups (microeconomics), the study of economics is defined by its evaluation of human behaviour in relation to the exploitation and control of scarce resources. In all disciplines there are varieties of opinion on the efficacies of different theories; in economics this can be illustrated by reference to the divergent theories regarding government intervention in markets advocated by Keynesian economists and those following the Chicago School. In practice economists prioritise their research by balancing the availability of data and the effectiveness of its collection against the needs of their audience (e.g. government agencies and corporations) and the strength of their beliefs in the determining factors that influence the behaviour of individuals in society (Kuznets, 1978). For example, when seeking solutions to economic depression a Keynesian may advocate increased government spending, whereas a Chicago School economist would suggest increased money supply, allowing a free market to correct itself.

Key concepts in economics include the evaluation of the cost and benefits of future economic activity and the maximisation of utility. Predicting the outcomes of activities with varying levels of uncertainty involve the collection of relevant data, risk analysis and the evaluation of statistical probability. In high-risk investment industries the effective collection and analysis of data is vital, not least in hydrocarbon exploration, where the large rewards for discovering untapped, scarce resources are balanced by the huge investments involved in exploration. The assessment of risk plays a significant part in evaluating the potential costs and economic value of recoverable hydrocarbon resources and multidisciplinary teams comprising geologists, statisticians, legal experts, engineers and economists are engaged within the HEI to ensure that rational choices are made, resources are used to their full potential and that risk is kept ‘as low as reasonably practical” (HSE, 2014). A range of complex and exhaustive appraisal models are used in evaluation, the core aims being to use data as efficiently as possible and minimise subjectivity in order to reduce uncertainty when ascertaining the economic risks and rewards (Nederlof, 2014).

The evaluation process can be broken down into three key stages:

  • Resource evaluation. This is normally undertaken using a “petroleum system model” and is based on the assumption of five independent geological processes that facilitate hydrocarbon accumulation: generation, migration, entrapment and retention and recovery (Häntschel & Kauerauf, 2009). Data for each of these processes are collected using a range of tools (e.g. Geographic Information Systems software) (Hood et al, 2000).
  • Monte Carlo statistical analysis. This uses computer-based statistical analysis tools (e.g. Palisade Corporation, 2014) to process input variables many thousands of times using different random choices to create vectors of equally probable outcomes. A typical output from this process is a range of expectation curves which display the predicted outcomes in ascending order of probability (Nederlof, 2014).
  • Economic appraisal. Essentially this involves translating the predicted amount of recoverable resources into a cash value. Considerations of the value of the resource need to account of inflation, predicted future prices, regulation, safety, health and environmental considerations and exploitation contracts and licences. All of these factors are subject to variations over time (e.g. possibility of a future ‘windfall tax’) and economists typically provide a number of alternative scenarios indicating the probabilities arising from the interplay of different variables (Haldorsen, 1996).

While the statistical analysis of this detailed mesh of quantitative data is a powerful tool in helping decision makers in the HEI, economists understand that care must be taken in reaching definitive conclusions and in making predictions. A key concern is that primary data may be treated without a suitable understanding the historical background, conventions and collection practices that influence the production of this data (Fogel, Fogel, Guglielmo & Grotte, 2013: 96). An appreciation of the contribution of anthropological research may be helpful is this area.


Although anthropologists “cast their net far and wide” (Eriksen, 2004: 45) in order to provide context for their observations, their work is undertaken primarily through close interaction with individuals and the groups they inhabit. In-depth, structured interviews are used extensively and the key research method is ‘participant observation’ – the goal being to extensively record everyday experiences as an aid to gaining new knowledge on the existence (or otherwise) of ‘human universals’ (shared characteristics).

Developing from the study of ‘exotic’ cultures in the 19th and early 20th century, it is perhaps inevitable that with a field as large as the scientific study of humanity at all times and in all places would branch into a heterogeneous collection of sub-disciplines – ‘urban anthropology’,  ‘design anthropology’, ‘theological anthropology’, ‘digital anthropology’, and so on.  Although there probably is an ‘anthropology’ for every area of human activity, each with its own unique ontology, the features that distinguishes this social science from other, similar, disciplines (e.g. sociology) resides primarily in its approach to data collection and interpretation. Unlike researchers in most other disciplines, anthropologists immerse themselves within the social and cultural life of their subjects, living closely ‘in the field’ with the people they are studying. The purpose is to attempt to see the world from the subjects’ point of view, and to provide a rich, contextualised, ‘thick’ description and localised interpretation of this perspective (Geertz, 1994: 140).

Data collection follows a systematic approach which typically focuses on particular fields of study, primarily: kinship, reciprocity, nature, thought and identification. For example an anthropologist may explore how the community they are researching view reciprocity; how gifts are exchanged, goods are paid for, and how the community view property, as well those things that cannot be exchanged or given away (Weiner, (1992: 33). Comparisons can then be made between groups with a view to establishing and understanding similarities and differences, and ultimately identifying characteristics which are unique to specific societies and those that are universally shared (Goodenough, 1970).

Within the terms of this essay,  perhaps the most appropriate sub-discipline to explore in some detail is where anthropologists are commissioned by commercial organisations to describe and analyse ‘organisational culture’ – what is typically referred to as ‘organisational anthropology’. Anthropologists working in the commercial sector are usually engaged in ‘problem-oriented’ research, attempting to uncover the root of human relations issues identified by corporate leaders (Catlin, 2006). Within this environment they apply anthropological methodologies to particular fields of interest, for example: work processes, group behaviour, organisational change, consumer behaviour, product design and the effects of globalisation and diversity (Jordan, 2010). The focus of this research is placed on talking with employees and management to reach descriptions and interpretations of the overall culture as well as any existing sub-cultures, with the aim of providing recommended courses of action that are relevant to the organisations’ strategic goals.

In addition to work in the corporate sector the anthropologists’ practice of long-term engagement is also useful to public policymakers where collected data can be extremely useful in tracking changes in over extended periods of time (Perry, 2013). Within the HEI, anthropologists explore the relationships between companies, state organisations and communities (Stammler & Wilson, 2006), the cultural implications of the regulation of risk (Kringen, 2008), the environmental impact on communities and their resilience to exploration (Buultjens 2013),  as well as land use and the social organisation of the workforce (Godoy, 1985).

Finally, Monte Carlo analysis is not simply the preserve of economic analysts. The method is used in other social sciences including social anthropology (Tate, 2013), linguistics (Klein, Kuppin & Meives, 1969), education (Pudrovska & Anishkin, 2013) and public health studies (Morera & Castro, 2013) and applied to statistical analysis when evaluating and predicting incomplete or missing data.

Proposal for an interdisciplinary approach

This essay has explored the relevant theories and research themes that influence those involved in economic decisions in the HEI and how anthropology approaches the study of cultures. A key element in the context of this essay is the evaluation of risk: how does the HEI balance risk and reward in the search for scarce, economically recoverable resources, and what can anthropology offer in understanding the human perception of risk. Central to the risk question, both evaluation and perception, is how data is used to aid economic decision making on the part of corporations, and to enable society to compare potential hazards and manage health and safety, and environmental concerns.

When experts analyse risk in the HEI, the terms they use to define the costs and benefits of a particular course of action are highly relevant to decision makers, but may have little meaning to “people in social settings” (Boholm, 2003: 166). While the maximisation of utility through rational choices motivates the statistical analysis of potential hydrocarbon fields, from the anthropology perspective this approach fundamentally misrepresents the essentially cultural construction of risk perception (Bourdieu, 2005: 215) and has “limited relevance for explaining how people think and act in situations where there is an element of uncertainty” (Boholm, 2003: 161).

Although generally useful, there are two essential problems with this approach. Firstly, anthropologists are divided on the concept of ‘culture’. In its plural form it can be seen as divisive and not conducive identifying human universals, definitions of ‘culture’ are often vague and do not acknowledge the permeability of boundaries in human society, or the possibilities for internal variation (Hannerz, 1992: 13). Secondly, when explaining ideas of risk and hazard, anthropology tends to favour definitions based on objective social phenomenon (e.g ‘taboo’ in traditional societies is viewed as a means of maintaining social order – Tansey and O’Riordan 1999: 74) rather than an individuals’ subjective consideration of risks based on available evidence (Slovic, 1987: 280). However, by taking care when making generalised statements regarding ‘culture’ and by exploring how people “identify, understand and manage uncertainty in terms of knowledge of consequences and probabilities of events” (Boholm, 2003: 166) – and by acknowledging the relevance of expert risk analysis, a consensus definition of risk can be expressed as: “a situation or event where something of human value (including humans themselves) has been put at stake and where the outcome is uncertain” (Rosa 1998: 28).

Managing risks at both a corporate and community level entails the timely communication of relevant data in a form that can be readily understood by all parties. In the current setting economic analysis can provide some highly relevant expert insight into risk in the HEI, and anthropological research can describe and interpret the context of the perception and consideration of risk and uncertainty.

In essence this combined approach would involve primary anthropological research methods including in-depth structured interviews, and participant observation within the HEI and affected communities. The outputs of these studies would be used to inform a more nuanced approach to uncertainty and risk in economic modelling and the use of computational methods (including Monte Carlo analysis) to predict the effects of social vulnerability and environmental protest activity on hydrocarbon exploration. By adopting this form of research methodology it is proposed that an effective approach to communicating risk can be formulated which may encourage a more transparent publication of data and help the HEI “to further the acceptable image of their activities” (Pearce, et al., 1981).


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