As the amount of linked data increases, so too does the diversity of data. While standards, procedures, and classification schemes are fundamental to sharing across organisational and institutional boundaries, a CIS needs more to support collaboration. It needs to afford negotiation between the various stakeholders’ goals, interests and concerns, and to support the identification of the key overarching goals of the collaboration. As such, the CIS needs to provide a flexible, ever changing, yet self-evident standard of classification and meta-data to accommodate for the increase in data without abstracting and erasing the diversity.
What goals do you have that others might not share? What goals are interrelated?
How are goals, interests, concerns communicated?
How can the CIS help clarify shared or divergent interests and concerns?
How can the CIS support collaboration amongst actors with competing goals?
How can the CIS encourage the articulation/translation of these goals?
How can these articulations be tied to data as it is gathered for, and used within, the CIS?
As the amount of linked data increases, so too does the diversity of data. Stakeholders often find it difficult to make sense of the various data coming their way, since they do not have the same focus in their engagements with the information as those who entered it into the system. This is because CISs put into conversation information gathered using several different methods and put together information that is intended to achieve different goals by the various actors involved.
While standards, procedures, and classification schemes are fundamental to sharing across organisational and institutional boundaries, a CIS needs more to support collaboration. To be useful, CISs need to afford negotiation between the various stakeholders’ goals, interests and concerns. Specifically, participants should be supported in taking one user’s specific way of knowing risks or incidents and translating it to be understood by fellow users with different backgrounds and experiences. Furthermore, CISs should support the identification of the key overarching goals of the system itself, as well as of the governing bodies, organisations, and individual users of the system. In other words, a CIS needs to provide a flexible, ever changing, yet self-evident standard of classification and meta-data to accommodate for the increase in data without abstracting and erasing the diversity.
In a study entitled ‘Understanding Complex Information Environments’, Van House, Butler, and Schiff (1998) explore the working patterns around information sharing and collaboration in relation to California watershed planning. There the authors examine how these ideas might play out in a watershed planning CIS which they describe as “distributed physically in time and space, and logically in terms of control; and with no omniscient agents organizing the work” (p. 336). During their study, the authors observed the engagements of a range of stakeholders, from government agencies, resource-based industries such as agriculture and timber, environmentally-based industries such as recreation, landowners and non-government environmental groups, and community groups. The planning took place at state, regional and local levels, often with the need to manage competing interests while the goal for these interactions in relation to watershed planning were for these stakeholders to come to as much of a shared understanding of the current state of their watershed regions as possible. From this they hoped to produce a common set of expectations from future actions and agreements for overarching goals.
However, Van House et al. found that the shared information was not just used for decision-making but equally “for defending points of view and persuading and educating others” (1998, p. 337), hence illustrating the qualities of information as a ‘boundary object’ (i.e. information that can be used in different ways by different communities). In doing so, the different stakeholders used different data and privileged different uses of the data.
- Fear of losing the legitimacy of their communities of practice that would limit their authoritative voice.
- Fear of the use of their data in unintended ways because the data were disassociated from their site of production and thus made to mean new things without consideration for the specifics from which they derive.
- Using descriptive meta-data that aimed made it possible to calibrate measurements, terminology and data elements across the range of information provided within the CIS.
- Using established mapping or reporting structures supported stakeholders in knowing they were appropriately combining different data from different sources. Van House et al. do note that, “whether such detail can be sufficiently specified is, however, debatable” (p. 340)
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