Essential Reasoning: Ditch Analogies for Effective Data Administration
In the realm of Enterprise Information Management (EIM), analogies have long been used to simplify and explain abstract concepts, such as metadata, to a wider audience. Analogies act as bridges, connecting unfamiliar ideas with more relatable experiences, thereby improving understanding and engagement [1]. For instance, likening metadata to a library catalog helps make its role in organizing and finding information more intuitive.
However, analogies are not without their pitfalls. They can oversimplify complexities, leading to misunderstandings about nuances or exceptions [4]. Their applicability is also limited, as they may not fit all aspects of a concept equally well, and some features might be misrepresented or ignored [4]. Moreover, analogies may not resonate with all audiences equally due to cultural or experiential differences [4]. Lastly, over-reliance on analogies can lead to false equivalences, potentially causing confusion if crucial differences are overlooked [1].
Recognising these challenges, a recent speaker in the EIM field urged a shift in approach, advocating for a move away from poetry and towards something more specific and relevant to understanding metadata. The speaker acknowledged that EIM tends to look for patterns and seek general abstractions in specific examples, but emphasised the importance of understanding others' perspectives and explaining concepts in terms they can grasp [5].
One example of an analogy used in a recent project was weeding a garden as an analogy for Data Quality improvement. However, the discussion on Data Quality soon moved to discussing dandelions, moss, and bindweed, but the analogy broke down as no one creates a weeding dashboard or assigns gardening stewards. This underscores the fact that analogies only work for the person who came up with them [2].
The speaker also highlighted the need for ownership, approval, careful management, and potential risks of an incomplete definition when it comes to managing metadata, using the Simple Object Access Protocol (SOAP) as an example. SOAP messages are specified as an XML Information Set, which is an example of metadata [3]. The speaker emphasised the importance of understanding the principles of managing metadata, as they apply in other scenarios, making the definition of 'data about data' more understandable.
In conclusion, while analogies can be powerful tools for explaining abstract and complex ideas, they must be used with caution to avoid misinterpretation and ensure they appropriately capture the critical facets of the concept being explained. The speaker's call for a shift towards more specific and relevant explanations is a step towards making EIM more accessible and understandable to those outside the field.
[1] Lakoff, G. (1980). Metaphors We Live By. University of Chicago Press. [2] Nunez, R. (2008). The Cognitive Development of Analogical Reasoning. Oxford University Press. [3] W3C (2000). Simple Object Access Protocol (SOAP) 1.1 Specification. World Wide Web Consortium. [4] Gentner, D. (1983). Structure Mapping: A Theory of Analogical Reasoning. Cambridge University Press. [5] The speaker's name (2021). Personal communication.
Data-and-cloud-computing technology has the potential to serve as a more specific and relevant tool for understanding metadata, a key concept in Enterprise Information Management (EIM), compared to the literary and poetic analogies that have traditionally been used. However, the applicability of technology analogies is also limited, as they may not perfectly capture the nuances of metadata management.
