Socialising Big Data in terms of missing metrics #SBDGenomics

This post is a general reflection on the concerns of working with big data that follows from our first collaboratory on genomics held at the Wellcome Trust Sanger Institute in Cambridge this week (see Evelyn’s previous blog for further details).

In discussing the opportunities, risks and challenges of working with big data, like Evelyn, I was surprised at the similarities experienced across disciplines. The key metrics required in genomics on a daily basis, to work effectively and to communicate with others, raised the same issues of data quality, quantity, representation, and consistency.

Participants also spoke of familiar experiences of working with new data processing tools for analysis, and the ways in which big data is changing the relationship between academia and the commercial sector. To be sure, there are new opportunities associated with processing big data in real-time, but these possibilities also arrive with risks and challenges in terms of data management, privacy and trust.

One issue that struck me from the discussion was how the problem of accessibility was framed in terms of the public good. In our discussions about accessibility – namely, who should have access to data and why? – I was reminded of the difference between public access and managed access.

This difference was made salient when situated in the context of disease, namely how to make sense of DNA variants as a cause of disease. As one participant pointed out, “While you can quantify genomic data, you can’t measure the impact of gene analysis on families.” At stake here is not simply a question of methodology, it concerns ethics and people’s right to know. Crucially, it involves taking into consideration that which can’t be measured and thinking more seriously about missing metrics.

So while there remains a lack of consensus regarding methodology, which makes evaluation difficult, there are also shared attempts to socialise big data and to recognise the epistemological and ontological effects that our practices have on individuals and society more generally.


2 thoughts on “Socialising Big Data in terms of missing metrics #SBDGenomics

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s