Mark Parsons (NSIDC) and Peter Fox (RPI) EGU 2012, GI 1.3 April 23, 2012, Vienna, Austria Exploring Metaphors for making Data Available.

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Presentation transcript:

Mark Parsons (NSIDC) and Peter Fox (RPI) EGU 2012, GI 1.3 April 23, 2012, Vienna, Austria Exploring Metaphors for making Data Available

ICSU SCCID recommendation content/uploads/2011/04/open_access.jpg g/Open_Access/Open_Access_Cloud_WEB.jpg

ICSU SCCID recommendation OECD guidelines = data access and sharing policies

ICSU SCCID recommendation Engage actively –publishers of all kinds together –library community –scientific researchers To –Document and promote community best practice in the handling of supplemental material, publication of data and appropriate data citation. dia/2010/03/reed-elsevier-logo240cs jpg shed%20Pics/Scientists.jpg

Goal? Data as a first class object Metaphors indicate a particular stakeholder perspective

Technical advances From: C. Borgman, 2008, NSF Cyberlearning Report

7 DataInformationKnowledge ProducersConsumers Context Presentation Organization Integration Conversation Creation Gathering Experience Ecosystem Stimulate Innovation Research Exploration

Data perspective 8 ProducersConsumers Quality Control Fitness for Purpose Fitness for Use Quality Assessment Trustee Trustor

Is this separation good or not? 9 ProducersConsumers Quality Control Fitness for Purpose Fitness for Use Quality Assessment Trustee Trustor

Multiple approaches - generic Organizations Data Centres Publishers Release (e.g. like software) Linked data … (am not going to cover them all)

An un-named US govt. agency

Pros/Cons - Data Centres (‘big iron’) Volume Streamlined Automation Auditable Reprocessing capability Central authority Funded Over-reliance on automation Weak documentation Use is assumed Roles ill-defined, reputation? Does not handle heterogeneity Preservation ? Overly focused on generation …

Pros/Cons - Publishers Simple Tested Disseminated Shifted burden Imprimatur De-facto preservation Citable Based on science norms Locked Static/ Not machine accessible Cost? Not scalable Cannot verify use

Pros/Cons - Release (software) Many stages (alpha, beta, release candidate, release) Versioned Documented and change notified Intends to couple user feedback to developers Packaged Licensing well thought out … Provenance implicit Preservation poorly dealt with Quality may be difficult to determine Attribution not part of the mind- set Derivative or embedded use not always well defined …

Pros/Cons - Linked data Scales Built on web Simple model design Tested Disseminated Machine processable No central authority Heterogeneous Use not assumed Flexible evolution Supports encapsulation Poor versioning Poor auditing No imprimatur No preservation/ stewardship Not human friendly Heterogeneous vocab. Changes data model Unknown evolution …

Setting of the roles and relations Yes it is about contracts… of all sorts… –But that’s a longer story.

Attributes in search of metaphors A new paradigm of Archive, Release, and Mediate that disaggregates the functions? Rapid, carefully versioned and described releases (like software)? Open software/web: Simple, Weak (least power), Scalable, Open? Active mediation between producers and consumers (like specialist shop keepers – a new role)?

Call to discussion Multiple metaphors, many considerations An ecosystem approach allows multiple solutions in a socio-technical system Significant opportunities for under-served data generators to get their data ‘out there’ perhaps publication (still a metaphor!) Consequences – it will be annoying for a while.. Role(s) for professional societies, e.g. statements on data Thanks for your attention - Watch for our Data Science Journal essay on this topic