Modelling Data Value in Digital Preservation

For decades, the Earth Science (ES) community has launched missions to monitor vital phenomena of our planet and, through measurements, obtain data for improving their models. Indeed the proper characterisation of phenomena, such as desertification, Arctic sea ice melting, volcanic activities or earthquakes effects, requires the analysis of data acquired in a long period and the validation of correctness of scientific models. This means that digital data, especially in the ES domain, represents an important asset to be preserved over time. Despite each single ES mission’s cost being quantified and supported by well documented evidence, ES organisations are not able to assess the value of data generated by those missions over time. This paper describes the rationale for and an approach to modelling the value of data/information to be preserved over long term in digital archive. This is the result of experience in the SCIDIP-ES project [16] which has considered the: i) definition of models for describing the value of digital data and related information; ii) characterisation of data/information value model through core set of key parameters and iii) identification of long term digital preservation activities that may potentially impact on key parameters and consequently on the value of digital assets. This model is being assessed in ES scenarios with data curators and archive managers.