Data Management and Preservation Planning for Big Science

Data Management and Preservation Planning for Big Science

‘Big Science’ that is, science which involves large collaborations with dedicated facilities, and involving large data volumes and multinational investments – is often seen as different when it comes to data management and preservation planning. Big Science handles its data differently from other disciplines and has data management problems that are qualitatively different from other discipline...

DMP Planning for Big Science Projects

This report exists to provide high-level guidance for the strategic and engineering development of Data Management & Preservation (DMP) plans for ‘Big Science’ data. Although the report’s nominal audience is therefore rather narrow, we intend the document to be of use to other planners and data architects who wish to implement good practice in this area. For the purposes of this report, we pres...

Big Data Science Needs Big Data Middleware

There has been a “Cambrian explosion” of big data systems proposed and evaluated in the last eight years, but relatively little understanding of how these systems or the ideas they represent compare and complement one another. In enterprise and science situations, “one size is unlikely to fit all”: we see analytics teams running multiple systems simultaneously. However, the highest level of abs...

Big Data, Data Science, and Civil Rights

Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how colleges and universities make admissions and financial aid decisions, and much ...

Data science, big data and granular mining