A Scalable Framework for Dynamic Data Citation of Arbitrary Structured Data

Abstract

Sharing research data is becoming increasingly important as it enables peers to validate and reproduce data driven experiments. Also exchanging data allows scientists to reuse data in different contexts and gather new knowledge from available sources. But with increasing volume of data, researchers need to reference exact versions of datasets. Until now access to research data often based on single archives of data files where versioning and subsetting support is limited. In this paper we introduce a mechanism that allows researchers to create versioned subsets of research data which can be cited and shared in a lightweight manner. We demonstrate a prototype that supports researchers in creating subsets based on filtering and sorting source data. These subsets can be cited for later reference and reuse. The system produces evidence that allows users to verify the correctness and completeness of a subset based on cryptographic hashing. We describe a replication scenario for enabling scalable data citation in dynamic contexts.

Reproducible Database Queries in Privacy Sensitive Applications

“…For storing the queries with their execution metadata, the concept of the query store was developed by Proell and Rauber (2014). The goal of the query store is to attach persistent identifiers to query results and allow retrieving the same data again by re-executing a query against historical data.…”

A Practical Workflow for an Open Scientific Lifecycle Project: EcoNAOS

“…The monitoring of rules applications on these pilot projects will lead to rules improvement and adaptation based on specific and generic requirements. A framework for citing evolving data, by quantification of the changes in the database as long as new data are added, is formulated in [31,32]. Citation of aggregated data has been also afforded by Baker, Amsi and Uytvanck [33].…”

Peer Review #3 of "Decentralized provenance-aware publishing with nanopublications (v0.2)"

“…There exist furthermore a number of approaches to applying peer-to-peer networks for RDF data (Filali et al, 2011), but they do not allow for the kind of permanent and provenance-aware publishing that we propose below. Moreover, only for the centralized and closed-world setting of database systems, approaches exist that allow for robust and granular references to subsets of dynamic datasets (Proell and Rauber, 2014).…”