03Mar '17

Deliverable 7.3 ADEQUATe Dissemination Plan

Dissemination Plan including target Groups and planned dissemination activities for the ADEQUATe project as well as measureable criteria for success.

01Jul '16

Deliverable 1.1 - Catalogue of quality dimensions and concrete metrics to assess (meta-)data quality

This document summarizes the set of metrics and algorithms to be implemented on the ADEQUATe platform. It is the result of the State-of-the-Art elicitation in deliverable 1.3, the crosscutting with user requirements of D1.2, and the goals of the project according to the Description of Work (DoW).

01Jul '16

Deliverable 1.2 - Requirements Specification

This report provides the results of the conducted focus group interviews, together with an online-based survey regarding current issues of data quality on open data portals in Austria. The report explains the structure and methodology behind both activities, along with an analysis, discussion, and summary of the combined outcomes. Based on these findings, together with the desk research results from the State-of-the-Art analysis in Deliverable D1.3, a set of suitable actions, metrics, and technology components for the requirements catalog in D.1.1 can be formulated. 

01Jul '16

Deliverable 1.3 - State-of-the-Art Analysis of Open Data Quality Assessment Metrics and Algorithms

This report summarizes the current state of the art (2016) on data quality by analysing research papers and projects. Details on data quality dimensions and metrics are given and implementation specifics regarding the assessment of these metrics are discussed. The report distinguishes DQ metrics which are specific for data portals, and metrics with a more general DQ assessment aspiration. Metrics are further divided into such which target the data portal or process level, and those which are relevant to the actual data itself. For the latter, we differentiate between subjective and objective metrics. Special attention is paid to those metrics which are relevant in a linked data context, and to those which are suitable to automatically assess and/or improve data quality.