A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain

Abstract

The paper presents a proposal for a framework for the identification, assessment and selection of open data sources based on certain quality criteria, such as accessibility, relevance, accuracy & reliability, clarity, timeliness & punctuality, and coherence & comparability. The framework concerns mainly open data sources and focuses on their quality. The open data are used to enhance existing internal data and to fuse them with data from other sources. The framework consists of few steps starting from definition of quality criteria based on review of relevant literature and user requirements, then identification of potential sources, sources assessment and selection, and finally data retrieval process. For each step, a specific approach is described, how it may be conducted in practice. The proposed framework is evaluated using a real use case scenario from the maritime domain. The main approach utilized in this use-case is the Delphi method with some characteristics of Analytic Hierarchy Process.

Big Data for Anomaly Detection in Maritime Surveillance: Spatial AIS Data Analysis for Tankers

“…Therefore, appropriate methods were developed to alleviate these quality issues. The process of internet sources selection and data fusion was described in detail in separate papers ( [35] and [19] respectively). As a result a vast amount of ancillary data for all types of vessels was acquired, such as tonnage, dimensions, detailed type, built year, builder, home port, data about detentions and inspections of ships as well as data about classification statuses of ships and their affiliation to a classification society.…”

Multilingual Ranking of Wikipedia Articles with Quality and Popularity Assessment in Different Topics

“…DBpedia is the semantic database resulting from the extraction of structured, multilingual knowledge from Wikipedia [18,19]. The data from this open databases are widely used in a number of domains: web search, life sciences, maritime domain, art market, digital libraries, business networks, and others [20][21][22][23].…”

Multilingual Ranking of Wikipedia Articles with Quality and Popularity Assessment in Different Topics

“…DBpedia is the semantic database resulting from extraction of structured, multilingual knowledge from Wikipedia [18,19]. The data from this open databases are widely used in a number of domains: web search, life sciences, maritime domain, art market, digital libraries, business networks and others [20][21][22][23].…”