Addressing challenges for knowledge discovery from data in the domain of seaport integration

Ana Ximena Halabi Echeverry, Deborah Richards

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)


Discovering knowledge from data for decision making is dependent on the existence of data relevant to the decision at hand. For decisions in domains that involve many different factors and concerns, such as seaport integration, data may exist across many repositories managed by different organizations with different goals and foci, not to mention different data structures, entities, labels, units of measurement, categories and time periods. To use this data for decision making, approaches to combine the data and handle missing values are two of the problems, among others, that need to be addressed. In this paper we discuss the need for managing micro and macro-level data and our approach to handle missing values.
Original languageEnglish
Title of host publicationKnowledge management and acquisition for intelligent systems
Subtitle of host publication12th Pacific Rim Knowledge Acquisition Workshop, PKAW 2012, Kuching, Malaysia, September 5-6 2012 : proceedings
EditorsDeborah Richards, Byeong Ho Kang
Place of PublicationHeidelberg, Germany
PublisherSpringer, Springer Nature
Number of pages13
ISBN (Print)9783642325403
Publication statusPublished - 2012
EventPacific Rim Knowledge Acquisition Workshop (12th : 2012) - Kuching, Malaysia
Duration: 5 Sept 20126 Sept 2012

Publication series

NameLecture notes in computer science
ISSN (Print)0302-9743


WorkshopPacific Rim Knowledge Acquisition Workshop (12th : 2012)
CityKuching, Malaysia


  • Seaport Integration
  • Data Aggregation
  • Missing Values


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