Data Quality Control 

Data Quality Control is a very important issue in the procedure of data collection and during the BlackSeaScene I project the topic has had a lot of attention. In Upgrade BlackSeaScene this effort will be even more extended, actual data quality assessments and flagging will be made to the datasets of the partners.

In BlackSeaScene I efforts have resulted in two products: A searchable inventory of the DQC procedures and a statistical tool to filter datasets for outliers.

  1. Under NA3 an inventory of Data Quality Control (DQC) and Data Quality Assessment (DQA) methods within the Black Sea countries has been made.
    This inventory formed the basis for a Data Quality Assessment on BSS partners data activities, which is followed by the introduction of current EU DQC and DQA methods and procedures. Partners will assess the quality of their data by systematic sampling and benchmarking, fillinf out a DQC form for their datasets (collected in EDMED), resulting in a sort of Data Quality Label.
    The created DQC inventory provides an overview of the DQC procedures per coutry and is related to the EDMED description of the datasets. The DQC form allows users to estimate the present quality of Black Sea datasets, managed by the regional partners.
    Please visit and search the inventory.
  2. The team from TU-Varna (BG) developed program- and web-based procedures for data quality analysis. Collected data is subjected to statistical procedures in order to study how disturbances in the measurement process influence the quality of information. Outliers are identified that are not representative for the analyzed object/process.

During the Upgrade BlackSeaScene project the methods directory will be extended and products will be updated.