Promoting High-Quality Data in OBIS: Insights from the OBIS Data Quality Assessment and Enhancement Project Team

The Ocean Biodiversity Information System (OBIS) (Klein et al. 2019) is a global database of marine biodiversity and associated environmental data, which provides critical information to researchers and policymakers worldwide. Ensuring the accuracy and consistency of the data in OBIS is essential for its usefulness and value, not only to the scientific community but also to the science-policy interface. The OBIS Data Quality Assessment and Enhancement Project Team (QCPT), formed in 2019 by the OBIS steering group, aims to assess and enhance data quality. It has been working on three categories of activities for this purpose: Data quality enhancement and management The OBIS QCPT organized data laundry events to identify and address data quality issues of published OBIS datasets. Furthermore, individual OBIS nodes were invited to give their data-processing presentations in the monthly meetings to foster knowledge sharing and collaborative problem-solving focused on data quality. Data quality issues and solutions highlighted in the presentations and data laundry events were documented in a dedicated GitHub repository as GitHub issues. The solutions for data quality issues and marine-specific pre-publication quality control tools, designed to identify the data quality issues, were provided as feedback to the OBIS Capacity Development Task Team. These inputs were used to create training resources (see OBIS manual, upcoming OBIS training course hosted on OceanTeacher Global Academy) aimed at preventing these issues. Standardization of OBIS data processing pipeline As OBIS uses the Darwin Core standard (Wieczorek et al. 2012), the use of standardized tests and assertions in the data processing pipeline is encouraged. To achieve this, the OBIS QCPT aligned OBIS quality checks with a subset of core tests and assertions (Chapman et al. 2020) developed by the Biodiversity Information Standards (TDWG) Biodiversity Data Quality (BDQ) Task Group 2 (TG2) (Chapman et al. 2020) as tracked in this GitHub issue. Not all default parameters of the core tests and assertions are optimal for marine biodiversity data. The OBIS QCPT met monthly to determine suitable parameters for customizing the tests. The pipeline produces a data quality report for each dataset with quality flags that indicate potential data quality issues, enabling node managers and data providers to review the flagged records. Community engagement The OBIS QCPT led a survey among data users to gather insights i