Data & Analytics

Data & Analytics play a vital role in the realization of the Sustainable Development Goals (SDGs). SDG 17 (Partnerships for the Goals) specifically emphasizes the need to enhance the availability of high-quality, timely, and reliable data. Accurate data and insightful analytics are essential for assessing progress, identifying gaps, making informed decisions, and creating effective policies related to each of the SDGs. For instance, they can help enhance education systems (SDG 4), optimize health services (SDG 3), reduce poverty (SDG 1), and mitigate climate change impacts (SDG 13). Moreover, advances in data collection methods, including mobile technology and remote sensing, can provide valuable insights for achieving sustainability. Therefore, robust data and analytics are integral to monitoring and accomplishing the SDGs.

This paper develops a coupling between SWAN and Thetis models to account for wave–current interactions occurring by the co-existence of wave and current flows. The different grids and time-steps employed by the model components allow greater flexibility. The two models run consecutively, and communicate internally to exchange the necessary parameters. These are the significant wave height, mean wave direction, mean wavelength and percentage of wave-breaking calculated by SWAN necessary for calculating radiation stress and wave roller effects, while Thetis provides water elevation and current velocity fields.
The article highlights the Indigenous approaches to conflict resolution vary considerably from society to society.
The gender pay gap has declined slightly, although the majority of organisations continue to have a gap in favour of males. This article explores a number of statistics covering pay and bonus gaps, with details of broad sector and industry, and relates to SDG 5, Gender Equality.
Monitoring the ocean carbon cycle is key to improved understanding. Satellites play a major role in our global carbon monitoring system. To make full use of satellite observations for ocean carbon monitoring the remote-sensing community needs to work closely with in-situ data experts, physical and biogeochemical modellers, Earth system scientists, climate scientists and marine policy experts.
AI, employers, economic forecast
With AI-driven labor market transformations being affected by economic troubles and other factors, this article explores the strategies leaders are using to help workers navigate these changes. Specifically, leaders are stepping up investing in at least four strategies to prepare workers for the prevailing disruption and empower them to successfully navigate the change while ensuring healthy work cultures and compelling work opportunities for all.
This study proposes a deep learning model based on a convolutional neural network, which can effectively fuse atmospheric information (wind field) and station water level information and can effectively forecast the station water level and also have a good response to the anomalous water level increase brought by storm surge.
The survey presented here was conducted to better understand public perceptions of climate change, human impacts and the value and management of marine and coastal ecosystems.
This article analyses the practice of indigenous conflict resolution mechanisms in building a culture of peace in Ethiopia.
This paper synthesized current knowledge of mesoscale eddies and their impacts on the marine ecosystem across the North Pacific and its marginal Seas, across the CCS region , the northeastern North Pacific and the Bering Sea, the western boundary of the North Pacific and marginal seas, and the extratropical open North Pacific. How climate change will modify mesoscale processes remains a key open challenge.
This paper show the mathematical and theoretical background of the machine learning algorithm used in this work, the LSTM. The data used are described and the methodology of framework is presented. It shows the predictions results based on LSTM and comparisons with ERA5 and buoy observations.