Session Contribution Rest List
A contribution rest export view for sessions.
GET /programme/20/export/?format=api
[
{
"title": "Advancements in Digital Twins of the Ocean to Increase Coastal Resilience",
"url": "/submissions/119",
"abstract": "<p>\n Technology is revolutionizing our approach to environmental challenges. Among the most promising tools of digitalization is the Digital Twin (DT), or more specifically the Digital Twin of the Ocean (DTO). This is a virtual replica of the ocean that holds immense potential for sustainable marine development. In order to successfully confront the increasing impacts and hazards of a changing climate (such as coastal erosion and flooding), it is vital to further develop the DTO in order to be able to monitor, predict, and protect vulnerable coastal communities. DTOs are powered by AI-enhanced data that integrates ocean conditions, ecosystems, and anthropogenic influences, along with novel AI-driven predictive modeling capabilities, combining wave, hydrodynamic, and morphodynamic models. This enables unprecedented accuracy in seamless forecasting capabilities. In addition to natural phenomena, DTOs can also include socio-economic factors (e.g. ocean-use, pollution). Thus, DTOs can be used to monitor the current ocean state, but also to simulate future ‘What-if’ Scenarios (WiS) for various human interventions. In this way the DTO can guide decisions for protecting the coast and sustainable use of marine resources, while also promoting collaboration on effective solutions for ocean conservation.\n</p>\n<p>\n In European projects such as the European Digital Twin Ocean (EDITO) ModelLab, work is ongoing to utilize the DTO to simulate various WiS that are co-designed with stakeholders. These include assessing the impacts of sea level rise, evaluating the success of various mitigation and adaptation strategies, such as Nature-Based Solutions (NBS). With the use of NBS, decision-makers from a variety of groups can be more informed about using vegetation to reduce erosion risk and wave heights on the coast, to reduces the cost of coastal protection. Another EDITO WiS addresses the development of commercially viable and sustainable offshore low-trophic aquaculture (LTA) in wind or fish farms, enhancing the sustainable blue economy. Working with a DTO to address such scenarios can provide better information for decision-making and highlight regions of the real ocean in need of special attention.\n</p>\n<p>\n These efforts also align with global initiatives like the EU Mission: Restore our Ocean and Waters, and Green Deal projects (e.g., Rest-COAST). Other relevant international initiatives include the COSS-TT (Coastal Ocean and Shelf Seas Task Team under OceanPredict) and UN Decade programmes (such as CoastPredict, and the Decadal Collaborative Center on Coastal Resilience (DCC-CR), and DITTO). The UN Ocean Decade DITTO Program in particular aims to establish and advance a digital framework for marine data, modeling and simulations, and advanced tools such as AI capabilities, to empower users to create their own workflows for utilizing DTOs, improving interoperability and ease of access to increase worldwide scientific collaboration.\n</p>\n<p>\n The DTO has the potential to play a significant role in advancing the sustainable development of the marine environment. DT-based What-If Scenarios foster cooperation among stakeholders in shared oceanic spaces, enabling data-driven decisions and collaborations. The DTO platform enables decision-making and management strategies for the sustainable utilization of ocean resources, which builds resilient communities and empowers decision makers, educators, researchers, and the general public in a changing world\n</p>\n",
"presentation_type": "Keynote",
"session": "Digital Twins",
"start": "2025-09-04T10:45:00+02:00",
"duration": "00:30:00",
"authors": [
{
"author": {
"first_name": "Joanna",
"last_name": "Staneva",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": true
},
{
"author": {
"first_name": "Kelli",
"last_name": "Johnson",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
},
{
"author": {
"first_name": "Benjamin",
"last_name": "Jacob",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
},
{
"author": {
"first_name": "Wei",
"last_name": "Chen",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
},
{
"author": {
"first_name": "Johannes",
"last_name": "Pein",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
}
],
"submitter": "Philipp Sebastian Sommer",
"event": "Data Science Symposium 2025",
"activity": null,
"accepted": true,
"license": "Creative Commons Attribution 4.0 International (CC-BY-4.0)",
"affiliations": [
"Helmholtz-Zentrum Hereon"
]
},
{
"title": "Toward a digital twin of the coastal sea: Progress in the Wadden Sea",
"url": "/submissions/69",
"abstract": "<p>\n Digital twins of the ocean (DTO) make marine data available to support the development of the blue economy and enable a direct interaction through bi-directional components. Typical DTOs provide insufficient detail near the coast, because their resolution is too coarse and the underlying models lack processes that become relevant in shallow areas, e.g., at wetting and drying of tidal flats. As roughly 2.13 Billion of the world’s population live near a coast, downscaling ocean information to a local scale becomes necessary, as many practical applications, e.g., sediment management, require high resolution data. For this reason, we focused on the appropriate downscaling of regional and global data from existing DTOs using a high-resolution (100s of meters), unstructured, three-dimensional, process-based hindcast model in combination with in-situ observations. This high-resolution model allows the fine tidal channels, estuaries, and coastal structures like dams and flood barriers to be represented digitally. Our digital twin includes tidal dynamics, salinity, sea water temperature, waves, and suspended sediment transport. Thanks to a fast and intuitive web interface of our prototype digital twin, the model data provided enable a wide range of coastal applications and support sustainable management. Bi-directional web processing services (WPS) were implemented within the interactive web-viewer and include ecological habitat calculator, sediment management, cable route planning and marine renewable energy. Our next steps focus on extending the digital twin closer to being operational and on exploring the ability to predict the short-term future system behavior.\n</p>\n",
"presentation_type": "Talk",
"session": "Digital Twins",
"start": "2025-09-04T11:15:00+02:00",
"duration": "00:15:00",
"authors": [
{
"author": {
"first_name": "Robert",
"last_name": "Lepper",
"orcid": "0000-0002-8446-2004"
},
"affiliation": [
"Bundesanstalt für Wasserbau"
],
"is_presenter": true
},
{
"author": {
"first_name": "Markus",
"last_name": "Reinert",
"orcid": "0000-0002-3761-8029"
},
"affiliation": [
"Bundesanstalt für Wasserbau"
],
"is_presenter": false
}
],
"submitter": "Robert Lepper",
"event": "Data Science Symposium 2025",
"activity": "AK Portal & Viewer Technologies (Viewer)",
"accepted": true,
"license": "Creative Commons Attribution 4.0 International (CC-BY-4.0)",
"affiliations": [
"Bundesanstalt für Wasserbau"
]
},
{
"title": "Design an interactive decision-support platform for offshore renewable energy managements",
"url": "/submissions/76",
"abstract": "<p>\n The rapid growth of offshore wind energy requires effective decision-support tools to optimize operations and manage risks. To address this, we developed iSeaPower, a web-based platform designed to support decision-making in offshore renewable energy tasks through real-time data analysis and interactive visualizations. iSeaPower integrates detailed meteorological and oceanographic data with advanced statistical methods, machine learning forecasts, and data assimilation techniques. This integration enables accurate predictions of weather windows, thorough risk assessments, and efficient operational planning for offshore wind energy stakeholders. iSeaPower is designed to optimize journey planning by considering weather conditions and travel duration. The current framework includes five methods tailored to different operational requirements. First, the forecasting method evaluates wind speed and wave height risks over short-term windows (1–3 days) using real-time weather data to quickly identify potential hazards. Second, historical database analysis calculates exceedance probabilities based on 30-day intervals from long-term historical data, revealing recurring weather risk patterns. Third, the delay time estimation method determines potential task delays across the entire year by analyzing monthly weather trends, supporting long-term operational planning and risk management. Fourth, machine learning approaches enhance the accuracy of seven-day forecasts by combining historical data with machine learning, improving short-term predictions. Finally, the updated statistics method with Monte Carlo simulation uses historical weather distributions and a forecasting operation system to provide probabilistic assessments of risks over 14-day periods. The framework produces detailed reports outlining exceedance probabilities, optimal travel windows, and clearly categorized risk levels to support informed decision-making.\n</p>\n",
"presentation_type": "Talk",
"session": "Digital Twins",
"start": "2025-09-04T11:30:00+02:00",
"duration": "00:15:00",
"authors": [
{
"author": {
"first_name": "Naseem",
"last_name": "Ali",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": true
},
{
"author": {
"first_name": "Beate",
"last_name": "Geyer",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
},
{
"author": {
"first_name": "Johannes",
"last_name": "Schulz-Stellenfleth",
"orcid": null
},
"affiliation": [
"Helmholtz-Zentrum Hereon"
],
"is_presenter": false
}
],
"submitter": "Naseem Ali",
"event": "Data Science Symposium 2025",
"activity": null,
"accepted": true,
"license": "Creative Commons Attribution 4.0 International (CC-BY-4.0)",
"affiliations": [
"Helmholtz-Zentrum Hereon"
]
}
]