Q1: Is your organisation based in Sweden and/or work with Swedish data? (collection, ingestion, processing, analysis, usage, output)
        Yes. 
        No. 

Q2: What is the size of your company / institution / organization?
        Micro (<5 employees)
        Small (<50 employees)
        Medium (<250 employees)
        Large (>250 employees)

Q3: Which group most accurately describes your organisation?
        Industry
        Government (including local, regional, and national)
        Academia
        Research institute
        Independent (including NGOs)

Q4: What best describes the general data maturity of your organisation?
        Novice: Limited data practices and minimal data-driven decision-making.
        Beginner: Initial data initiatives are underway, but not fully integrated into business processes.
        Intermediate: Some advanced data practices, with data-driven decision-making becoming more common.
        Advanced: Well-established data practices, with a high degree of integration into business processes.
        Expert: Leading-edge data practices, with a strong culture of data-driven decision-making.

Q5: To what extent is does your organisation work with ocean data?
	Not al all
        Rarely
	Occasionally
        Frequently
        Extensively

Q6: Which of the following best describes the typical ocean environment (distance from shore, Sweden or outside of Sweden) of the ocean data which your organization work with? 
        Coastal (inside baseline of any country, green line on map shows Sweden's baseline)
        Nearshore (territorial water of any country, gray line on map shows Sweden's teritorial water, 12 nm from the baseline)
        Near offshore (Exclusive Economic Zone of any country, blue line on map shows Sweden's EEZ, up to 200 nm outside of territorial water)
        Open ocean (not in any country's Exclusive Economic Zone)
        Swedish water
        Non-Swedish water
	Annat

Q7: Which role best describes you in relation to ocean data in your organisation?
        Data user
        Data collector
        Data scientist
        Data engineer
	Dava viewer
        Data enthusiast
        Annat

Q8: Approximately how many years of experience with data in general do you have (in both current and previous positions)?
        less than 3 years
        3 - 8 years
        8 - 15 years
        more than 15 years

Q9: Approximately how many years of experience with ocean data do you have (in both current and previous positions)?
        less than 3 years
        3 - 8 years
        8 - 15 years
        more than 15 years

Q10: Select the programming languages you consider yourself proficient in: (Select all that apply)
        No programming experience
        MATLAB
	Python
        R
        Java
        JavaScript
        C++
	C#
	Julia
	Swift
	Annat

Q11: Does your organisation collect ocean data?
        Yes. 
        No, but we have collected data in the past. 
        No, we have never collected data. 

Q12: To what extent does your organistaion rely on collecting its own ocean data versus using external providers?
        We collect our own ocean data exclusively.
        We mostly collect our own ocean data but also use external providers.
        We equally rely on collecting our own ocean data and using external providers.
        We mostly rely on external providers but also collect some ocean data internally.
        We exclusively rely on external providers for our ocean data.

Q13: What typically describes the frequency of the ocean data collection of your organisation?
        Never
        Daily
        Weekly
        Monthly
        Quarterly
        Annually
	Streaming (continuous or real-time)
        Irregular/Ad hoc

Q14: How sensitive (e.g., in terms of national security, GDPR) is the ocean data your organisation collects?
        Not sensitive
        Low sensitivity
        Moderate sensitivity
        High sensitivity
        Very high sensitivity

Q15: What is the main type of ocean data your organisation collects?
        Images / Video (e.g. from ROV or drop cameras)
        Time-series data (e.g. sensors)
        Raster data (e.g. GIS mapping)
        Satellite data
        Annat

Q16: How much ocean data is collected by your organisation per year? (roughly)
        1-10GB
        10GB-100GB
        100GB-1TB
        More than 1TB
	More than 1PB
        Don't know
        Annat

Q17: When looking for ocean data externally, which are your preferred data providers? (Select all that apply)
        SND (Swedish National Data Service)
        EMODnet
        SMHI / SHARK / SHARKweb
        Copernicus
        Ifremer
        SwAM / HaV
        Annat

Q18: Which of the following processing activities does your organization typically perform on collected ocean data? (Select all that apply)
        Data cleaning and preprocessing
        Aggregation and summarization
        Statistical analysis
        Machine learning and predictive modeling
        Other (please specify)
        None of the above

Q19: Where is your ocean data typically stored?
        External hard drives or local devices
        On-premise servers
        Cloud storage services
        Database systems
        Data warehouses
        Distributed file systems
	Annat

Q20: Which data format do you typically use when analysing ocean data?
        JSON
        CSV / XLS (Excel)
        JPG / PNG / SVG (Image)
        MP4 / MOV / AVI (Movies)
        GEOTIFF / SHP (GIS formats)
        NetCDF
        Proprietary format
        Annat

Q21: Which of the following is most commonly used for ocean data analysis in your organisation? (Select all that apply)
        MATLAB
        Python (e.g., NumPy, Pandas)
        R
        ArcGIS
        QGIS
        Tableau
        Excel
        Proprietary software
        None of the above
        Annat

Q22: Has your organisation used machine learning / AI techniques when dealing with ocean data?
        Not at all
        Very little
        Somewhat
        Quite a bit
	Extensively
        Don't know

Q23: What are the main goals when analysing ocean data inside your organisation? (Select all that apply)
        Surveying
        Identifying trends and patterns
        Species / environmental monitoring
        Compliance and regulatory reporting
        Informing decision-making / planning
        Predictive modeling and forecasting
        Annat

Q24: What do you see as the potential use case(s) for AI in your organisation's ocean data applications based on its current needs?
        Data Quality Control
        Automated Data Analysis
        Autonomous Data Collection
        Marine Species Identification
        Climate Change Impact Assessment
        Predictive Modeling
        Enhanced Decision Support
        Real-time Monitoring
        Integration with Other Technologies

Q25: What is the main target audience for your data?
        Internal stakeholders (e.g., management, employees)
        External stakeholders (e.g., customers, clients, partners)
        Regulatory bodies and compliance agencies
        Research and academic institutions
        General public
        Annat

Q26: Does your organization publish any of the ocean data it collects?
        We regularly publish a wide range of data (at least once a year)
        We infrequently publish data
        We publish specific datasets on request
        We do not publish data at all
        Annat

Q27: Does your organization offer an easy way to share its ocean data?
        Yes, by a well-established API for data sharing. 
        Yes, by a dedicated infrastructure for data sharing via services, such as file transfer. 
        No, but access can be granted by request, e.g. via e-mail. 
        No, we do not have any way of granting access to our data. 
        Annat

Q28: Which of the following best describe the typical data outputs from your organisation? (Select all that apply)
        Reports and Dashboards
        Visualizations
        Predictions and Forecasts
        Alerts and Notifications
        Recommendations
        Processed Data Sets
        Automation Outputs
	Consumer Segmentation
        Time-Series Data
        Geospatial Data Outputs
        Compliance and Regulatory Reports
        Processed Images or Videos
        Simulations and Scenarios
        Financial Metrics
	Engagement Metrics

Q29: Which ocean data tasks are the most time-consuming in your organisation?
        Data collection
        Data cleaning
        Data processing
        Data analysis
	Data ingestion
        Data publishing

Q30: What are the biggest challenges facing your organisation when dealing with ocean data? (Select all that apply)
        Regulation
        Lack of data
        Data integration
        Scaling issues
        Lack of standardization

Q31: What are the main challenges you experience when looking for ocean data? (Select all that apply)
        Data Accessibility
        Data Silos / Fragmentation
        Spatial / Temporal Resolution
        Data Quality
        Lack of metadata / standardization
        Limited coverage of region of interest
        Data Security / Privacy
        Data Cost
        Data Interoperability
        Annat

Q32: Which of the following are currently affecting your organisation / field most in relation to ocean data? (Select all that apply)
        Advancements in data analytics and artificial intelligence
        Regulatory changes impacting data privacy and security
        Emerging technologies and data collection methods
        Increased competition and changing market dynamics
        Evolving customer expectations and demands
        The amount/size of data and the many sources.
        Cybersecurity threats and data breaches
        Integration of big data and Internet of Things (IoT)
        Changes in data governance and compliance standards
        Annat
