Data Quality in Life Cycle Assessment

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Related lectures (32)

Page 1 of 4

Representativeness, Reliability, and Contribution

Discusses data quality evaluation, reliability, representativeness, and process contribution in Life Cycle Assessment.

Analytics on Data at Rest and Data in Motion

Explores combining data at rest with data in motion, emphasizing the Lambda architecture complexities and quality assessment of streams and batches.

Big Data: Challenges and Implications

Explores the challenges and implications of Big Data, emphasizing the importance of data quality and ethical considerations.

Data Warehousing: Overview and Challenges

Introduces data warehousing fundamentals, challenges, and the innovative concept of a 'lakehouse'.

Data Handling: Problems and Distributions

Covers common data problems and important distributions, along with correlation and dependencies analysis.

Hedonic Pricing Method: Housing and Environmental Goods

Covers the Hedonic Pricing Method for assessing implicit prices of goods and introduces the Contingent Valuation Method for estimating environmental goods' value.

In Silico Neuroscience: Data Reproducibility and Reusability

Emphasizes data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods.

Image Processing: Practical

Covers practical image processing using Fiji software, emphasizing data quality importance.

Developing Environmental Health Strategies: Precision Public Health

Delves into developing environmental health strategies, emphasizing precision public health and the challenges of large-scale health studies.

Sustainable Resilient Value Chains: Circular Economy Insights

Covers the transition to circular economy and sustainable value chains in manufacturing.