Related papers: Policy Aware Geospatial Data
The General Data Protection Regulation contains a blanket prohibition on the transfer of personal data outside of the European Economic Area unless strict requirements are met. The rationale for this provision is to protect personal data…
Generative models that can produce realistic images have improved significantly in recent years. The quality of the generated content has increased drastically, so sometimes it is very difficult to distinguish between the real images and…
Geological processes determine the distribution of resources such as critical minerals, water, and geothermal energy. However, direct observation of geology is often prevented by surface cover such as overburden or vegetation. In such…
Mining Software Repositories (MSRs) is an evidence-based methodology that cross-links data to uncover actionable information about software systems. Empirical studies in software engineering often leverage MSR techniques as they allow…
The demand for a huge amount of data for machine learning (ML) applications is currently a bottleneck in an empirically dominated field. We propose a method to combine prior knowledge with data-driven methods to significantly reduce their…
This paper introduces a novel problem, distributional information embedding, motivated by the practical demands of multi-bit watermarking for large language models (LLMs). Unlike traditional information embedding, which embeds information…
In cross-silo federated learning (FL), sensitive text datasets remain confined to local organizations due to privacy regulations, making repeated training for each downstream task both communication-intensive and privacy-demanding. A…
Building Information Modeling (BIM) is increasingly used in the construction industry, but existing studies often ignore embedded rebars. Ground Penetrating Radar (GPR) provides a potential solution to develop as-built BIM with surface…
Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The use of Big Data in farming requires the collection and…
Sharing scientific data, with the objective of making it fully discoverable, accessible, assessable, intelligible, usable, and interoperable, requires work at the disciplinary level to define in particular how the data should be formatted…
Machine Learning (ML) has been integrated into various software and systems. Two main components are essential for training an ML model: the training data and the ML algorithm. Given the critical role of data in ML system development, it…
The exponential growth in the number of complex datasets every year requires more enhancement in machine learning methods to provide robust and accurate data classification. Lately, deep learning approaches have achieved surpassing results…
In general, DRM (Digital Rights Management) system is responsible for the safe distribution of digital content, however, DRM system is achieved with individual function modules of cryptography, watermarking and so on. In this typical system…
This article focuses on the legal issues associated with open government data licenses. This study compares current open data licenses and argues that licensing terms reflect policy considerations, which are quite different from those…
Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are…
We propose a differentially private data generation paradigm using random feature representations of kernel mean embeddings when comparing the distribution of true data with that of synthetic data. We exploit the random feature…
Heterogeneous collections of ground and airborne imagery can readily be used to create high-quality 3D models and novel viewpoint renderings of the observed scene. Standard photogrammetry pipelines generate models in arbitrary coordinate…
The race to train language models on vast, diverse, and inconsistently documented datasets has raised pressing concerns about the legal and ethical risks for practitioners. To remedy these practices threatening data transparency and…
This paper addresses the harmonization of metadata from diverse repositories of language resources (LRs). Leveraging linked data and RDF techniques, we integrate data from multiple sources into a unified model based on DCAT and META-SHARE…
As an emerging field, MS-based proteomics still requires software tools for efficiently storing and accessing experimental data. In this work, we focus on the management of LC-MS data, which are typically made available in standard…