CICI: Data Provenance: Collaborative Research: CY-DIR Cyber-Provenance Infrastructure for Sensor-Based Data-Intensive Research

如今，包括生物学、医学、农学、能源管理、水文学和地球科学在内的许多学科的科学家都依赖于使用从各种来源收集的大量数据集。这种收集是通过计算机技术的进步而实现的，例如收集湿度、空气质量等数据的传感器，以及分析数据的强大计算机系统。科学研究数据使用的增加带来了一些重要的挑战。数据可能存在错误，从而影响从数据得出的结论。科学研究必须具有可重复性，以支持科学不当行为的验证和检测。应对这些挑战需要跟踪研究项目中使用的数据。示例包括：跟踪数据的来源（例如获取一些图像的手机）及其地理位置；跟踪哪些计算机系统处理了数据；跟踪科学家如何修改给定数据。这样的一组信息被称为出处——非常类似于艺术品的出处。管理来源在技术上很复杂；但这对于数据密集型研究来说至关重要。该项目通过开发用于安全管理来源的软件系统，在这个方向上取得了重要进展。该项目开发了一个网络基础设施的来源管理系统，其中包括不同类型的主机、设备和数据管理系统。该概念验证系统被称为基于传感器的数据密集型研究的网络来源基础设施（CY-DIR），将在科学家基于传感器的数据收集过程的整个生命周期中为科学家提供支持，包括持续监控传感器以确保收集和记录来源，以及跨不同数据管理系统对数据的可追溯使用和处理。 CY-DIR 为研究人员提供有关传感器收集的数据的来源和元数据。通过使用传感器、安全日志记录技术和安全处理器中的高效加密技术，可以确保来源安全。该项目的研究将在几个领域提供新颖的成果：传感器数据的来源技术；传感器、移动设备和无人机系统的密钥管理；来源感知流数据处理技术；保护来源数据免遭篡改；跨不同数据管理系统的来源数据集成。

Today scientists in many disciplines, including biology, medicine, agronomy, energy management, hydrology, and earth sciences, rely on the use of massive datasets collected from various sources. Such collections are made possible by advances in computer technology such as sensors which collect data such as humidity, air quality and so forth, and powerful computer systems that analyze the data. The increased use of data for scientific research poses some important challenges. Data can have errors which impact conclusions derived from the data. Scientific research has to be reproducible to support validation and detection of scientific misconduct. Addressing these challenges requires tracking data used in research projects. Examples include: tracking the source that originated the data -- for example a mobile phone that acquired some images- and its geographic location; tracking which computer systems processed the data; tracking how scientists modified given data. Such a set of information is referred to as provenance -- very much like the provenance of artistic artifacts. Managing provenance is technically complex; yet it is key for data-intensive research. This project makes important advances in this direction by developing software systems for securely managing provenance. This project develops a provenance management system for cyberinfrastructure that includes different types of hosts, devices, and data management systems. The proof-of-concept system, referred to as Cyber-provenance Infrastructure for Sensor-based Data-Intensive Research (CY-DIR), will support scientists throughout the life-cycle of their sensor-based data collection processes, including the continuous monitoring of sensors to ensure that provenance is collected and recorded, and the traceable use and processing of the data across different data management systems. CY-DIR provides researchers with provenance and metadata about data being collected by sensors. Provenance security will be assured by the use of efficient encryption techniques for use in sensors, secure logging techniques, and secure processors. Research from this project will provide novel results in several areas: provenance techniques for sensor data; cryptographic key management for sensors, mobile devices, and unmanned aircraft systems; provenance aware streaming data processing techniques; protection of provenance data against tempering; provenance data integration across different data management systems.