Thomas C. O'Reilly

Standards-Based Plug & Work for Instruments in Ocean Observing Systems

Ocean observing systems may include a wide variety of sensor and instrument types, each with its own capabilities, communication protocols, and data formats. Connecting disparate devices into a network typically requires specialized software drivers that translate command and data between the protocols of the individual instruments, and that of the platform on which they are installed. In addition, such platforms typically require extensive manual configuration to match the driver software and other operational details of each network port to a specific connected instrument. In this paper, we describe an approach to “plug & work” interoperability, using standardized protocols to greatly reduce the amount of instrument-specific software and manual configuration required for connecting instruments to an observatory system. Our approach has two main components. First, we use the sensor interface descriptor (SID) model, based on the Open Geospatial Consortiums (OGC) SensorML standard, to describe each instruments protocol and data format, and to provide a generic driver/parser. Second, a new OGC standard known as the programmable underwater connector with knowledge (PUCK) protocol enables storage and retrieval of the SID file from the instrument itself. We demonstrate and evaluate our approach by applying it to three commonly used marine instruments in the OBSEA (Barcelona, Spain) observatory test bed.

MBARI Technology for Self-Configuring Interoperable Ocean Observatories

The ocean science and engineering communities have identified some key requirements for large-scale ocean observatories at a recent ORION-sponsored workshop, and these requirements are being refined by the ORION project and others. MBARI has developed and deployed hardware and software technologies that address many of these requirements. In particular, we describe how these technologies address several key issues: (1) scalable integration, configuration, and management of large numbers of diverse instruments and data streams, (2) reliable association of instrument data and contextual metadata, and (3) development of observatory infrastructure and components that are interoperable among a variety of observatory architectures, including at-sea systems with relatively limited power and bandwidth availability. We focus on three technologies developed at MBARI. These technologies work together to enable MBARIs self-configuring self-describing MOOS mooring-based observatory. Yet these technologies have been designed to be largely independent of an observatorys physical implementation, and will be deployed for testing on the MARS cable-to-shore observatory test-bed. Moreover each of the technologies provide components that could be selectively used by other observatories. For example, PUCKs could be widely useful and are not dependent in any way on SIAM middleware or SSDS metadata structures. We also describe lessons learned during development and deployment of these technologies, and how policies and human-procedures interact with the new technologies. Finally, we discuss how these technologies are being refined through community efforts such as the emerging Marine Plug and Work Consortium and Marine Metadata Initiative

Ocean Observing System Instrument Network Infrastructure

We summarize results of a Workshop on Instrument Software Infrastructure held at MBARI, Moss Landing, California USA from September 13-15, 2004, jointly sponsored the National Science Foundation (NSF) and Ocean Research Interactive Observatory Networks (ORION) program. The Workshop included over fifty participants, including international participants from Germany, Canada, and Japan. This was one of the first technical workshops in the development of a series of ocean observatories under the US Ocean Observatory Initiative (OOI) being managed under the ORION program. The specific focus of this workshop was to define the standard requirements to be met by software infrastructure for sensors, instruments and platforms for observing systems in the ORION program. These requirements include the issues of configuring, interfacing, and managing devices, including sensors and actuators, to a networked based observing system as well as managing the resources necessary to support such devices. The topics include the capability of supporting plug-and-work instrumentation using service oriented network architecture. A major issue addressed is the observatory infrastructure requirements necessary for managing data and metadata coming from sensors and instruments of the observatory in support of an integrated data management system

Issues in Data Management in Observing Systems and Lessons Learned

With ocean observatories growing in importance and several development efforts underway, it is critical to understand the goals and issues that an ocean observing system will have to face and solve. There are many components such as network infrastructure, instrumentation, control systems, data systems and client applications that will need to interoperate seamlessly in order for the observatory to effectively meet the needs of the research community, policy makers, and the general public. For example, instruments serve as the critical foundation to the usefulness of the information extracted from an ocean observatory. However, configuring these instruments for deployment in an observatory can be a time consuming and error-prone task. Although manageable on an instrument-by-instrument basis, configuration becomes a very important issue as the size of the observatory and the number of instruments it operates grows. Each instrument type also has its unique power, communication and bandwidth requirements that further complicate their integration into observatory systems. As the complexity of integrating the instruments into the observatory increases, so does the overall operating cost of the observatory, thus affecting the overall capability of the system. For this reason, adding and removing instruments needs to be as simple as possible, which necessitates that the infrastructure handle a large portion of that integration automatically. Once these instruments are successfully deployed, the infrastructure must also be able to monitor the health and status of the various observatory assets. Once past the configuration and management issues of instruments, the observatory still faces other issues from this collection of data from these heterogeneous instruments. Metadata and data management are particularly difficult problems to handle from a systematic perspective. Being able to capture and utilize metadata and data is certainly one requirement of a data management system, but having it operate in an automated and robust way creates even more complications. The metadata associated with data must be correctly captured by the system but also maintained correctly and linked with other related metadata throughout the system. Through this metadata, the relationship between the data and its context (source, environment, location, etc) can be captured and utilized in the analysis of the data in search of various phenomenon like events, trends, patterns, etc. Adding to these complicated tasks is the requirement that this data system must interoperate with other systems as both a server and a client. Even with these high level goals and issues defined, there is no substitute for practical experience in affirming that the right goals and issues were identified. At the Monterey Bay Aquarium Research Institute (MBARI), we have had an active ocean observing development project (Monterey Ocean Observing System-MOOS) going for the past several years. With that experience, we have been able to identify several key issues and lessons learned that are relevant to ocean observatories both from the development and operational perspectives. This paper will describe the different goals that the MOOS system and its associated data management system, the Shore-Side Data System (SSDS) address. Specifically, we will discuss how the SSDS handles various data and metadata related issues and what is gained by solving those issues. Practical examples of these solutions will be given and they will be used to illustrate how, and why, certain issues are important for the data management system to address. As a final wrap up, a section on lessons learned will be discussed to help transition what we have learned to the general oceanographic community