A Miniature Data Repository on a Raspberry Pi

L'A. propose d'etendre le Simple Knowledge Organization System (SKOS) Core Guide (Guide des Systemes Simples d'Organisation des Connaissances) en lui adjoignant un mecanisme pour suivre les changements que connaissent les arrangements conceptuels tels que thesaurus ou plans de classification. Ce mecanisme d'ontogenie du vocabulaire permettrait d'ameliorer la recherche d'information et de prevenir la perte de documents, grâce a un systeme de recherche persistente parmi les differentes versions d'un meme plan conceptuel.

Currently, most of the repositories implement Dublin Core (DC) as metadata standard, allowing the application of Protocol for Metadata Harvesting (OAI-PMH: Open Archives Initiative — Protocol for Metadata Harvesting). However, DC is not the most appropriate standard for the description of learning objects, which makes necessary resort to other standards. The Learning Object Metadata (LOM) standard emerges as the most suitable for the description of learning objects. Also, other standards such as Common European Research Information Format (CERIF) Metadata Object Description Schema (MODS) arise among others. This variety of standards makes the interoperability between repositories will become increasingly complex. Most solutions, until now, propose to adopt a metadata standard and include the necessary metadata to be harvested. This paper presents a solution based on ontologies for interoperability between repositories that use different metadata in the description of its objects

The government of the Republic of Indonesia had issued a regulation to substitute computer terms in foreign language that have been used earlier into official computer terms in Bahasa Indonesia. This regulation was stipulated in Presidential Decree No. 2 of 2001 concerning the introduction of official computer terms in Bahasa Indonesia (known as Senarai Padanan Istilah/SPI). After sixteen years, people of Indonesia, particularly for academics, should have implemented the official computer terms in their official publications. This observation is conducted to discover the implementation of official computer terms usage in scientific publications which are written in Bahasa Indonesia. The data source used in this observation are the publications by the academics, particularly in computer science field. The method used in the observation is divided into four stages. The first stage is metadata harvesting by using Open Archive Initiative - Protocol for Metadata Harvesting (OAI-PMH). Second, converting the harvested document (in pdf format) to plain text. The third stage is text-preprocessing as the preparation of string matching. Then the final stage is searching the official computer terms based on 629 SPI terms by using Boyer-Moore algorithm. We observed that there are 240,781 foreign computer terms in 1,156 scientific publications from six universities. This result shows that the foreign computer terms are still widely used by the academics.

Soil moisture plays a significant role in both water and energy cycles. It is important to manage and analyze in situ sensor observations of soil moisture due to its impacts on agricultural and hydrological processes. Google Fusion Tables (GFT) is a cloud computing database that provides a service on the Web for data management and integration. Using GFT for managing soil moisture sensor observations, it is possible to take advantages of GFT for collaborative management, on-the-fly visualization, and flexible integration and analysis. The Open Geospatial Consortium (OGC) sensor observation service (SOS) can provide real-time or near-real-time observations in an interoperable way. Combing SOS and GFT together can take the best of both. The paper investigates how GFT could be employed for managing, visualizing, and analyzing soil moisture sensor observations. It describes the design and implementation of a cloud-based SOS for managing soil moisture data using cloud computing databases. By storing sensor observations in GFT, the SOS service is scalable, and observations can be visualized and analyzed on demand. Challenges and approaches on the integration of GFT and SOS are discussed. A prototype service on sharing and managing soil moisture sensor observations is developed to demonstrate the applicability of the approach.

SummaryThe Open Archives Initiative (OAI) is dedicated to solving problems of digital library interoperability. Its focus has been on defining simple protocols, most recently for the exchange of metadata from archives. The OAI evolved out of a need to increase access to scholarly publications by supporting the creation of interoperable digital libraries.As a first step towards such interoperability, a metadata harvesting protocol was developed to support the streaming of metadata from one repository to another, ultimately to a provider of user services such as browsing, searching, or annotation. This article provides an overview of the mission, philosophy, and technical framework of the OAI.

Semantic mediation of observation datasets through Sensor Observation Services

The Open Archives Initiative (OAI) Protocol for Metadata Harvesting (PMH) facilitates efficient interoperability between digital collections, in particular by enabling service providers to construct, with relatively modest effort, search portals that present aggregated metadata to specific communities. This paper describes the experiences of the University of Illinois at Urbana-Champaign Library as an OAI service provider. We discuss the creation of a search portal to an aggregation of metadata describing cultural heritage resources. We examine several key challenges posed by the aggregated metadata and present preliminary findings of a pilot study of the utility of the portal for a specific community (student teachers). We also comment briefly on the potential for using text analysis tools to uncover themes and relationships within the aggregated metadata.

The World-Wide Sensor Web is generating tremendous amount of real-time sensor data streams and will enable scientists to observe phenomena that are previously unobservable. As the concept of sensor web is to connect all the sensors and their data to achieve shared goals, improving the openness and accessibility of sensor data is important. The Open Geospatial Consortium Sensor Observation Service (SOS) defines standard web service protocols for sharing sensor data online in an interoperable manner. However, SOS has a relatively weak ecosystem, which makes it difficult to build and consume, and it only supports predefined queries. On the other hand, the OASIS1 Open Data Protocol (OData) has a strong ecosystem and flexible query functions. But the soft-typing approach of OData requires it to have a commonly agreed data model to be interoperable. As we argue that the two standards can benefit from each other, we propose a sensor data mediator solution and define an SOS entity data model for OData (SOS-OData) to bridge these two standards. Our prototype demonstrates that the proposed system can convert between existing SOS and SOS-OData services. As a result, we not only can consume SOS data with the flexible OData query functions, but can also easily build an SOS-compliant service with the strong OData ecosystem. We argue that the bridging between these two standards would consequently lead us to the vision of open data for sensor web.

The profusion of non-relevant information for a given query on the Web explains the pressing need for formulating ebullient strategies for pertinent Web resource discovery and retrieval. One of the major requirements for effective document retrieval is its diligently encoded metadata. At the same time metadata standards to be followed for annotating documents from large collections are pretty complex. This is because the standardized global metadata cannot represent all the elusive forms of document metadata for improved retrieval ranking. In this context, we propose an approach to facilitate document retrieval from multidisciplinary domains where each belonging to discrete domains would be indexed in a segregated instance of a repository. This would facilitate document metadata customization for each specific discipline by adding specific metadata themes. Since the approach retains the standard metadata schema in addition to the customized metadata schema, it would result in enhanced resource discovery. The metadata retrieval process will be supported by an extended protocol for metadata harvesting (X-PMH) [1] and will be implemented in each repository. The extended metadata harvesting approach has been used to tie together the metadata customization components made at various repository instances. The proposed framework could be integrated into Open Digital Libraries (ODLs) [2] and shall serve as an intrinsic model that adds value in the context of multidisciplinary metadata simplicity, maintenance, and descriptive metadata availability in the event of repository instance failures. Our approach is to implement this cost-effective architecture using the PKP-OAI (Public Knowledge Project – Open Archive Initiative) [3,4] harvester on DSpace [5], an open source digital repository platform that supports metadata harvesting in its innate form. Once this is fully achieved, a federated search build upon such repository instances using open source technologies [6] would yield promising results in the context of information retrieval.

Assessing the status and trends of the environment requires the collection, management and publication of spatially referred observations. Since many years, Long-Term Ecological Research sites in Europe collect ecological data, resulting in long-term data series. Nowadays, advanced software tools can enable discovering, accessing, and distributing collected data in a user friendly way. Based on Open Geospatial Consortium (OGC) standards, Web based Geographic Information System allows access to interoperable distributed repositories of observations. The present paper gives an overview of the methods and solutions proposed and tested in the LIFE+ project EnvEurope for the community of researchers of the Long-Term Ecosystem Research (LTER) Network in Europe. These solutions consist in a straightforward online environment for metadata management and discovery, shaped on the ecological community and its practices; components of a Spatial Data Infrastructure including both a network of repositories deploying observations via OGC SOS (Sensor Observation Service) services and Web user interfaces to access and visualize them. The success of the presented approach is linked to the development and availability of easy to define, ready to use tools, enabling site managers to create their own repositories and services.

We developed a mechanism for seamlessly providing weather data and long-term historical climate data from a gridded data source through an international standard web API, which was the Sensor Observation Service (SOS) defined by the Open Geospatial Consortium (OGC). The National Agriculture and Food Research Organization (NARO) Japan has been providing gridded climate data consisting of nine daily meteorological variables, which are average, minimum, maximum of air temperature, relative humidity, sunshine duration, solar radiant exposure, downward longwave radiation, precipitation and wind speed for 35 years covering Japan. The gridded data structure is quite useful for spatial analysis, such as developing crop suitability maps and monitoring regional crop development. Individual farmers, however, make decisions using historical climate information and forecasts for an incoming cropping season of their farms. In this regard, climate data at a point-based structure are convenient for application development to support farmers’ decisions. Through the proposed mechanism in this paper, the agricultural applications and analysis can request point-based climate data from a gridded data source through the standard API with no need to deal with the complicated hierarchical data structure of the gridded climate data source. Clients can easily obtain data and metadata by only accessing the service endpoint. The mechanism also provides several web bindings and data encodings for the clients’ convenience. Caching, including the pre-caching mechanism, was developed and evaluated to secure an effective response time. The mechanism enhances the accessibility and usability of the gridded weather data source, as well as SOS API for agricultural applications.

A conceptual data modeling framework with four levels of abstraction for environmental information

Monitoring the environment is critical for scientists to understand the environmental dynamics. However, the traditional monitoring systems such as sensor networks are usually labor-intensive and complicated to deploy. As the concept of citizen sensing has been proposed to include volunteers into the environmental monitoring systems, a key to realize the citizen sensing vision is to empower citizens with the low-cost and easy-to-use sensing devices. In this paper, we focus on two technologies that have the potential to realize the citizen sensing vision: the Internet of Things (IoT) and the world-wide sensor web. In order to address the issues from the decentralized and heterogeneous nature of IoT devices and sensors, we propose the TinySOS service, a tiny web server hosting a light-weight profile of Open Geospatial Consortium (OGC) Sensor Observation Service (SOS). By hosting open standard sensor web services on the IoT devices, not only the devices become self-describable, self-contained, and interoperable, but also the collected observations are accessible via the Internet as soon as they are measured. In this case, the sensor web can provide real-time sensor data streams in a much higher spatial and temporal resolution, which consequently allows scientists to observe phenomena that were previously unobservable.

PurposeTo make CDS/ISIS databases OAI‐compliant.Design/methodology/approachOne of the biggest obstacles for information dissemination to a user community is that many digital libraries or bibliographic databases use heterogeneous technologies that inhibit interoperability. The Open Archives Initiative (OAI) addresses interoperability by using a framework to facilitate the discovery of content stored in distributed archives or bibliographic databases through the use of the OAI Protocol for Metadata Harvesting (OAI‐PMH). Though the OAI‐PMH is becoming the de facto standard, many of the legacy databases or bibliographic systems, for various reasons, are not OAI‐compliant. CDS/ISIS is one such database system. In this paper, we discuss the static repository (SR) approach to make CDS/ISIS databases OAI‐compliant. The records from a CDS/ISIS database are exported onto a file and the exported records are then converted to the SR XML file format. The SR file is made OAI‐compliant either by ingesting it into the Kepler Archivelet or through the intermediation of a static repository gateway (SRG).FindingsThe SR is a simple approach for making bibliographic records contained in non‐OAI‐compliant systems, OAI‐compliant.Research limitations/implicationsThe SR approach is meant for records, which are relatively static. If the OAI‐compliance is achieved through the SRG, then the number of records contained in a SR file should not exceed 5,000. However, if the SR file is ingested into the Kepler Archivelet, then there is no restriction on the number of records contained in a SR file.

Location nowadays is an important aspect of the Web. One scenario in this respect are archives or collections of geo-tagged media items. More concretely, we can think of collections in the arts and humanities available via OAI-PMH (a protocol for metadata harvesting) on the web or web accessible personal media archives maintained in a peer-to-peer manner. In such scenarios for search problems, source selection becomes an important aspect. For example, we would like to access only those collections containing media items in a certain geospatial region (maybe we are interested in images from Shanghai only). Here, the geospatial search criterion allows for a high selectivity. What is needed in such a scenario are expressive and nevertheless compact representations or descriptions of the ``geospatial footprint'' of each collection. A minimum bounding rectangle would be a trivial but not very accurate option. Generally, summarization techniques for this purpose can be distinguished into three categories, geometric approaches, space partitioning approaches and hybrid approaches. In this work, we present novel hybrid techniques, which mostly apply a set of approximating minimum area rectangles for subspace description together with quantization techniques in order to increase the selectivity of the summaries and, at the same time, keep the storage requirements small.