The METAFOR project: preserving data through metadata standards for climate models and simulations

Climate modeling is a complex process, requiring accurate and complete metadata in order to identify, assess and use climate data stored in digital repositories. The preservation of such data is increasingly important given the development of ever-increasingly complex models to predict the effects of global climate change. The EU METAFOR project has developed a Common Information Model (CIM) to describe climate data and the models and modelling environments that produce this data. There is a wide degree of variability between different climate models and modelling groups. To accommodate this, the CIM has been designed to be highly generic and flexible, with extensibility built in. METAFOR describes the climate modelling process simply as "an activity undertaken using software on computers to produce data." This process has been described as separate UML packages (and, ultimately, XML schemas). This fairly generic structure canbe paired with more specific "controlled vocabularies" in order to restrict the range of valid CIM instances. The CIM will aid digital preservation of climate models as it will provide an accepted standard structure for the model metadata. Tools to write and manage CIM instances, and to allow convenient and powerful searches of CIM databases,. Are also under development. Community buy-in of the CIM has been achieved through a continual process of consultation with the climate modelling community, and through the METAFOR team’s development of a questionnaire that will be used to collect the metadata for the Intergovernmental Panel on Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs.

Towards a standardised metadata protocol for urban meteorological networks

With the growing number and significance of urban meteorological networks (UMNs) across the world, it is becoming critical to establish a standard metadata protocol. Indeed, a review of existing UMNs indicate large variations in the quality, quantity, and availability of metadata containing technical information (i.e., equipment, communication methods) and network practices (i.e., quality assurance/quality control and data management procedures). Without such metadata, the utility of UMNs is greatly compromised. There is a need to bring together the currently disparate sets of guidelines to ensure informed and well-documented future deployments. This should significantly improve the quality, and therefore the applicability, of the high-resolution data available from such networks. Here, the first metadata protocol for UMNs is proposed, drawing on current recommendations for urban climate stations and identified best practice in existing networks

Understanding climate data through commentary metadata: the CHARMe project

We describe the CHARMe project, which aims to link climate datasets with publications, user feedback and other items of "commentary metadata". The system will help users learn from previous community experience and select datasets that best suit their needs, as well as providing direct traceability between conclusions and the data that supported them. The project applies the principles of Linked Data and adopts the Open Annotation standard to record and publish commentary information. CHARMe contributes to the emerging landscape of "climate services", which will provide climate data and information to influence policy and decision-making. Although the project focuses on climate science, the technologies and concepts are very general and could be applied to other fields.

Towards a Protocol for the Attachment of Metadata to Service Descriptions and its Use in Semantic Discovery

Service discovery in large scale, open distributed systems is difficult because of the need to filter out services suitable to the task at hand from a potentially huge pool of possibilities. Semantic descriptions have been advocated as the key to expressive service discovery, but the most commonly used service descriptions and registry protocols do not support such descriptions in a general manner. In this paper, we present a protocol, its implementation and an API for registering semantic service descriptions and other task/user-specific metadata, and for discovering services according to these. Our approach is based on a mechanism for attaching structured and unstructured metadata, which we show to be applicable to multiple registry technologies. The result is an extremely flexible service registry that can be the basis of a sophisticated semantically-enhanced service discovery engine, an essential component of a Semantic Grid.

Mapping Attribution Metadata to the Open Provenance Model

A description of a data item's provenance can be provided in dierent forms, and which form is best depends on the intended use of that description. Because of this, dierent communities have made quite distinct underlying assumptions in their models for electronically representing provenance. Approaches deriving from the library and archiving communities emphasise agreed vocabulary by which resources can be described and, in particular, assert their attribution (who created the resource, who modied it, where it was stored etc.) The primary purpose here is to provide intuitive metadata by which users can search for and index resources. In comparison, models for representing the results of scientific workflows have been developed with the assumption that each event or piece of intermediary data in a process' execution can and should be documented, to give a full account of the experiment undertaken. These occurrences are connected together by stating where one derived from, triggered, or otherwise caused another, and so form a causal graph. Mapping between the two approaches would be benecial in integrating systems and exploiting the strengths of each. In this paper, we specify such a mapping between Dublin Core and the Open Provenance Model. We further explain the technical issues to overcome and the rationale behind the approach, to allow the same method to apply in mapping similar schemes.

Ontology-based metadata for e-learning content

Nowadays, the popularity of the Web encourages the development of Hypermedia Systems dedicated to e-learning. Nevertheless, most of the available Web teaching systems apply the traditional paper-based learning resources presented as HTML pages making no use of the new capabilities provided by the Web. There is a challenge to develop educative systems that adapt the educative content to the style of learning, context and background of each student. Another research issue is the capacity to interoperate on the Web reusing learning objects. This work presents an approach to address these two issues by using the technologies of the Semantic Web. The approach presented here models the knowledge of the educative content and the learner’s profile with ontologies whose vocabularies are a refinement of those defined on standards situated on the Web as reference points to provide semantics. Ontologies enable the representation of metadata concerning simple learning objects and the rules that define the way that they can feasibly be assembled to configure more complex ones. These complex learning objects could be created dynamically according to the learners’ profile by intelligent agents that use the ontologies as the source of their beliefs. Interoperability issues were addressed by using an application profile of the IEEE LOM- Learning Object Metadata standard.

New technologies, old habits: automation without innovation

This research investigated the underuse of technological tools by innovative organizations which are acknowledged for their use of and familiarity with new technologies. The research conducted an analysis of 58 institutional repositories (IRs) out of 43 educational and research institutions which are internationally renowned for excellence. The core aspect of the analysis was the use of IRs for publishing and dealing with evidence in order to legitimize and add value to scientific research. The following items were analyzed: (a) the logical structuring of scientific communication published in the IRs; (b) the metadata which describe scientific communication based on the terms of the DCMI protocol used; (c) the availability of software functions which facilitate the queries and publication of evidences. Results show that the introduction of IRs did not add value to the quality of research in\ terms of associating and publishing evidence that could back them up. A strong tendency to replicate the traditional library model of physical collections was observed. It was concluded that merely possessing good technological tools is not sufficient for fostering innovation and strategic gains in organizations, even if their implementation takes place in highly promising and favorable environments.

Metadata Authority Description Schema (MADS): uma alternativa à utilização do formato MARC 21 para dados de autoridade

Introduction: Authority records interchange requires establishing and using metadata standards, such as MARC 21 Format for Authority Data, format used by several cataloging agencies, and Metadata Authority Description Schema (MADS), that has received little attention and it is a little widespread standard among agencies. Purpose: Presenting an introductory study about Metadata Authority Description Schema (MADS). Methodology: Descriptive and exploratory bibliographic research. Results: The paper address the MADS creation context, its goals and its structure and key issues related to conversion of records from MARC 21 to MADS. Conclusions: The study concludes that, despite its limitations, MADS might be used to create simple authority records in Web environment and beyond libraries context.

A conversão de registros na implantação de repositórios institucionais: o caso do Repositório Institucional UNESP

O Repositório Institucional UNESP foi criado em 2013 e, para sua implantação, foi povoado com dados obtidos de forma automática. Considerando a experiência realizada na UNESP, este trabalho tem por objetivo apresentar os processos utilizados para a conversão dos registros coletados de três diferentes fontes de dados (Web of Science, SciELO e Scopus) para inclusão no repositório. A partir da coleta dos registros, os padrões de metadados da Web of Science, da SciELO e da Scopus foram mapeados para o perfil de aplicação de metadados utilizado no repositório. Os registros foram coletados como arquivos XML e, para sua conversão, foram elaboradas folhas de estilo utilizando a linguagem XSLT. Após essa conversão, os arquivos XML foram convertidos em arquivos CSV e, então, importados no Repositório. Conclui-se que os processos de conversão utilizados permitiram alcançar as metas iniciais do Repositório e evitaram a necessidade de inclusão dos registros de forma manual.