Content Metadata Research Articles

Real-time context-aware social media recommendation

Social media recommendation has attracted great attention due to its wide applications in online advertisement and entertainment, etc. Since contexts highly affect social user preferences, great effort has been put into context-aware recommendation in recent years. However, existing techniques cannot capture the optimal context information that is most discriminative and compact from a large number of available features flexibly for effective and efficient context-aware social recommendation. To address this issue, we propose a generic framework for context-aware recommendation in shared communities, which exploits the characteristics of media content and contexts. Specifically, we first propose a novel approach based on the correlation between a feature and a group of other ones for selecting the optimal features used in recommendation, which fully removes the redundancy. Then, we propose a graph-based model called content---context interaction graph, by analysing the metadata content and social contexts, and the interaction between attributes. Finally, we design hash-based index over Apache Storm for organizing and searching the media database in real time. Extensive experiments have been conducted over large real media collections to prove the high effectiveness and efficiency of our proposed framework.

Bibliographic Control and Resource Description Access Standard in Malaysia

Technological advances and emergence of digital information present a significantly different challenge than libraries had before. With abundance of digital formats of information available in libraries, a new standard of cataloging has been introduced. The standard for cataloging that emphasized on the content of metadata which can support the discovery, identification and employment of information resources in library or known as Resource Description and Access (RDA) is designed for the digital environment. It is expected to have full implementation in all libraries in Malaysia by 2017. This announcement has been made by the former director of National Library of Malaysia. To accomplish this mission, training is considered a basic requirement for every librarian before the introduction of RDA. However, it is found to be great challenges in conducting training and implementation of RDA in many libraries. With regards to this matter this study focuses on literatures on RDA pertaining to; training, costs, cataloging procedures and integrated library system. The framework may become foundation for libraries in supporting RDA in bibliographic control. The insight will inspire and inform a wide array of new research agenda in the cataloging and metadata literature.

Metadata Life Cycles, Use Cases and Hierarchies

The historic view of metadata as “data about data” is expanding to include data about other items that must be created, used, and understood throughout the data and project life cycles. In this context, metadata might better be defined as the structured and standard part of documentation, and the metadata life cycle can be described as the metadata content that is required for documentation in each phase of the project and data life cycles. This incremental approach to metadata creation is similar to the spiral model used in software development. Each phase also has distinct users and specific questions to which they need answers. In many cases, the metadata life cycle involves hierarchies where latter phases have increased numbers of items. The relationships between metadata in different phases can be captured through structure in the metadata standard, or through conventions for identifiers. Metadata creation and management can be streamlined and simplified by re-using metadata across many records. Many of these ideas have been developed to various degrees in several Geoscience disciplines and are being used in metadata for documenting the integrated life cycle of environmental research in the Arctic, including projects, collection sites, and datasets.

Comparison of the Features of EPUB E-Book and SCORM E-Learning Content Model

E-books nowadays have greatly evolved in its presentation and functions, however its features for education need to be investigated and inspired because people who are accustomed to using printed books may consider and approach it in the same way as they do printed ones. Therefore, the authors compared the EPUB e-book content model with the SCORM e-learning content model from the respects of their content presentation, metadata and package structures. Drs. Chang and Hung found that 1) EPUB has the possibility to implement the advantage of content sharing and reusing. 2) EPUB e-books can present educational materials with multimedia and interactive components based on web technology. However, content creators should beware of the limited supported media types 3) EPUB lacks dedicated educational metadata. 4) EPUB e-books have a content reflow mechanism to adjust layouts to fit small screen devices and are able to use all resources offline. Finally, they determined the research issues and strategies that are worthy of further investigation and development for EPUB e-books in education based on our findings.

A novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures

Advances in Metadata research have been instrumental in predictions and ‘fitness-of-use evaluation’ for the effective Decision-making process. For the past two decades, the model has been developed to provide visual assistance for assessing the quality information in metadata and quantifying the degree of metadata population. Still, there is a need to develop a framework that can be generic to adopt all the standards available for Geospatial Metadata. The computational analysis of metadata for specific applications remains uncharted for investigations and studies. This work proposes a computational framework for Geospatial Metadata by integrating TopicMaps and Hypergraphs (HXTM) based on the elements and their dependency relationships. A purpose-built dataset extracted from schemas of various standardisation organisations and existing knowledge in the discipline is utilised to model the framework and thereby evaluate ranking strategies. Hypergraph-Helly Property based Weight-Assignment Algorithm (HHWA) have been proposed for HXTM framework to calculate Stable weights for Metadata Elements. Recursive use of Helly-property ensures predominant elements, while Rank Order Centroid (ROC) method is used to compute standard weights. A real corpus using case studies from FGDC’s Standard for Geospatial Metadata, INSPIRE Metadata Standards, and ISRO Metadata Content Standard (NSDI 2.0) is used to validate the proposed framework. The observations show that the Information Gain (Entropy) of the proposed model along with the algorithm proves to be computationally smart for quantification purposes and visualises the strength of Metadata Elements for all applications. A prototype tool, ‘MetDEVViz- MetaData Editor, Validator & Visualization’ is designed to exploit the benefits of the proposed algorithm for the case studies that acts as a web service to provide a user interface for editing, validating and visualizing metadata elements.

Full-range, solar-reflected hyperspectral microscopy to support earth remote sensing research

Over the past 20 years, hyperspectral microscopy has grown into a robust field of analysis for a number of applications. The visible to near-infrared (VNIR; 400 to 1000 nm) region of the spectrum has demonstrated utility for the characterization of healthy and diseased tissue and of biomolecular indicators at the cellular level. Here, we describe the development of a hyperspectral imaging (HSI) microscope that is aimed at material characterization to complement traditional stand-off, earth remote sensing with hyperspectral sensors. We combine commercial off the shelf technology to build an HSI microscope to collect spectral data with illumination provided by a tunable laser. Hyperspectral imaging microscopy (HIM) facilitates detailed examination of target materials at the subcentimeter spatial scale. The custom-built, laser illumination HSI microscope covers the NIR to shortwave infrared (NIR/SWIR; 900 to 2500 nm) solar-reflected spectral range. It is combined with a separate VNIR sensor (400 to 900 nm) that utilizes quartz–tungsten–halogen lamps for illumination. The combined sensors provide a means to collect >10,000 s of spectra in the full VNIR/SWIR spectral range from both pure substances and precisely engineered linear and nonlinear mixtures. The large abundance of spectra allows for a more detailed understanding of the variability and multivariate probability distributions of spectral signatures. This additional information aids in understanding the variability observed in ground truth spectra collected from portable spectrometers, and it greatly enhances sample description and metadata content. In addition, HIM data cubes can serve as proxies, as “microscenes,” for systems engineering applications such as trade studies for HSI acquired by air- and space-borne sensors.

Towards a holistic model for quality of learning object repositories

PurposeThis paper aims to address the need to ensure the quality of metadata records describing learning resources. We propose improvements to a metadata-quality model, specifically for the compliance sub-feature of the functionality feature. Compliance is defined as adherence level of the learning object metadata content to the metadata standard used for its specification. The paper proposes metrics to assess the compliance, which are applied to a set of learning objects, showing their applicability and usefulness in activities related to resources management.Design/methodology/approachThe methodology considers a first stage of metrics refinement to obtain the indicator of the sub-feature compliance. The next stage is the proposal evaluation, where it is determined if metrics can be used as a conformity indicator of learning object metadata with a standard (metadata compliance). The usefulness of this indicator in the information retrieval area is approached through an assessment of learning objects where the quality level of its metadata and the ranking in which they are retrieved by a repository are correlated.FindingsThis study confirmed that the best results for metrics of standardization, completeness, congruence, coherence, correctness and understandability, which determine the compliance indicator, were obtained for learning objects whose metadata were better labelled. Moreover, it was found that the learning objects with the highest level of compliance indicator have better positions in the ranking when a repository retrieves them through an exact search based on metadata.Research limitations/implicationsIn this study, only a sub-feature of the quality model is detailed, specifically the compliance of learning object standard. Another limitation was the size of the learning objects set used in the experiment.Practical implicationsThis proposal is independent from any metadata standard and can be applied to improve processes associated with the management of learning objects in a repository-like retrieval and recommendation.Originality/valueThe originality and value of this proposal are related to quality of learning object metadata considered from a holistic point of view through six metrics. These metrics quantify both technical and pedagogical aspects through automatic evaluation and supported by experts. In addition, the applicability of the indicator in recovery systems is shown, by example to be incorporated as an additional criterion in the learning object ranking.

The influence of community recommendations on metadata completeness

Many communities use standard, structured documentation that is machine-readable, i.e. metadata, to make discovery, access, use, and understanding of scientific datasets possible. Organizations and communities have also developed recommendations for metadata content that is required or suggested for their data developers and users. These recommendations are typically specific to metadata representations (dialects) used by the community. By considering the conceptual content of the recommendations, quantitative analysis and comparison of the completeness of multiple metadata dialects becomes possible. This is a study of completeness of EML and CSDGM metadata records from DataONE in terms of the LTER recommendation for Completeness. The goal of the study is to quantitatively measure completeness of metadata records and to determine if metadata developed by LTER is more complete with respect to the recommendation than other collections in EML and in CSDGM. We conclude that the LTER records are broadly more complete than the other EML collections, but similar in completeness to the CSDGM collections.

국내 과학기술콘텐츠 전거데이터 구축을 위한 소속기관명 식별 방법과 시스템에 관한 연구

과학기술콘텐츠(논문, 특허, 보고서)는 과학기술에 대한 연구와 개발을 위해 연구자들이 가장 많이 활용하는 참고자료이다. 과학기술콘텐츠와 도서관에서 보유 중인 서지 정보 검색을 위해 다양한 검색 요소(제목, 초록, 키워드, 발행 연도, 학술지명, 저자명, 출판사 등)를 활용한 서비스들이 제공되고 있다. 저자의 소속기관명 전거데이터는 저자 식별을 위한 요소, 특정 기관의 연구, 개발 결과물 검색을 위한 요소 등으로 유용하게 활용될 수 있지만 현재 서비스되고 있는 국내 학술 정보와 도서관 서지 검색 서비스들에서는 소속기관명에 대해 고려하지 않고 있다. 이에 따라 본 연구에서는 국내 과학기술콘텐츠의 전거데이터 구축을 위해 식별 대상인 과학기술콘텐츠의 메타데이터에 포함되어 있는 소속기관 데이터를 분석하고 본 연구에서 제안한 문자열 간의 포함관계를 고려한 문자열 완전일치 검색(Exact String Matching) 방법을 활용한 식별 방법과 시스템을 제안한다. Science and technology contents (research papers, patents, reports) are the most common reference material for researchers involved in research and development in the fields of science and technology. Based on various search elements (title, abstract, keyword, year of publication, name of journal, name of author, publisher, etc.), many services are available for users to search science and technology contents and bibliographic information owned by libraries. Authority data on organization name can be useful as an element for author identification and as an element to search for results produced by specific organizations. However, organization name is not taken into account by current search services for domestic academic information and bibliographic records. This study analyzes organization name data contained in the metadata of science and technology contents, which are the basis of the establishment of authority data, and proposes a method and system based on string containment and exact string matching.

Ultra HD Blu-ray Format Video Characteristics

The Blu-ray Disc Association recently finished a new format extension called Ultra HD Blu-ray. The new format supports next-generation video technologies and several optional enhancements. This paper provides an in-depth description of the video technologies offered by Ultra HD Blu-ray and an overview of new optional features. The Ultra HD Blu-ray format allows improvement to the video representation by increasing the pixel code value quantization to 10 bits, enabling representation of high dynamic range imagery using SMPTE ST 2084 electrooptical transfer function, enabling representation of wide color gamut imagery using International Telecommunications Union Radiocommunication Sector (ITU-R) BT.2020 color primaries, increasing spatial resolution to 3840 $\times$ 2160, and allowing increased frame rates up to 60p. Carriage of mastering display color volume metadata described by SMPTE ST 2086 and new content metadata parameters called maximum content light level (MaxCLL) and maximum frame average light level (MaxFALL) are also enabled by the new format. Additionally, the Ultra HD Blu-ray format improves compression efficiency by using the new HEVC/H.265 video compression standard.

Computational data privacy in wireless networks

Wireless networks appeal to privacy eavesdroppers that secretly capture packets from the open medium and read the metadata and data content in search of any type of information through data mining and statistical analysis. Addressing the problems of personal privacy for wireless users will require flexible privacy protection mechanisms adaptively to the frequently varying context. Privacy quantification is prerequisite for enabling a context-aware privacy protection in wireless networks. This paper proposes to quantify the data privacy during wireless communication processes. We give a computational quantification method of data privacy through introducing the concepts of privacy entropy and privacy joint entropy, which permits users and applications to on-demand customize their preferential sensitivity extent of privacy leakage and protection strength. Accordingly, we put forward a data-privacy protection scheme in order to explain how to utilize the proposed computational quantification method of data privacy against the excessive disclosure of data privacy. The results show that the computational quantitation method can effectively characterize the real-time fluctuation of data privacy during communication processes and provide the reliable judgment to context-aware privacy protection, which enables to real-timely control the present data privacy to an anticipated target and to balance a tradeoff between the data privacy and communication efficiency.

An Overview of Repositories of Learning Objects

This work addresses the dispersion of learning resources on the Internet-many languages, all areas of knowledge, aims at different audiences, many “sizes” and varied quality; many are open to all. This paper presents the results of some searches on the Internet for Control Systems resources and suggests the implementation of a union catalog of metadata of contents from cooperating institutions. Union catalogs of theses and dissertations are mentioned as possible models.

MTN: A South African mobile telecommunications group in Africa and Asia

ABSTRACTThe MTN Group, based in South Africa, is a multinational enterprise from an emerging economy (EE-MNE), operating mobile telecommunications networks in Asia and Africa. It was built up by negotiating licences and by acquiring operators, notably Investcom, a Lebanese-owned firm with operations in Asia, Africa and Cyprus. Such opportunities arose from the liberalisation of national markets and the financialisation of the sector. MTN now has licences from some very unattractive governments, to which it pays taxes, provides wire-tapping, collects metadata and censors content. Its business partners have included political parties, cronies of political leaders and individuals on a United Nations asset freeze list. It denies allegations it displaced a rival in Iran by corrupt means. It successfully became a major international operator, but acquisitions have stopped, forcing it to rely on organic growth and new technologies.

Nomenclatural availability of preliminary electronic versions of taxonomic papers: in need of a clear definition

The question of the nomenclatural availability of preliminary electronic versions of taxonomic papers, distributed online 'ahead of print' by some journals and publishing companies, is addressed again. We disagree with Krell's suggestion to 'distinguish between content and bibliographical metadata'. The concept of 'biblio- graphical metadata' does not exist in the Code and should not be incorporated into it. The citation of publication date, issue and page numbers are part of the relevant information that is useful in bibliographic references, in text citations and in synonymic lists that appear in taxonomic publications (which have a much longer life than most other publications), and should be considered part of the 'content' of a taxonomic paper. In particular, the page of first appearance of a name or of a nomenclatural act is traditionally cited in taxonomic revisions, monographs, faunas and catalogues, whether printed or stored in online databases, and this information is very useful for serious taxonomists. Having two different sets of information in this respect, in a first version of the work first published online but then discarded from the website of the journal, and in a subsequent one included into a journal issue, would be an indisputable source of confusion, which would not be solved by calling artificially both these versions the 'version of record' as if they were identical. The fact that 'pagination is not regulated' by the Code is fully irrelevant here: many aspects of taxonomic works are not regulated by the Code but are of crucial importance for the discipline of taxonomy. Krell's proposal is motivated, according to his own words, by some publishers' desire to make their publications more 'attractive as outlets of taxonomic research'. But the purpose of the Code is not to make some journals more attractive than others; it is to help working taxonomists in their daily work, to make it easier, more straightforward, efficient, reliable and useful, and less prone to ambiguity. We recommend rejecting Krell's suggestion. On the other hand, we make the new proposal of the creation of a 'label' to which some online journals and publishing companies might adhere, taking the engagement to publish online only one single version of each paper, with its final date, issue number and pagination. Authors will then have the possibility to choose their publication outlet among those having this label or those following the practice of 'early view'. Currently, such preliminary versions of papers are unavailable under the 2012 Amendment of the Code.

Enhancing the online discovery of geospatial data through taxonomy, folksonomy and semantic annotations

Spatial data infrastructures (SDIs) are meant to facilitate dissemination and consumption of spatial data, amongst others, through publication and discovery of spatial metadata in geoportals. However, geoportals are often known to geoinformation communities only and present technological limitations which make it difficult for general purpose web search engines to discover and index the data catalogued in (or registered with) a geoportal. The mismatch between standard spatial metadata content and the search terms that Web users employ when looking for spatial data, presents a further barrier to spatial data discovery. The need arises for creating and sharing spatial metadata that is discoverable by general purpose web search engines and users alike. Using folksonomies and semantic annotations appears as an option to eliminate the mismatch and to publish the metadata for discovery on the Web. Based on an analysis of search query terms employed when searching for spatial data on the Web, a taxonomy of search terms is constructed. The taxonomy constitutes the basis towards understanding how web resources in general, and HTML pages with standard spatial metadata in particular, can be documented so that they are discoverable by general purpose web search engines. We illustrate the use of the constructed taxonomy in semantic annotation of web resources, such as HTML pages with spatial metadata on the Web.

Meeting the Needs of Data Management Training: The Federation of Earth Science Information Partners (ESIP) Data Management for Scientists Short Course.

With the proliferation of digital technologies, scientists are exploring various methods for the integration of data to produce scientific discoveries. To maximize the potential of data for science advancement, proper stewardship must be provided to ensure data integrity and usability both for the short- and the long-term. In order to assist scientists and their library and information partners to gain familiarity, skills, and knowledge of data management, the Federation of Earth Science Information Partners (ESIP) has developed the Data Management for Scientists Short Course. The Short Course provides training on a range of data management topics, including metadata, file formats, and interoperable content. This paper provides an overview of the background and motivation for data management, followed by an introduction to the Short Course. The discussion on the Short Course' features demonstrates the advantages of learning the fundamentals of data management through the Short Course. The paper concludes by emphasizing the importance of familiarity with data management practices for both researchers and their library and information partners. [ABSTRACT FROM AUTHOR]

A web-based IPTV content syndication system for personalized content guide

In this paper, we propose a web-based content syndication system in which users can easily choose Internet protocol television (IPTV) contents. This system generates personalized content guide to provide a list of IPTV contents with respect to users' interests and statistics information of their online social community. For this, IPTV contents and relevant metadata are collected from various sources and transformed. Then, the service and content metadata are processed by user metadata including audience measurement and community metadata. The metadata flows are separated from content flows of transport network. The implementation of IPTV content syndication system demonstrates how to arrange IPTV contents efficiently from content providers to the end user's screen. We also show that the user metadata including online community information are important for the system's performance and the user's satisfaction.

Domain discovery and expansion in multimedia metadata for digital TV broadcast

The emergence of the Interactive Digital TV iDTV is improving the transmission quality and making available new features and services to the user. With the advent of digital convergence between TV and web platforms, new proposals of semantic organisation of content are being developed, introducing concepts of Semantic Web and knowledge representation that allow semantic description of metadata content through ontologies. This paper proposes a component for finding domains and expansion of multimedia metadata in broadcast DTV based on the Semantic Web concepts and analysis of lexical and semantic similarity, integrated with knowledge TV platform.

Constructing compact and effective graphs for recommender systems via node and edge aggregations

Exploiting graphs for recommender systems has great potential to flexibly incorporate heterogeneous information for producing better recommendation results. As our baseline approach, we first introduce a naïve graph-based recommendation method, which operates with a heterogeneous log-metadata graph constructed from user log and content metadata databases. Although the naïve graph-based recommendation method is simple, it allows us to take advantages of heterogeneous information and shows promising flexibility and recommendation accuracy. However, it often leads to extensive processing time due to the sheer size of the graphs constructed from entire user log and content metadata databases. In this paper, we propose node and edge aggregation approaches to constructing compact and effective graphs called ‘Factor-Item bipartite graphs’ by aggregating nodes and edges of a log-metadata graph. Experimental results using real world datasets indicate that our approach can significantly reduce the size of graphs exploited for recommender systems without sacrificing the recommendation quality.

Human content filtering in Twitter: The influence of metadata

Social micro-blogging systems such as Twitter are designed for rapid and informal communication from a large potential number of participants. Due to the volume of content received, human users must typically skim their timeline of received content and exercise judgement in selecting items for consumption, necessitating a selection process based on heuristics and content meta-data. This selection process is not well understood, yet is important due to its potential use in content management systems.In this research we have conducted an open online experiment in which participants are shown quantitative and qualitative meta-data describing two pieces of Twitter content. Without revealing the text of the tweet, participants are asked to make a selection. We observe the decisions made from 239 surveys and discover insights into human behaviour on decision making for content selection. We find that for qualitative meta-data consumption decisions are driven by online friendship and for quantitative meta-data the largest numerical value presented influences choice. Overall, the ‘number of retweets’ is found to be the most influential quantitative meta-data, while displaying multiple cues about an author׳s identity provides the strongest qualitative meta-data. When both quantitative and qualitative meta-data is presented, it is the qualitative meta-data (friendship information) that drives selection. The results are consistent with application of the Recognition heuristic, which postulates that when faced with constrained decision-making, humans will tend to exercise judgement based on cues representing familiarity. These findings are useful for future interface design for content filtering and recommendation systems.