Search (1532 results, page 1 of 77)

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Abstract

The lifecycles of format technology have been a defining concern for digital stewardship research and practice. However, little evidence exists to provide robust methods for assessing the state of any given format technology and describing its evolution over time. This article introduces relevant models from diffusion theory and market research and presents a replicable analysis method to compute models of technology evolution. Data cleansing and the combination of multiple data sources enable the application of nonlinear regression to estimate the parameters of the Bass diffusion model on format technology market lifecycles. Through its application to a longitudinal data set from the UK Web Archive, we demonstrate that the method produces reliable results and show that the Bass model can be used to describe format lifecycles. By analyzing adoption patterns across market segments, new insights are inferred about how the diffusion of formats and products such as applications occurs over time. The analysis provides a stepping stone to a more robust and evidence-based approach to model technology evolution.

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Abstract

Twitter, Facebook, and other related systems that we call social awareness streams are rapidly changing the information and communication dynamics of our society. These systems, where hundreds of millions of users share short messages in real time, expose the aggregate interests and attention of global and local communities. In particular, emerging temporal trends in these systems, especially those related to a single geographic area, are a significant and revealing source of information for, and about, a local community. This study makes two essential contributions for interpreting emerging temporal trends in these information systems. First, based on a large dataset of Twitter messages from one geographic area, we develop a taxonomy of the trends present in the data. Second, we identify important dimensions according to which trends can be categorized, as well as the key distinguishing features of trends that can be derived from their associated messages. We quantitatively examine the computed features for different categories of trends, and establish that significant differences can be detected across categories. Our study advances the understanding of trends on Twitter and other social awareness streams, which will enable powerful applications and activities, including user-driven real-time information services for local communities.

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Date

15. 1.2016 19:22:28

Source

Linked data and user interaction: the road ahead. Eds.: Cervone, H.F. u. L.G. Svensson

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Abstract

Purpose - In recent years, a large number of data repositories have been built and used. However, the extent to which scientific data are re-used in academic publications is still unknown. The purpose of this paper is to explore the functions of re-used scientific data in scholarly publication in different fields. Design/methodology/approach - To address these questions, the authors identified 827 publications citing resources in the Dryad Digital Repository indexed by Scopus from 2010 to 2015. Findings - The results show that: the number of citations to scientific data increases sharply over the years, but mainly from data-intensive disciplines, such as agricultural, biology science, environment science and medicine; the majority of citations are from the originating articles; and researchers tend to reuse data produced by their own research groups. Research limitations/implications - Dryad data may be re-used without being formally cited. Originality/value - The conservatism in data sharing suggests that more should be done to encourage researchers to re-use other's data.

Date

20. 1.2015 18:30:22

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Date

22. 3.2013 16:18:36

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Abstract

"Explore" is a user task introduced in the Functional Requirements for Subject Authority Data (FRSAD) final report. Through various case scenarios, the authors discuss how structured data, presented based on Linked Data principles and using knowledge organisation systems (KOS) as the backbone, extend the explore task within and beyond subject authority data.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

Numerous studies have explored the possibility of uncovering information from web search queries but few have examined the factors that affect web query data sources. We conducted a study that investigated this issue by comparing Google Trends and Baidu Index. Data from these two services are based on queries entered by users into Google and Baidu, two of the largest search engines in the world. We first compared the features and functions of the two services based on documents and extensive testing. We then carried out an empirical study that collected query volume data from the two sources. We found that data from both sources could be used to predict the quality of Chinese universities and companies. Despite the differences between the two services in terms of technology, such as differing methods of language processing, the search volume data from the two were highly correlated and combining the two data sources did not improve the predictive power of the data. However, there was a major difference between the two in terms of data availability. Baidu Index was able to provide more search volume data than Google Trends did. Our analysis showed that the disadvantage of Google Trends in this regard was due to Google's smaller user base in China. The implication of this finding goes beyond China. Google's user bases in many countries are smaller than that in China, so the search volume data related to those countries could result in the same issue as that related to China.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22

Theme

Data Mining

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Abstract

The present challenge faced by scientists working with Big Data comes in the overwhelming volume and level of detail provided by current data sets. Exceeding traditional empirical approaches, Big Data opens a new perspective on scientific work in which data comes to play a role in the development of the scientific problematic to be developed. Addressing this reconfiguration of our relationship with data through readings of Wittgenstein, Macherey, and Popper, we propose a picture of science that encourages scientists to engage with the data in a direct way, using the data itself as an instrument for scientific investigation. Using GIS as a theme, we develop the concept of cyber-human systems of thought and understanding to bridge the divide between representative (theoretical) thinking and (non-theoretical) data-driven science. At the foundation of these systems, we invoke the concept of the "semantic pixel" to establish a logical and virtual space linking data and the work of scientists. It is with this discussion of the relationship between analysts in their pursuit of knowledge and the rise of Big Data that this present discussion of the philosophical foundations of Big Data addresses the central questions raised by social informatics research.

Date

7. 3.2019 16:32:22

Theme

Data Mining

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Abstract

I analyze the text of an article that appeared in this journal in 2007 that published the results of a questionnaire in which a number of experts were asked to define the concepts of data, information, and knowledge. I apply standard information retrieval techniques to build a list of the most frequent terms in each set of definitions. I then apply information extraction techniques to analyze how the top terms are used in the definitions. As a result, I draw data-driven conclusions about the aggregate opinion of the experts. I contrast this with the original analysis of the data to provide readers with an alternative viewpoint on what the data tell us.

Date

16. 6.2014 19:22:57

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Abstract

This article describes in detail the library implementation of a Resource Description and Access (RDA) Enrichment project. The library "hybridized," or enriched legacy data from Anglo-American Cataloguing Rules bibliographic records by the addition of specific RDA elements. The project also cleaned up various other elements in the bibliographic data that were not directly RDA-related. There were over 28 million changes and edits made to these records, changes that would never have been made otherwise because the library lacked the resources to do them independently. The enrichment project made the bibliographic data consistent, and helped prepared the data for its eventual transition to a linked data environment.

Date

21. 1.2016 19:08:22

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Abstract

Researchers are producing an unprecedented deluge of data by using new methods and instrumentation. Others may wish to mine these data for new discoveries and innovations. However, research data are not readily available as sharing is common in only a few fields such as astronomy and genomics. Data sharing practices in other fields vary widely. Moreover, research data take many forms, are handled in many ways, using many approaches, and often are difficult to interpret once removed from their initial context. Data sharing is thus a conundrum. Four rationales for sharing data are examined, drawing examples from the sciences, social sciences, and humanities: (1) to reproduce or to verify research, (2) to make results of publicly funded research available to the public, (3) to enable others to ask new questions of extant data, and (4) to advance the state of research and innovation. These rationales differ by the arguments for sharing, by beneficiaries, and by the motivations and incentives of the many stakeholders involved. The challenges are to understand which data might be shared, by whom, with whom, under what conditions, why, and to what effects. Answers will inform data policy and practice.

Date

11. 6.2012 15:22:29

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Abstract

This paper describes the range and variation in access and use control policies and tools used by 24 web-based data repositories across a variety of fields. It also describes the rationale provided by repositories for their decisions to control data or provide means for depositors to do so. Using a purposive exploratory sample, we employed content analysis of repository website documentation, a web survey of repository managers, and selected follow-up interviews to generate data. Our results describe the range and variation in access and use control policies and tools employed, identifying both commonalities and distinctions across repositories. Using concepts from commons theory as a guiding theoretical framework, our analysis describes the following five dimensions of repository rules, or data commons boundaries: locus of decision making (depositor vs. repository), degree of variation in terms of use within the repository, the mission of the repository in relation to its scholarly field, what use means in relation to specific sorts of data, and types of exclusion.

Date

22. 8.2014 16:56:41

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Date

18. 3.2014 19:13:22

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Abstract

A lot of information that is already available on the Web, or retrieved from local information systems and social networks is structured in data silos that are not semantically related. Semantic technologies make it emerge that the use of typed links that directly express their relations are an advantage for every application that can reuse the incorporated knowledge about the data. For this reason, data integration, through reengineering (e.g. triplify), or querying (e.g. D2R) is an important task in order to make information available for everyone. Thus, in order to build a semantic map of the data, we need knowledge about data items itself and the relation between heterogeneous data items. In this paper, we present our work of providing Lexical Linked Data (LLD) through a meta-model that contains all the resources and gives the possibility to retrieve and navigate them from different perspectives. We combine the existing work done on knowledge domains (based on the Information Coding Classification) within the Multilingual Lexical Linked Data Cloud (based on the RDF/OWL EurowordNet and the related integrated lexical resources (MultiWordNet, EuroWordNet, MEMODATA Lexicon, Hamburg Methaphor DB).

Date

22. 9.2014 19:01:18

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

Purpose - The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach - The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings - The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value - Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.

Date

20. 1.2015 18:30:22

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Abstract

Defined in 1999 and paired with XML, the Resource Description Framework (RDF) has been cast as an RDF Schema, producing data that is well-structured but not validated, permitting certain illogical relationships. When stakeholders convened in 2014 to consider solutions to the data validation challenge, a W3C working group proposed Resource Shapes and Shape Expressions to describe the properties expected for an RDF node. Resistance rose from concerns about data and schema reuse, key principles in RDF. Ideally data types and properties are designed for broad use, but they are increasingly adopted with local restrictions for specific purposes. Resource Shapes are commonly treated as record classes, standing in for data structures but losing flexibility for later reuse. Of various solutions to the resulting tensions, the concept of record classes may be the most reasonable basis for agreement, satisfying stakeholders' objectives while allowing for variations with constraints.

Footnote

Contribution to a special section "Linked data and the charm of weak semantics".

Source

Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22

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Abstract

Digital archives are the preferred means for open access to research data. They play essential roles in knowledge infrastructures-robust networks of people, artifacts, and institutions-but little is known about how they mediate information exchange between stakeholders. We open the "black box" of data archives by studying DANS, the Data Archiving and Networked Services institute of The Netherlands, which manages 50+ years of data from the social sciences, humanities, and other domains. Our interviews, weblogs, ethnography, and document analyses reveal that a few large contributors provide a steady flow of content, but most are academic researchers who submit data sets infrequently and often restrict access to their files. Consumers are a diverse group that overlaps minimally with contributors. Archivists devote about half their time to aiding contributors with curation processes and half to assisting consumers. Given the diversity and infrequency of usage, human assistance in curation and search remains essential. DANS' knowledge infrastructure encompasses public and private stakeholders who contribute, consume, harvest, and serve their data-many of whom did not exist at the time the DANS collections originated-reinforcing the need for continuous investment in digital data archives as their communities, technologies, and services evolve.

Date

7. 7.2019 11:58:22

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Abstract

As a part of a research project aiming to connect library data to the unfamiliar data sets available in the Linked Data (LD) community's CKAN Data Hub (thedatahub.org), this project collected, analyzed, and mapped properties used in describing and accessing music recordings, scores, and music-related information used by selected music LD data sets, library catalogs, and various digital collections created by libraries and other cultural institutions. This article reviews current efforts to connect music data through the Semantic Web, with an emphasis on the Music Ontology (MO) and ontology alignment approaches; it also presents a framework for understanding the life cycle of a musical work, focusing on the central activities of composition, performance, and use. The project studied metadata structures and properties of 11 music-related LD data sets and mapped them to the descriptions commonly used in the library cataloging records for sound recordings and musical scores (including MARC records and their extended schema.org markup), and records from 20 collections of digitized music recordings and scores (featuring a variety of metadata structures). The analysis resulted in a set of crosswalks and a unified crosswalk that aligns these properties. The paper reports on detailed methodologies used and discusses research findings and issues. Topics of particular concern include (a) the challenges of mapping between the overgeneralized descriptions found in library data and the specialized, music-oriented properties present in the LD data sets; (b) the hidden information and access points in library data; and (c) the potential benefits of enriching library data through the mapping of properties found in library catalogs to similar properties used by LD data sets.

Date

28.10.2013 17:22:17

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Abstract

This paper reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The paper discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and /or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the DDC (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

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Abstract

Machine-Readable Cataloging (MARC) is currently the most broadly used bibliographic standard for encoding and exchanging bibliographic data. However, MARC may not fully support representation of the dynamic nature and semantics of digital resources because of its rigid and single-layered linear structure. The Functional Requirements for Bibliographic Records (FRBR) model, which is designed to overcome the problems of MARC, does not provide sufficient data elements and adopts a predetermined hierarchy. A flexible structure for bibliographic data with detailed data elements is needed. Integrating MARC format with the hierarchical structure of FRBR is one approach to meet this need. The purpose of this research is to propose an approach that can facilitate interoperability between MARC and FRBR by providing a conceptual structure that can function as a mediator between MARC data elements and FRBR attributes.

Date

10. 9.2000 17:38:22