1,720,965 research outputs found
Dealing with inconsistent and incomplete data in a semantic technology setting
No full textSemantic and traditional databases are vulnerable to Inconsistent or Incomplete Data (IID). A data set stored in a traditional or semantic database is queried to retrieve record(s) in a tabular format. Such retrieved records can consist of many rows where each row contains an object and the associated fields (columns). However, a large set of records retrieved from a noisy data set may be wrongly analysed. For example, a data analyst may ascribe inconsistent data as consistent or incomplete data as complete where he did not identify the inconsistency or incompleteness in the data. Analysis on a large set of data can be undermined by the presence of IID in that data set. Reliance as a result is placed on the data analyst to identify and visualise the IID in the data set.
The IID issues are heightened in open world assumptions as evident in semantic or Resource Description Framework (RDF) databases. Unlike the closed world assumption in traditional databases where data are assumed to be complete with its own issues, in the open world assumption the data might be assumed to be unknown and IID has to be tolerated at the outset. Formal Concept Analysis (FCA) can be used to deal with IID in such databases. That is because FCA is a mathematical method that uses a lattice structure to reveal the associations among objects and attributes in a data set.
The existing FCA approaches that can be used in dealing with IID in RDF databases include fault tolerance, Dau's approach, and CUBIST approaches. The new FCA approaches include association rules, semi-automated and automated methods in FcaBedrock. These new FCA approaches were developed in the course of this study. To underpin this work, a series of empirical studies were carried out based on the single case study methodology. The case study, namely the Edinburgh Mouse Atlas Gene Expression Database (EMAGE) provided the real-life context according to that methodology. The existing and the new FCA approaches were used in identifying and visualising the IID in the EMAGE RDF data set.
The empirical studies revealed that the existing approaches used in dealing with IID in EMAGE are tedious and do not allow the IID to be easily visualised in the database. It also revealed that existing FCA approaches for dealing with IID do not exclusively visualise the IID in a data set. This is unlike the new FCA approaches, notably the semi-automated and automated FcaBedrock that can separate out and thus exclusively visualise IID in objects associated with the many value attributes that characterise such data sets. The exclusive visualisation of IID in a data set enables the data analyst to identify holistically the IID in his or her investigated data set thereby avoiding mistaken conclusions.
The aim was to discover how effective each FCA approach is in identifying and visualising IID, answering the research question: "How can FCA tools and techniques be used in identifying and visualising IID in RDF data?" The automated FcaBedrock approach emerged to be the best means for visually identifying IID in an RDF data set. The CUBIST approaches and the semi-automated approach were ranked as 2nd and 3rd, respectively, whilst Dau's approach ranked as 4th. Whilst the subject of IID in a semantic technology setting could be explored further, it can be concluded that the automated FcaBedrock approach best identifies and visualises the IID in an RDF thus semantic data set
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriating Data from Structured Sources for Formal Concept Analysis
Get PDFFormal Concept Analysis (FCA) is a principled way of deriving a concept hierarchy from a collection of objects and their associated attributes, building on the mathematical theory of lattices and ordered sets.
To conduct FCA, some appropriation steps need to be taken on a set of data as a prerequisite. Firstly, the data need to be acquired from a data source and decisions need to be made about how the data will be analyzed, such as
which objects will be included in the analysis, and how each attribute should be interpreted. They then need to be transformed into a formal context, which can then be visualized as a formal concept lattice.
Transforming a formal context into its constituent formal concepts is a process which is well defined and well understood in literature. The same holds true for converting formal concepts into a formal concept lattice.
On the other hand, the process of appropriating a dataset into a formal context tends to be an ad-hoc and bespoke one. ToscanaJ can produce formal contexts from a relational database, while ConExp can produce simple formal
contexts in a manual fashion. In the CUBIST project, Dau developed a semi-automated, scalingless approach to generate formal contexts out of a triple store by concatenating the object-attribute pairs returned from the resulting
table into their corresponding formal attributes, while Orphanides developed an approach that also provided scaling capabilities, albeit again relying on triple store data. Cubix, the final prototype of the CUBIST project, incorporated the approaches of Dau and Orphanides in an interactive web frontend.
FcaBedrock is an Open-source software (OSS) developed as part of this study, employing a series of steps to appropriate data for FCA in a semi-automated, user-driven environment. To underpin this work, we take a case
study approach, using two case studies in particular: the UCI Machine Learning (ML) Repository—a dataset repository for the empirical analysis of machine learning algorithms—and the e-Mouse Atlas of Gene Expression (EMAGE), a
database of anatomical terms for each Theiler Stage (TS) in mouse development. We compare our approach with existing approaches, using datasets from the two case studies. The appropriation of the datasets become an integral part of
our evaluation, providing the real-life context and use-cases of our proposed approach.
The UCI ML Repository and EMAGE case studies revealed how prior to this study, a multitude of existing data sources, types and formats, were either not accessible, or not easily accessible to FCA; the data appropriation processes were in most cases tedious and time-consuming, often requiring the
manual creation of formal contexts out of datasets. In other cases, rigid, non-flexible approaches were developed, with hardcoded assumptions made about the underlying use-case they were developed for. This is unlike the software
and techniques developed in this study, where the same semi-automated steps can consistently facilitate the appropriation of data for FCA, from the most common data sources and their underlying data types.
The aim of this study was to discover how effective each FCA approach is in appropriating data for FCA, answering the research question: “How can data from structured sources, consisting of various data types, be acquired
and appropriated for FCA in a semi-automated, user-driven environment?”. FcaBedrock emerged as the best appropriation approach, by abstracting the issue of structured sources away using the ubiquitous CSV (Comma Separated Value) file format as an input source and by providing both automated and semi-automated means of creating meaningful formal contexts from a dataset. Dau’s CUBIST scalingless approach, while semi-automated, was restricted to RDF triple stores and did not provide any flexibility as to how each attribute
of the dataset should be interpreted. Orphanides’s CUBIST scaleful approach, while providing more flexibility with its scaling capabilities, was again restricted to RDF triple stores. The CUBIST interactive approach improved upon those
ideas, by allowing the user to drive the analysis via a user-friendly web frontend. ToscanaJ was restricted to only using SQL/NoSQL databases as an input source, while both ToscanaJ and ConExp provided no substantial appropriation
techniques other than creating a formal context by hand
Exploring the applicability of formal concept analysis on Market Intelligence data
No full textThis paper examines and identifies issues associated with the applicability of FCA on sample data provided by a CUBIST use-case partner. The paper explains the various steps related to the transformation of these data to formal contexts, such as preprocessing, cleansing and simplification, as well as preprocessing and limitation issues, by us-ing two FCA tools currently being developed in CUBIST, FcaBedrock and InClose. The paper demonstrates what is achievable to date, using the above-mentioned tools and what issues need to be considered to achieve more meaningful and intuitive FCA analyses. The paper con-
cludes by suggesting and explaining techniques and features that should be implemented in later iterations of these tools, to deal with the identified barriers. This work has been carried out as a part of the European
CUBIST FP7 Project: http://www.cubist-project.e
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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