XML Elements Research Articles

Better than XML: Towards a lexicographic markup language

This article takes a critical look at how XML is used in lexicography and asks the question, why do dictionary entries often end up looking so complex when encoded in XML? The main reason for the perceived complexity of XML-encoded dictionaries is purely structural markup: XML elements which contain other XML elements instead of human-readable text. The over-abundance of purely structural markup in lexicography is caused by the nature of lexicographic content, much of which is inherently headed. XML has no support for headedness and neither do other commonly used languages such as JSON and YAML. In this article we propose a number of constraints and extensions to XML, JSON and YAML which add support for headedness into these languages.

Syntactical method for reconstructing highly fragmented OOXML files

A common task in computer forensics is to recover files that lack file system metadata. In the case of searching for file fragments in unallocated space, file carving is the most often used method, which is ideal for unfragmented data. However, such methods and the tools based on them are ineffective for recovering OOXML files with a high fragmentation level. These methods do not provide reliable determination of the correct order of fragments. Techniques for reconstructing documents based on the analysis of words and phrases are also ineffective in fragmented OOXML documents. The main reason is that OOXML files are ZIP archives and, as a result, store data on disk space in a compressed form. This paper proposes a syntactical method for reconstructing OOXML documents based on knowledge about the internal structure of this file type, regardless of their content. The details of the implementation of the reconstruction algorithm and the peculiarities of restoring certain types of local elements of the document were considered. The efficiency of the algorithm was tested on the Govdocs1 and NapierOne datasets. The proposed method was applied to 4096-byte data blocks, which correspond to the standard cluster size in different file systems. The experimental results confirmed the method's suitability for practical use with 82.97 % of recovered files, including 34.38 % reconstructed completely, 0.43 % excluding the last 21 bytes at most, and another 48.16 % excluding embeddings that require other approaches. In the latter case, obtaining a fully working document without displaying graphic images and other contents of different embeddings is possible. The presence in OOXML files of CRC-32 hashes of the uncompressed data stream of each local element allows us to confirm the correctness of information recovery and its integrity unambiguously. Simultaneously, the method's effectiveness depends mainly on data verification methods during the reconstruction of local elements that occupy at least three clusters in the file. Therefore, this method is supposed to be improved by developing new mechanisms for verifying XML elements.

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying

Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. Yet, few of the existing approaches consider XML semantics, and the methods that process semantics generally rely on computationally expensive word sense disambiguation (WSD) techniques, or apply semantic analysis in one stage only: performing query relaxation/refinement over the bag of words retrieval model, to reduce processing time. In this paper, we describe a new approach for XML keyword search aiming to solve the limitations mentioned above. Our solution first transforms the XML document collection (offline) and the keyword query (on-the-fly) into meaningful semantic representations using context-based and global disambiguation methods, specially designed to allow almost linear computation efficiency. We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. Experimental results highlight the quality and potential of our approach.

Information Design for Small Screens: Toward Smart Glass Use in Guidance for Industrial Maintenance

<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Background:</b> Smart glasses and other extended reality (XR) solutions provide new ways of utilizing technical documentation with hands-busy tasks in the field. Scaling up the use of XR solutions in industry has been difficult due to the manual authoring of content for each device and task. Therefore, authoring solutions and information design methods need to be developed to scale content automatically to different devices and applications. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Literature review:</b> Related work includes smart glasses and industrial maintenance work, categorization based on users' skill levels, and standardized guidelines in information design. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research questions:</b> 1. How should information content be designed and created to support use in smart glasses and other small-screen devices in addition to existing delivery channels? 2. How can the same information content be utilized to deliver relevant content to users based on their skill levels? 3. Are the users of technical instructions ready to accept smart glasses and XR as a delivery channel? <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methodology:</b> We describe a study that focused on designing maintenance instructions for small screens. The information was authored in DITA XML format, and a smart glass application was used in user tests to evaluate the delivery and usability of the information. We used thinking aloud and participant observation as well as questionnaires to collect data. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results and discussion:</b> The chosen information design methods successfully compressed technical information, and automatic filtering of content supported different use cases. Participants were enthusiastic about the use of smart glasses, and the instructions helped in performing tasks. <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusions:</b> Information designed with the user-centered approach of minimalism works best with instructions on small screens, and filtering information using DITA XML elements is an efficient way to scale information for different user needs.

Crossref 4.4.2 XML Elements and Attributes

For anyone trying to understand both the basics and the full range of options available when making a DOI metadata submission to Crossref, this linked table of XML element and attribute descriptions gives one small publisher’s best understanding of the most recent version of Crossref’s metadata submission elements and attributes. As of April 2021, the most recent version of Crossref XML files is 4.4.2. This table provides definitions for the six Crossref XML Schema Definition (xsd) files that include the most commonly used description elements of a DOI submission: crossref4.4.2.xsd, common4.4.2.xsd, fundref.xsd, AccessIndicators.xsd, clinicaltrials.xsd, and relations.xsd. The table also includes a brief description of the main features of the externally defined jats:abstract (JATS) element. This table focuses not on XML syntax but on the intent and structure of the elements from a small publisher perspective. This table is one small publisher’s interpretation of Crossref XML and is not authoritative in any way. It will inevitably contain errors, and the author takes no responsibility for its use, which is necessarily and entirely at your own risk. Any submissions created with information from this table should be verified for correctness against the official automated documentation and tools at the Crossref submission site. Note, however, that occasional errors and inconsistencies in those Crossref XML files were uncovered during the creation of this table. Every effort has been made here both to document inconsistencies in the original files and in this interpretation of those files. Important links to Crossref documentation, including comment on the apparent status of Crossref web pages, are provided in the References section after the table on the last document page.

Mapping XML to RDF: An algorithm based on element classification and aggregation

Many data in Web are exchanged and stored in XML. RDF achieves rapid response and reasoning by aggregating a large amount of knowledge. It has been widely used in intelligent field as a way of data organization. Building RDF based on XML is the focus of this article. This paper analyzes the tree structure of XML, divides the XML elements into three sub-models according to the structure, then aggregates and classifies XML elements, and abstracts the aggregates into three abstract structure models, and finally proposes related mapping rules. Based on the optimization of existing methods, this paper proposes an XML-to-RDF mapping algorithm based on element classification and aggregation, which is reflected in three aspects: optimized mapping rules to ensure the completeness and accuracy of data content and semantics; proposed general algorithms for different types of XML; identified equivalent elements of XML and solved the problem of RDF data redundancy caused by such equivalent elements.

JATS4R - working together to apply the standard standardly

JATS4R is a volunteer-run organisation that produces recommendations for how people should use the Journal Article Tag Suite (JATS XML) to aid the exchange, reuse, and mining of content. This paper briefly describes this overlay to the NISO Standard Z39.96-2019 which itself defines a set of XML elements and attributes for tagging journals articles and provides three models. JATS4R brings a level of normalization to the use of the basic standard to ensure interoperability across vendors. This paper discusses what JATS4R does, how the standard is maintained and updated, what the oversight group has achieved since it was established in 2013, and what the future may hold.

Scalable Storage Management Architecture for Common Information Model/Web-Based Enterprise Management Environments

Web-Based Enterprise Management (WBEM) is independent of platforms and managed resources so that it can used to unify storage management. WBEM consists of three components. Common Information Model (CIM) is the main component which utilizes a common data format, language and methodology for collecting and describing storage resources. xml CIM encoding defines the way that represents the CIM classes and instances by XML elements. CIM Operations over HTTP makes CIM operations in an open and standardized environment based on HTTP. In this paper, we propose a novel storage architecture that enhances efficiency of storage management under CIM/WBEM environments namely Scalable Storage Management Architecture (SSMA). SSMA is developed based on OpenPegasus. In addition, SSMA has better delay performance than traditional proxy CIMOM.

ABCD 3.0 Ready to Use

The TDWG standard ABCD (Access to Biological Collections Data task group 2007) was aimed at harmonizing terminologies used for modelling biological collection information and is used as a comprehensive data format for transferring collection and observation data between software components. The project ABCD 3.0 (A community platform for the development and documentation of the ABCD standard for natural history collections) was financed by the German Research Council (DFG). It addressed the transformation of ABCD into a semantic web-compliant ontology by deconstructing the XML-schema into individually addressable RDF (Resource Description Framework) resources published via the TDWG Terms Wiki (https://terms.tdwg.org/wiki/ABCD_2). In a second step, informal properties and concept-relations described by the original ABCD-schema were transformed into a machine-readable ontology and revised (Güntsch et al. 2016). The project was successfully finished in January 2019. The ABCD 3 setup allows for the creation of standard-conforming application schemas. The XML variant of ABCD 3.0 was restructured, simplified and made more consistent in terms of element names and types as compared to version 2.x. The XML elements are connected to their semantic concepts using the W3C SAWSDL (Semantic Annotation for Web Services Description Language and XML Schema) standard. The creation of specialized applications schemas is encouraged, the first use case was the application schema for zoology. It will also be possible to generate application schemas that break the traditional unit-centric structure of ABCD. Further achievements of the project include creating a Wikibase instance as the editing platform, with related tools for maintenance queries, such as checking for inconsistencies in the ontology and automated export into RDF. This allows for fast iterations of new or updated versions, e.g. when additional mappings to other standards are done. The setup is agnostic to the data standard created, it can therefore also be used to create or model other standards. Mappings to other standards like Darwin Core (https://dwc.tdwg.org/) and Audubon Core (https://tdwg.github.io/ac/) are now machine readable as well. All XPaths (XML Paths) of ABCD 3.0 XML have been mapped to all variants of ABCD 2.06 and 2.1, which will ease transition to the new standard. The ABCD 3 Ontology will also be uploaded to the GFBio Terminology Server (Karam et al. 2016), where individual concepts can be easily searched or queried, allowing for better interactive modelling of ABCD concepts. ABCD documentation now adheres to TDWG’s Standards Documentation Standard (SDS, https://www.tdwg.org/standards/sds/) and is located at https://abcd.tdwg.org/. The new site is hosted on Github: https://github.com/tdwg/abcd/tree/gh-pages.

Encoding Textual Variants of the Early Modern Slovenian Poetic Texts in TEI

The paper deals with the problem of encoding the verses and textual variants in the critical edition of Foglar’s Manuscript, a Styrian Baroque hymn book from the mid-eighteenth century. We first show the diplomatic transcript of the verse in selected problematic cases, after which we present the method applied to produce a critical apparatus for approaching textual variants. The base text, i.e. Foglar’s Manuscript, is compared with versions in eight other manuscripts and prints from the eighteenth and early nineteenth centuries. Variants are encoded with XML elements according to the TEI Consortium Guidelines (TEI) as units of the critical apparatus. We highlight some examples of the detailed encoding of rhymes, feet, verse replacements, and textual variants on the spelling, vocabulary and lexical levels of the language. To conclude, we present a number of possibilities for the online display of the electronic diplomatic transcript. The need for the adaptability of these tools to the Slovenian literary tradition is evident.

Named Entity Based Ranking with Term Proximity for XML Retrieval

In this article, an indexing scheme that includes the named entity category for each indexed term is proposed. Based on this, two methods are proposed, one to infer the semantics of an XML element based on its data content, called the confidence value of the element, and the second method computes the proximity scores of the query terms. The confidence value of an element is obtained based on the probability of a named entity category in the data content of the underlying XML element. The proximity score of the query terms measures the proximity and ordering of the query term within an XML element. The article then shows how a ranking function uses the confidence value of an XML element and proximity score to mitigate the impact of higher frequency terms and compute the relevance between a keyword query and an XML fragment. Finally, a keyword search system is introduced and experiments show that the proposed system outperforms existing approaches in terms of search quality and achieve a higher efficiency.

A hybrid logic for XML reference constraints

XML emerged as the (meta) mark-up language for representing, exchanging, and storing semistructured data. The structure of an XML document may be specified either through DTD (Document Type Definition) language or through the specific language XML Schema. While the expressiveness of XML Schema allows one to specify both the structure and constraints for XML documents, DTD does not allow the specification of integrity constraints for XML documents. On the other side, DTD has a very compact notation opposed to the complex notation and syntax of XML Schema. Thus, it becomes important to consider the issue of how to express further constraints on DTD-based XML documents, still retaining the simplicity and succinctness of DTDs. According to this scenario, in this paper we focus on a (as much as possible) simple logic, named XHyb, expressive enough to allow the specification of the most common integrity and reference constraints in XML documents. In particular, we focus on constraints on ID and IDREF(S) attributes, which are the common way of logically connecting parts of XML documents, besides the usual parent-child relationship of XML elements. Differently from other previously proposed hybrid logics, in XHyb IDREF(S) attributes are explicitly expressible by means of suitable syntactical constructors. Moreover, we propose a refinement of the usual graph representation of XML documents in order to represent XML documents in a formal and intuitive way without flatten accessibility through IDREF(S) to the usual parent-child relationship. Model checking algorithms are then proposed, to verify that a given XML document satisfies the considered constraints.

Multi-Query Optimization on RSS Feeds

RSS feeds are text-content rich, semantically heterogeneous, and contain dynamic XML elements streamed in asynchronous and pull strategies. Hence, for efficient retrieval of RSS feeds, semantic-aware querying operators have been proposed in the literature (Getahun and Chbeir in Inf Sci 237(237):313–342, 2013). However, it is commonly admitted that the use of semantic information would improve, on one hand, the relevance of query result but, on the other hand, at the cost of degrading the efficiency and the performance of the system. To benefit from query execution on semantic information while keeping the efficiency of the system, we propose here a multi-query optimization approach for semantic RSS feed queries. Our approach processes queries by examining the semantic relationship between them and their corresponding windows. It generates a multi-query chain for queries using their window relations for faster execution at runtime. In addition, we propose an operator called quickDrop for semantic load shedding to gracefully decrease irrelevant data load. To validate the proposed approach, we developed a prototype and conducted a set of experiments. The obtained results show that the use of our approach significantly improves the performance of the system.

Identifying XML Entities Via Virtual Keys

Since data are acquired from a number of sources, a real-world entity commonly owns multiple formats of representations. Although the heterogeneity issue maintains a prominent concern in data integration and data mining, entity identification is an effective means to solve duplicates. However, the efforts in complicated structures, such as XML data, are not as extensive as the practical relevance that has been explored in the context of relational databases. This article focuses on the duplication detection of XML element based on Sorted Neighbor Method (SNM) and Multi-Pass SNM (MPS). The XEIVK (XML Entities Identification via Virtual Keys) algorithm primarily homogenizes the structures by labels mapping to the template. Subsequently, the virtual keys are created by extracting content of nodes after determining the weight. It calculates the degree of textual similarities in an orchestrated function within a set number of clusters in terms of nodes’ information gain ratio. The experiment illustrates that XEIVK outperforms both SNM and MPS significantly on high precision, meanwhile the less time consuming benefits from the filtering strategies.

Towards a Normal Form and a Query Language for Extended Relations Defined by Regular Expressions

This paper introduces a generalized data base concept that unites relational and semi structured data models. As an important theoretical result we could find a quadratic decision algorithm for the implication problem of functional and join dependencies defined on the united data model. As practical contribution we presented a normal form for the new data model as a tool for data base design. With our novel representations of regular expressions, a more effective searching method could be developed. XML elements are described by XML schema languages such as a DTD or an XML Schema definition. The instances of these elements are semi-structured tuples. A semi-structured tuple is an ordered list of (attribute: value) pairs. We may think of a semi-structured tuple as a sentence of a formal language, where the values are the terminal symbols and the attribute names are the non-terminal symbols. In the authors' former work (Szabó and Benczúr, 2015) they introduced the notion of the extended tuple as a sentence from a regular language generated by a grammar where the non-terminal symbols of the grammar are the attribute names of the tuple. Sets of extended tuples are the extended relations. The authors then introduced the dual language, which generates the tuple types allowed to occur in extended relations. They defined functional dependencies (regular FD - RFD) over extended relations. In this paper they rephrase the RFD concept by directly using regular expressions over attribute names to define extended tuples. By the help of a special vertex labeled graph associated to regular expressions the specification of substring selection for the projection operation can be defined. The normalization for regular schemas is more complex than it is in the relational model, because the schema of an extended relation can contain an infinite number of tuple types. However, the authors can define selection, projection and join operations on extended relations too, so a lossless-join decomposition can be performed. They extended their previous model to deal with XML schema indicators too, e.g., with numerical constraints. They added line and set constructors too, in order to extend their model with more general projection and selection operators. This model establishes a query language with table join functionality for collected XML element data.

Building semantic trees from XML documents

The distributed nature of the Web, as a decentralized system exchanging information between heterogeneous sources, has underlined the need to manage interoperability, i.e., the ability to automatically interpret information in Web documents exchanged between different sources, necessary for efficient information management and search applications. In this context, XML was introduced as a data representation standard that simplifies the tasks of interoperation and integration among heterogeneous data sources, allowing to represent data in (semi-) structured documents consisting of hierarchically nested elements and atomic attributes. However, while XML was shown most effective in exchanging data, i.e., in syntactic interoperability, it has been proven limited when it comes to handling semantics, i.e., semantic interoperability, since it only specifies the syntactic and structural properties of the data without any further semantic meaning. As a result, XML semantic-aware processing has become a motivating challenge in Web data management, requiring dedicated semantic analysis and disambiguation methods to assign well-defined meaning to XML elements and attributes. In this context, most existing approaches: (i) ignore the problem of identifying ambiguous XML elements/nodes, (ii) only partially consider their structural relationships/context, (iii) use syntactic information in processing XML data regardless of the semantics involved, and (iv) are static in adopting fixed disambiguation constraints thus limiting user involvement. In this paper, we provide a new XML Semantic Disambiguation Framework titled XSDFdesigned to address each of the above limitations, taking as input: an XML document, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts extracted from a reference machine-readable semantic network. XSDF consists of four main modules for: (i) linguistic pre-processing of simple/compound XML node labels and values, (ii) selecting ambiguous XML nodes as targets for disambiguation, (iii) representing target nodes as special sphere neighborhood vectors including all XML structural relationships within a (user-chosen) range, and (iv) running context vectors through a hybrid disambiguation process, combining two approaches: concept-basedand context-based disambiguation, allowing the user to tune disambiguation parameters following her needs. Conducted experiments demonstrate the effectiveness and efficiency of our approach in comparison with alternative methods. We also discuss some practical applications of our method, ranging over semantic-aware query rewriting, semantic document clustering and classification, Mobile and Web services search and discovery, as well as blog analysis and event detection in social networks and tweets.

Building Semantic Trees from XML Documents

The distributed nature of the Web, as a decentralized system exchanging information between heterogeneous sources, has underlined the need to manage interoperability, i.e., the ability to automatically interpret information in Web documents exchanged between different sources, necessary for efficient information management and search applications. In this context, XML was introduced as a data representation standard that simplifies the tasks of interoperation and integration among heterogeneous data sources, allowing to represent data in (semi-) structured documents consisting of hierarchically nested elements and atomic attributes. However, while XML was shown most effective in exchanging data, i.e., in syntactic interoperability, it has been proven limited when it comes to handling semantics, i.e., semantic interoperability, since it only specifies the syntactic and structural properties of the data without any further semantic meaning. As a result, XML semantic-aware processing has become a motivating challenge in Web data management, requiring dedicated semantic analysis and disambiguation methods to assign well-defined meaning to XML elements and attributes. In this context, most existing approaches: (i) ignore the problem of identifying ambiguous XML elements/nodes, (ii) only partially consider their structural relationships/context, (iii) use syntactic information in processing XML data regardless of the semantics involved, and (iv) are static in adopting fixed disambiguation constraints thus limiting user involvement. In this paper, we provide a new XML Semantic Disambiguation Framework titled XSDF designed to address each of the above limitations, taking as input: an XML document, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts extracted from a reference machine-readable semantic network. SDF consists of four main modules for: (i) linguistic pre-processing of simple/compound XML node labels and values, (ii) selecting ambiguous XML nodes as targets for disambiguation, (iii) representing target nodes as special sphere neighborhood vectors including all XML structural relationships within a (user-chosen) range, and (iv) running context vectors through a hybrid disambiguation process, combining two approaches: concept-based and context-based disambiguation, allowing the user to tune disambiguation parameters following her needs. Conducted experiments demonstrate the effectiveness and efficiency of our approach in comparison with alternative methods. We also discuss some practical applications of our method, ranging over semantic-aware query rewriting, semantic document clustering and classification, Mobile and Web services search and discovery, as well as blog analysis and event detection in social networks and tweets.

Containment for Conditional Tree Patterns

A Conditional Tree Pattern (CTP) expands an XML tree pattern with labels attached to the descendant edges. These labels can be XML element names or Boolean CTPs. The meaning of a descendant edge labelled by A and ending in a node labelled by B is a path of child steps ending in a B node such that all intermediate nodes are A nodes. In effect this expresses the until B, A holds construction from temporal logic.This paper studies the containment problem for CTP. For tree patterns (TP), this problem is known to be coNP-complete. We show that it is PSPACE-complete for CTP. This increase in complexity is due to the fact that CTP is expressive enough to encode an unrestricted form of label negation: ${*}\setminus a$, meaning "any node except an a-node". Containment of TP expanded with this type of negation is already PSPACE-hard. CTP is a positive, forward, first order fragment of Regular XPath. Unlike TP, CTP expanded with disjunction is not equivalent to unions of CTP's. Like TP, CTP is a natural fragment to consider: CTP is closed under intersections and CTP with disjunction is equally expressive as positive existential first order logic expanded with the until operator.

EDDDS: An Efficient Duplicate Data Detection System

Duplicate Detection is critical task of any database of any organization. Duplicates are nothing but the same real time entities or objects are presented in the form of different structure and in the different formats. We can find out the duplicates in relational data, in complex data and hierarchical data like XML. There are lots of works already presented in the past for finding the duplicates in the relational data. But nowadays there is more focus on finding duplicates in the XML data. Because of XML is very popular for data storing and extensively used for data exchange between the organizations. Here we have done an extensive literature survey on this topic and proposed a duplicate detection method that incorporates some of the existing paper's ideas and some of our original ideas. In addition to improving the efficiency and effectiveness, we also checks for its typographical errors when comparing the two XML elements. To test the correctness of our method, we are comparing it with existing duplicate detection system, and giving more focus on how we get higher precision and recall values in the various datasets we have used.

A Novel Testing Model for SOA based Services

SOA (Service-Oriented Architecture) filled the gap between software and commercial enterprise. SOA integrates multiple web services. We bear to secure the caliber of web services that gives guarantee about what network services work and their output results. There is close to work has to be performed for an automatic test case generation for SOA based services. But, full coverage of XML elements is missing. To the best of our knowledge this all works do not attempt to cover all possible elements of the XML schema presents in the WSDL file. There is also a need to apply different assertions on each service operation for generating the test cases. To overcome this problem we proposed a novel testing model for SOA based application. This new testing model helps us to get the automatic test cases of SOA based application. We build up our new test model with the aid of our proposed test case generation algorithm and test case selection algorithm. In the end, we generate the test suite execution results and find the coverage of XML schema elements present in the WSDL file.