Semistructured Data

This paper explores seventeen Icelandic teachers' perspectives and strategies for supporting the plurilingual development of children from first-generation immigrant families attending compulsory schools in Iceland. The data emerges from a large-scale qualitative research project entitled "Language policies and practices of diverse immigrant families in Iceland and their implications for education". The study's theoretical framework utilises multicultural education theory and the scholarship on culturally and linguistically sustaining pedagogies. The analytical process was conducted concurrently throughout the research period, employing qualitative procedures of thematic content analysis, coding, and cross-comparison of data. The findings indicate that despite the strong foundations of inclusivity, equality, and sustainability outlined in the Icelandic national curriculum guide and legal documents, there is a lack of clear language policies at the school level. Whilst the participating teachers acknowledge the importance of plurilingualism, their teaching methods and perspectives often remain at a surface level, prioritising the development of Icelandic over a deeper engagement with students' full linguistic repertoires. Therefore, this study emphasises the need for a broader range of professional development opportunities to enhance teachers' abilities to support cultural and linguistic diversity in compulsory schools in Iceland.

Una ricerca a integrazione delle conoscenze sul lessico dei gessai in Sicilia (Castiglione 2012) mi ha condotto ad approfondire alcuni momenti del processo ergologico, in particolare quello relativo alle fasi del fuoco. A tal fine, sono stati individuati due gessai, testimoni diretti di un lavoro ormai scomparso, i quali operavano l'uno a Raffadali (Ag) e l'altro a Castrofilippo (Ag)-sebbene favarese di origine-i quali hanno fornito un resoconto completo dell'ambiente e delle procedure relativi al mondo del gesso [1]. Un'ulteriore inchiesta condotta a Canicattì ha permesso di individuare il figlio di un gessaio, il quale ha fornito un'ampia mole di dati lessicali.

An ad hoc data source is any semistructured data source for which useful data analysis and transformation tools are not readily available. Such data must be queried, transformed and displayed by systems administrators, computational biologists, financial analysts and hosts of others on a regular basis. In this paper, we demonstrate that it is possible to generate a suite of useful data processing tools, including a semi-structured query engine, several format converters, a statistical analyzer and data visualization routines directly from the ad hoc data itself, without any human intervention. The key technical contribution of the work is a multiphase algorithm that automatically infers the structure of an ad hoc data source and produces a format specification in the PADS data description language. Programmers wishing to implement custom data analysis tools can use such descriptions to generate printing and parsing libraries for the data. Alternatively, our software infrastructure will push these descriptions through the PADS compiler, creating format-dependent modules that, when linked with formatindependent algorithms for analysis and transformation, result in fully functional tools. We evaluate the performance of our inference algorithm, showing it scales linearly in the size of the training data -completing in seconds, as opposed to the hours or days it takes to write a description by hand. We also evaluate the correctness of the algorithm, demonstrating that generating accurate descriptions often requires less than 5% of the available data.

Semistructured data is now widely used in both web applications and database systems. Much of the research into this area defines algorithms that transform the data and schema, such as data integration, change management, view definition, and data normalization. While some researchers have defined a formalism for the work they have undertaken, there is no widely accepted formalism that can be used for the comparison of algorithms within these areas. The requirements of a formalism that would be helpful in these situations are that it must capture all the necessary semantics required to model the algorithms, it should not be too complex and it should be easy to use. This paper describes a first step in defining such a formalism. We have modelled the semantics expressed in the ORA-SS (Object Relationship Attribute data model for SemiStructured data) data modelling notation in two formal languages that have automatic verification tools. We compare the two models and present the findings.

Semistructured data is typically represented using XML. However, little semantic information can be captured using XML. Other data models, such as the Object Relationship Attribute data model for Semistructured data (ORA-SS), have been introduced to represent more detailed semantic information. Automatic analysis of the data models would enable us to reveal inconsistencies both at the schema and instance levels of the semistructured data. The aim of this paper is to encode the semantics of the ORA-SS data model in the Alloy formal language and automatically validate the semistructured data design using the Alloy Analyzer. It enables us to check the consistency of an ORA-SS schema and its instances.

Semistructured data has become prevalent with the growth of the Internet. The development of new web applications that require efficient design and maintenance of large amounts of data makes it increasingly important to design "good" semistructured databases to prevent data redundancy and updating anomalies. However, it is not easy, even impossible, for current semistructured data models to capture the semantics traditionally needed for designing databases. In this paper, we show how an Object-Relationship-Attribute model for SemStructured data (ORA-SS) can facilitate the design of "good" semistructured databases. This is accomplished via the normalization of ORA-SS. An XML DTD or Schema generated from a normal form ORA-SS schema diagram has no undesirable redundancy, and thus no updating anomalies for the complying semistructured databases. The general design methodology and detailed steps for converting an ORA-SS schema diagram into a normal form ORA-SS schema diagram are presented. These steps can also be used as guidelines for designing semistructured databases using the ORA-SS model.

The rapid growth of the World Wide Web has resulted in a dramatic increase in semistructured data usage, creating a growing need for effective and efficient utilization of semistructured data. In order to verify the correctness of semistructured data design, precise descriptions of the schemas and transformations on the schemas must be established. One effective way to achieve this goal is through formal modeling and automated verification. This paper presents the first step towards this goal. In our approach, we have formally specified the semantics of the ORA-SS (Object-Relationship-Attribute data model for Semistructured data) data modeling language in PVS (Prototype Verification System) and provided automated verification support for both ORA-SS schemas and XML (Extensible Markup Language) data instances using the PVS theorem prover. This approach provides a solid basis for verifying algorithms that transform schemas for semistructured data.

The rapid growth of the World Wide Web has resulted in a dramatic in- crease in semistructured data usage, creating a growing need for effective and efficient utilization of semistructured data. In order to verify the correctness of semistructured data design, precise descriptions of the schemas and transformations on the schemas must be established. One effective way to achieve this goal is through formal model- ing and automated verification. This paper presents the first step towards this goal. In our approach, we have formally specified the semantics of the ORA-SS (Object- Relationship-Attribute data model for Semistructured data) data modeling language in PVS (Prototype Verification System) and provided automated verification support for both ORA-SS schemas and XML (Extensible Markup Language) data instances using the PVS theorem prover. This approach provides a solid basis for verifying algo- rithms that transform schemas for semistructured data.

Existing systems that support semistructured views do not maintain semantics during the process of designing the views. Thus, these systems do not guarantee the validity and reversibility of the views. In this paper, we propose an approach to address the issue of valid and reversible semistructured views. We design a set of view operators for designing semistructured views. These operators are select, drop, join and swap. For each operator, we develop a complete set of rules to maintain the semantics of the views. In particular, we maintain the evolution and integrity of relationships once an operator is applied. We also examine the reversible view problem under our operators and develop rules to guarantee that the designed views are reversible. Finally, we examine the changes in the participation constraints of relationship types during the view design process, and develop rules to ensure the correctness of the participation constraints.

Semistructured data has become prevalent with the growth of the Internet. The development of new web applications that require efficient design and maintenance of large amounts of data makes it increasingly important to design "good" semistructured databases to prevent data redundancy and updating anomalies. However, it is not easy, even impossible, for current semistructured data models to capture the semantics traditionally needed for designing databases. In this paper, we show how an Object-Relationship-Attribute model for SemStructured data (ORA-SS) can facilitate the design of "good" semistructured databases. This is accomplished via the normalization of ORA-SS. An XML DTD or Schema generated from a normal form ORA-SS schema diagram has no undesirable redundancy, and thus no updating anomalies for the complying semistructured databases. The general design methodology and detailed steps for converting an ORA-SS schema diagram into a normal form ORA-SS schema diagram are presented. These steps can also be used as guidelines for designing semistructured databases using the ORA-SS model.

Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool -RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels.

Semistructured data is typically represented using XML. However, little semantic information can be captured using XML. Other data models, such as the Object Relationship Attribute data model for Semistructured data (ORA-SS), have been introduced to represent more detailed semantic information. Automatic analysis of the data models would enable us to reveal inconsistencies both at the schema and instance levels of the semistructured data. The aim of this paper is to encode the semantics of the ORA-SS data model in the Alloy formal language and automatically validate the semistructured data design using the Alloy Analyzer. It enables us to check the consistency of an ORA-SS schema and its instances.

Semistructured data is becoming increasingly important for web applications with the development of XML and related technologies. Designing a "good" semistructured database is crucial to prevent data redundancy, inconsistency and undesirable updating anomalies. However, unlike relational databases, there is no normalization theory to facilitate the design of good semistructured databases. In this paper, we introduce the notion of a semistructured schema and identify the various anomalies that may occur in such a schema. A Normal Form for Semistructured Schemata, NF-SS, is proposed. A semistructured schema in NF-SS guarantees minimal redundancy and hence no undesirable updating anomalies for the associated semistructured databases. Furthermore, a semistructured schema in NF-SS gives a more reasonable representation of real world semantics. We develop an iterative algorithm based on a set of heuristic rules to restructure a semistructured schema into a normal form. These design methods also provide insights into the normalization task for semistructured databases.

Semistructured data is now widely used in both web applications and database systems. Much of the research into this area defines algorithms that transform the data and schema, such as data integration, change management, view definition, and data normalization. While some researchers have defined a formalism for the work they have undertaken, there is no widely accepted formalism that can be used for the comparison of algorithms within these areas. The requirements of a formalism that would be helpful in these situations are that it must capture all the necessary semantics required to model the algorithms, it should not be too complex and it should be easy to use. This paper describes a first step in defining such a formalism. We have modelled the semantics expressed in the ORA-SS (Object Relationship Attribute data model for SemiStructured data) data modelling notation in two formal languages that have automatic verification tools. We compare the two models and present the findings.

The dramatic expansion of semistructured data has led to the development of database systems for manipulating the data. Despite its huge potential, there is still a lack of formality and verification support in the design of good semistructured databases. Like traditional database systems, developed semistructured database systems should contain minimal redundancies and update anomalies, in order to store and manage the data effectively. Several normalization algorithms have been proposed to satisfy these needs, by transforming the schema of the semistructured data into a better form. It is essential to ensure that the normalized schema remains semantically equivalent to its original form. In this paper, we present tool support for reasoning about the correctness of semistructured data normalization. The proposed approach uses the ORA-SS data modeling notation and defines its correctness criteria and rules in the PVS formal language. It further utilizes the PVS theorem prover to perform automated checking on the normalized schema, checking that functional dependencies are preserved, no data is lost and no spurious data is created. In summary, our approach not only investigates the characteristics of semistructured data normalization, but also provides a scalable and automated first step towards reasoning about the correctness of normalization algorithms on semistructured data.

Semistructured data is now widely used in both web applications and database systems. There are many research challenges in this area, such as data integra- tion, change management, view definition, and data normalization. Traditionally in these areas a formal- ism is defined for the database model, and properties of the algorithms can be reasoned about, such as the dependency preserving property of the normalization algorithm in the relational data model. Because re- search into semistructured data is still in its infancy, many algorithms have been defined in this area and a number of formalisms have been proposed but there is no widely accepted formalism that is generally ac- cepted to reason about the properties of the algo- rithms. Such a formalism must capture all the nec- essary semantics required to model the algorithms, should not be too complex, and should be easy to use. Another area that has been developing steadily is automatic verification. This involves formally speci-...

The rapid growth of the World Wide Web has resulted in more data being accessed over the Internet. In turn there is an increase in the use of semistructured data, which plays a crucial role in many web applications particularly with the introduction of XML and its related technologies. This increase in use makes the design of good semistructured data structures essential. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. In this paper, we demonstrate an approach to formally validate the ORA-SS data models in order to enhance the correctness of semistructured data design. A mathematical semantics for the ORA-SS notation is defined using the Z formal language, and further validation processes are carried out to check the correctness of the semistructured data models at both the schema and instance levels.

Semi-structured data is becoming increasingly important with the introduction of XML and related languages and technologies. The recent shift from DTDs (document type de nitions) to XML-Schema for XML data highlights the importance of a schema de nition for semi-structured data ...

The rapid increase in semistructured data usage has lead to the development of various database systems for semistructured data. Web services and applications that utilize large amounts of semistructured data require data to remain consistent and be stored efficient. Several normalization algorithms for semistructured database systems have been developed to satisfy these needs. However, these algorithms lack the verification that would ensure that data and constraints among the data are not lost or corrupted during normalization. In this paper, we propose a set of correctness criteria for normalization of semistructured data, which require that functional dependencies are preserved, data is not lost, and spurious data is not created during normalization. We use the Z specification language to provide a precise and declarative definition of our criteria.

XML is a rather verbose representation of semistructured data, which may require huge amounts of storage space. We propose a summarized representation of XML data, based on the concept of instance pattern, which can both provide succinct information and be directly queried. The physical representation of instance patterns exploits itemsets or association rules to summarize the content of XML datasets. Instance patterns may be used for (possibly partially) answering queries, either when fast and approximate answers are required, or when the actual dataset is not available, for example, it is currently unreachable. Experiments on large XML documents show that instance patterns allow a significant reduction in storage space, while preserving almost entirely the completeness of the query result. Furthermore, they provide fast query answers and show good scalability on the size of the dataset, thus overcoming the document size limitation of most current XQuery engines.

While most business applications typically operate on structured data that can be effectively managed using relational databases, some applications use more complex semistructured data that lacks a stable schema. XML techniques are available for the management of semistructured data, but such techniques tend to be ineffective when applied to large amounts of heterogeneous data, in particular in applications with complex query requirements. In this paper we describe an approach that relies on the mapping of multiple semistructured data sets to objectrelational structures and uses an object-relational database to support complex query requirements. We illustrate this approach using weakly heterogeneous oceanographic data.

Temporal XML is a timestamped instance of an XML data model or, more literally, an XML document in which specially-interpreted timestamps are present. In general an XML data model instance is a tree or graph in which each node corresponds to an element, attribute, or value, and each edge represents the lexical nesting of the child in the parent's content. In temporal XML, a timestamp is added to some nodes or edges in the instance. The timestamp represents the lifetime of the node or edge in one or more temporal dimensions, usually valid time or transaction time. As an example, Figure 1 shows a fragment of a temporal XML data model. The bibliographic data in the figure contains information about publishers, books, and authors. The figure also has timestamps that represent when each piece of data was entered into the data collection (i.e., the timestamps represent the transaction-time lifetime of each element). The bibliography began on 12/21/01, and remains current (until now). Information about the Butterfly Books publisher was entered on 1/1/04, and it started publishing a book by Jane Austen on 2/2/04. The title of that book was originally misspelled, but was corrected on 5/29/05. Alternatively, temporal XML is literally an XML document or data collection in which specially-interpreted timestamps, formatted in XML, are included. Such a document yields a temporal XML data model instance when parsed.

Motivated to a large extent by the substantial and growing prominence of the WorldWide Web and the potential benefits that may be obtained by applying database concepts and techniques to web data management, new data models and query languages have emerged that contend with web data. These models organize data in graphs where nodes denote objects or values and edges are labeled with single words or phrases. Nodes are described by the labels of the paths that lead to them, and these descriptions serve as the basis for querying. This paper proposes an extensible framework for capturing and querying meta-data properties in a semistructured data model. Properties such as temporal aspects of data, prices associated with data access, quality ratings associated with the data, and access restrictions on the data are considered. Specifically, the paper defines an extensible data model and an accompanying query language that provides new facilities for matching, slicing, collapsing, and coalescing properties. It also briefly introduces an implemented, SQLlike query language for the extended data model that includes additional constructs for the effective querying of graphs with properties.

We describe a configurable tool for extracting semistructured data from a set of HTML pages andfor converting the extracted information into database objects. The input to the extractor is adeclarative specification that states where the data of interest is located on the HTML pages, andhow the data should be packaged into objects. We have implemented the Web extractor usingthe Python programming language stressing efficiency and ease-of-use. We also describe variousways of improving the functionality of our current prototype. The ...

This paper proposes an approach for representing and querying semistructured Web data, which is based on nested tables allowing internal nested structural variations. Our motivation is to reduce the complexity found in typical query languages for semistructured data and to provide users with an alternative for quickly querying data obtained from multiple-record Web pages. We show the feasibility of our proposal by developing a prototype for a graphical query interface called QSByE (Querying Semistructured data By Example), which implements a set of QBE-like operations that extends typical nested-relational-algebra operations to handle semistructured data.

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This paper is about a special version of PDL, designed by Marcus Kracht for reasoning about sibling ordered trees. It has four basic programs corresponding to the child, parent, left-and right-sibling relations in such trees. The original motivation for this language is rooted in the field of model-theoretic syntax. Motivated by recent developments in the area of semistructured data, and, especially, in the field of query languages for XML (eXtensible Markup Language) documents, we revisit the language. This renewed interest comes with a special focus on complexity and expressivity aspects of the language, aspects that have so far largely been ignored. We survey and derive complexity results, and spend most of the paper on the most important open question concerning the language: what is its expressive power? We approach this question from two angles: Which first order properties can be expressed? And which second order properties? While we are still some way from definitive answers to these questions, we discuss two first order fragments of the PDL language for ordered trees, and show how the language can be used to express some typical (second order) problems, like the boolean circuit and the frontier problem.

Introduction. Social Semantic software, for example Semantik Wikis, combines collaborative work and social interaction between users with Semantic Web technologies. Reasoning, seen as the generation of new data from declarative specifications, and querying, seen as high-level and declarative access and data construction, are distinguishing features of Semantic software. In order to benefit non-expert users of social software, both technologies should be easy to use while at the same time providing expressive power to advanced users. ...

The paper presents the development of a virtual database for the genotypic selection of cereal cultivars starting from phenotypic traits. The database is realized by integrating two existing web databases, Gramene 1 and Graingenes 2 , and a pre-existing data source developed by the Agrarian Faculty of the University of Modena and Reggio Emilia. The integration process gives rise to a virtual integrated view of the underlying sources. This integration is obtained using the MOMIS system (Mediator envirOnment for Multiple Information Sources), a framework developed by the Database Group of the University of Modena and Reggio Emilia (www.dbgroup.unimo.it). MOMIS performs information extraction and integration from both structured and semistructured data sources. Information integration is performed in a semi-automatic way, by exploiting the knowledge in a Common Thesaurus (defined by the framework) and the descriptions of source schemas with a combination of clustering and Description Logics techniques. Momis allows querying information in a transparent mode for the user regardless of the specific languages of the sources. The result obtained by applying MOMIS to Gramene and Graingenes web databases is a queriable virtual view that integrates the two sources and allow performing genotypic selection of cultivars of barley, wheat and rice based on phenotypic traits, regardless of the specific languages of the web databases. The project is conducted in collaboration with the Agrarian Faculty of the University of Modena and Reggio Emilia and funded by the Regional Government of Emilia Romagna.

Data integration is the problem of combining data residing at distributed heterogeneous sources, including multimedia sources, and providing the user with a unified view of these data. Ontology based Data Integration involves the use of ontology(s) to effectively combine data and information from multiple heterogeneous sources [16]. Ontologies, with respect to the integration of data sources, can be used for the identification and association of semantically corresponding information concepts, i.e. for the definition of semantic mappings among concepts of the information sources. MOMIS is a Data Integration System which performs information extraction and integration from both structured and semistructured data sources [6]. In [5] MOMIS was extended to manage "traditional" and "multimedia" data sources at the same time. STASIS is a comprehensive application suite which allows enterprises to simplify the mapping process between data schemas based on semantics [1]. Moreover, in STASIS, a general framework to perform Ontology-driven Semantic Mapping has been proposed [7]. This paper describes the early effort to combine the MOMIS and the STASIS frameworks in order to obtain an effective approach for Ontology-Based Data Integration for data and multimedia sources.

Web warehousing plays a key role in providing the managers with up-to-date and comprehensive information about their business domain. On the other hand, since XML is now a standard de facto for the exchange of semi-structured data, integrating XML data into web warehouses is a hot topic. In this paper we propose a semi-automated methodology for conceptual design of web warehouses from XML sources modeled by XML Schemas. In our methodology, conceptual design is carried out by first creating a Schema graph, then navigating the functional dependencies expressed by its arcs in order to derive a correct multidimensional representation. The problem of correctly inferring the needed information is solved by querying the source XML documents and, if necessary, by asking the designer's help. The approach is implemented in a prototype that reads an XML Schema and produces in output the conceptual scheme for the web warehouse.

Finding optimum and near optimum edit scripts between an XML document and a schema is essential to correcting invalid XML documents. In this paper, we consider finding K optimum edit scripts between an XML document and a regular tree grammar. We first prove that the problem is NP-hard. We next show a pseudopolynomial-time algorithm for solving the problem.

In this paper, we present, to our knowledge, the first known I/O efficient solutions for computing the k-bisimulation partition of a massive directed graph, and performing maintenance of such a partition upon updates to the underlying graph. Ubiquitous in the theory and application of graph data, bisimulation is a robust notion of node equivalence which intuitively groups together nodes in a graph which share fundamental structural features. kbisimulation is the standard variant of bisimulation where the topological features of nodes are only considered within a local neighborhood of radius k 0. The I/O cost of our partition construction algorithm is bounded by O(k • sort (|Et|) + k • scan(|Nt|) + sort (|Nt|)), while our maintenance algorithms are bounded by O(k • sort (|Et|) + k • sort (|Nt|)). The space complexity bounds are O(|Nt| + |Et|) and O(k • |Nt| + k • |Et|), resp. Here, |Et| and |Nt| are the number of disk pages occupied by the input graph's edge set and node set, resp., and sort (n) and scan(n) are the cost of sorting and scanning, resp., a file occupying n pages in external memory. Empirical analysis on a variety of massive real-world and synthetic graph datasets shows that our algorithms perform efficiently in practice, scaling gracefully as graphs grow in size.

Building large Web sites is similar in many ways to building knowledge and database systems. In particular, by providing a declarative, logical view of a Web site's data and structure, many of a site builder's tasks, such as creating complex sites, modifying a site's structure, and creating multiple versions of a site, are simplified significantly. New systems, such aS STRUDEL, support logical views of Web sites by allowing site builders to construct a site declaratively. In this paper, we address an important problem for site builders: verifying that a Web site's structure conforms to certain constraints. Specifically, we consider the problem of verifying that a Web site created declaratively by STRUDEL satisfies certain integrity constraints, such as 'all pages are reachable from the root' and 'every organization page points to its suborganizations', etc. Our contributions are (1) formulating the verification problem as an entailment problem in a logical setting, and (2) presenting a sound and complete algorithm for verifying large classes of integrity constraints that occur in practice. Our algorithm uses a novel data structure, the site schema, which enables us to identify cases in which the general reasoning problem reduces to a decidable problem.

In this paper, we proposed a new approach, called FiVaTech for the problem of Web data extraction. FiVaTech is a page-level data extraction system which deduces the data schema and templates for the input pages generated from a CGI program. FiVaTech uses tree templates to model the generation of dynamic Web pages. FiVaTech can deduce the schema and templates for each individual Deep Web site, which contains either singleton or multiple data records in one Web page. FiVaTech applies tree matching, tree alignment, and mining techniques to achieve the challenging task. The experiments show an encouraging result for the test pages used in many state-of-the-art Web data extraction works.

We develop an algorithmic framework to decompose a collection of time-stamped text documents into semantically coherent threads. Our formulation leads to a graph decomposition problem on directed acyclic graphs, for which we obtain three algorithms-an exact algorithm that is based on minimum cost flow and two more efficient algorithms based on maximum matching and dynamic programming that solve specific versions of the graph decomposition problem. Applications of our algorithms include superior summarization of news search results, improved browsing paradigms for large collections of text-intensive corpora, and integration of time-stamped documents from a variety of sources. Experimental results based on over 250,000 news articles from a major newspaper over a period of four years demonstrate that our algorithms efficiently identify robust threads of varying lengths and time-spans.

In the last few years an interest in native XML databases has surfaced. With other authors we argue that such databases need their own provisions for concurrency control since traditional methods are inadequate to capture the complicated update-behavior that is possible for XML documents. Ideally, updates should not be limited to entire document trees, but should involve subtrees and even individual elements. Providing a suitable scheduling algorithm for semistructured data can significantly improve collaborative systems that store ...

One of the most common datasets used by many corporations to gain business intelligence is event log files. Oftentimes, the records in event log files are temporally ordered, and need to be grouped by user ID with the temporal ordering preserved to facilitate mining user behaviors. This kind of analytical workload, here referred to as RElative Order-pReserving based Grouping (RE-ORG), is quite common in big data analytics. Using MapReduce/Hadoop for executing RE-ORG tasks on ordered datasets is not efficient due to its internal sort-merge mechanism. In this paper, we propose a distributed framework that adopts an efficient group-ordermerge mechanism to provide faster execution of RE-ORG tasks. We demonstrate the advantage of our framework by comparing its performance with Hadoop through extensive experiments on real-world datasets. The evaluation results show that our framework can achieve up to 6.3x speedup over Hadoop in executing RE-ORG tasks.

In this paper, we will deal with quantitative and qualitative data collected throughout the last quarter of the 20th century in Sicily. We will focus on the mapping of the latest sociolinguistic results obtained by means of an ample investigation, and then included in the Linguistic Atlas of

In a scenario with "traditional" and "multimedia" data sources, this position paper discusses the following question: "How can a multimedia local source (e.g., Windsurf) supporting ranking queries be integrated into a mediator system without such capabilities (e.g., MOMIS)?" More precisely, "How to support ranking queries coming from a multimedia local source within a mediator system with a "traditional" query processor based on an SQL-engine?" We first describe a naïve approach for the execution of range and Top-K global queries where the MOMIS query processing method remains substantially unchanged, but, in the case of Top-K queries, it does not guarantee to obtain K results. We then discuss two alternative modalities for allowing MOMIS to return the Top-K best results of a global query. ⋆ An open source version of the MOMIS system is delivered by the academic UNIMORE spin-off DataRiver (www.datariver.it); this work is developed in the context of the "DataRiver Data Integrator" project, funded to DataRiver by the Italian Ministry of Economic Development, "Fondo per l'Innovazione Tecnologica-FIT Start-Up".

There are many database applications that require users to coordinate and communicate. Friends want to coordinate travel plans, students want to jointly enroll in the same set of courses, and busy professionals want to coordinate their schedules. These tasks are difficult to program using existing abstractions provided by database systems because in addition to the traditional ACID properties provided by the system they all require some type of coordination between users. This is fundamentally incompatible with isolation in the classical ACID properties. In this position paper, we argue that it is time for the database community to look beyond isolation towards principled and elegant abstractions that allow for communication and coordination between some notion of (suitably generalized) transactions. This new area of declarative data-driven coordination (D3C) is motivated by many novel applications and is full of challenging research problems. We survey existing abstractions in data...

We present an architecture to coordinate the construction of the context within which meaningful information between heterogeneous information systems can be exchanged. We call this coordinator SCOPES (Semantic Coordinator Over Parallel Exploration Spaces). A classification of semantic conflicts we proposed elsewhere is used to build and refine the context, by discovering the semantic mapping rules (inter-schema correspondence assertions) between corresponding elements of the communicating systems. A truth maintenance system is used to manage the multiple intermediate contexts. It provides a mechanism to infer or retract assertions on the basis of the knowledge acquired during the reconciliation process. This nonmonotonic technique is used in conjunction with the Dempster-Shafer theory of belief functions to model the likelihood of alternative contexts. Finally, we propose an algorithm which illustrates how the various components of the architecture interact with one another in order to build context.

Now that the use of XML is prevalent, methods for mining semi-structured documents have become even more important. In particular, one of the areas that could greatly benefit from in-depth analysis of XML's semi-structured nature is cluster analysis. Most of the XML clustering approaches developed so far employ pairwise similarity measures. In this paper, we study clustering algorithms, which use patterns to cluster documents without the need for pairwise comparisons. We investigate the shortcomings of existing approaches and establish a new pattern-based clustering framework called XPattern, which tries to address these shortcomings. The proposed framework consists of four steps: choosing a pattern definition, pattern mining, pattern clustering, and document assignment. The framework's distinguishing feature is the combination of pattern clustering and document-cluster assignment, which allows to group documents according to their characteristic features rather than their direct similarity. We experimentally evaluate the proposed approach by implementing an algorithm called PathXP, which mines maximal frequent paths and groups them into profiles. PathXP was found to match, in terms of accuracy, other XML clustering approaches, while requiring less parametrization and providing easily interpretable cluster representatives. Additionally, the results of an in-depth experimental study lead to general suggestions concerning pattern-based XML clustering.