A graph-based meta-model for heterogeneous data management

The wave of interest in data-centric applications has spawned a high variety of data models, making it extremely difficult to evaluate, integrate or access them in a uniform way. Moreover, many recent models are too specific to allow immediate comparison with the others and do not easily support incremental model design. In this paper, we introduce GSMM, a meta-model based on the use of a generic graph that can be instantiated to a concrete data model by simply providing values for a restricted set of parameters and some high-level constraints, themselves represented as graphs. In GSMM, the concept of data schema is replaced by that of constraint, which allows the designer to impose structural restrictions on data in a very flexible way. GSMM includes GSL, a graph-based language for expressing queries and constraints that besides being applicable to data represented in GSMM, in principle, can be specialised and used for existing models where no language was defined. We show some sample applications of GSMM for deriving and comparing classical data models like the relational model, plain XML data, XML Schema, and time-varying semistructured data. We also show how GSMM can represent more recent modelling proposals: the triple stores, the BigTable model and Neo4j, a graph-based model for NoSQL data. A prototype showing the potential of the approach is also described

Operational and abstract semantics of the query language G-Log

The amount and variety of data available electronically have dramatically increased in the led decade; however, data and documents are stored in different ways and do notusual# show their internal structure. In order to take ful advantage of thetopolk9dQ# structure ofdigital documents, andparticulIII web sites, theirhierarchical organizationshouliz explizatio introducing a notion of querysimil; to the one usedin database systems. A good approach, in that respect, is the one provided bygraphical querylrydM#99; original; designed to model object bases and lndd proposed for semistructured data, la, G-Log. The aim of this paper is to providesuitabl graph-basedsemantics to thislisd;BI# supporting both data structure variabil#I andtopol#Ik;M similpol#I between queries and document structures. A suite ofoperational semantics basedon the notion ofbisimulQM#I is introduced both at theconcr--h level (instances) andat theabstru( level (schemata), giving rise to a semantic framework that benefits from the cross-fertil9;dl of tool originalM designed in quite different research areas (databases, concurrency,loncur static analysis)

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

How Much Method-in-Use Matters? A Case Study of Agile and Waterfall Software Projects and their Design Routine Variation

Development methods are rarely followed to the letter, and, consequently, their effects are often in doubt. At the same time, information systems scholars know little about the extent to which a given method truly influences software design and its outcomes. In this paper, we approach this gap by adopting a routine lens and using a novel methodological approach. Theoretically, we treat methods as (organizational) ostensive routine specifications and deploy routine construct as a feasible unit of analysis to analyze the effects of a method on actual, “performed” design routines. We formulated a research framework that identifies method, situation fitness, agency, and random noise as main sources of software design routine variation. Empirically, we applied the framework to examine the extent to which waterfall and agile methods induce variation in software design routines. We trace-enacted design activities in three software projects in a large IT organization that followed an object-oriented waterfall method and three software projects that followed an agile method and then analyzed these traces using a mixed-methods approach involving gene sequencing methods, Markov models, and qualitative content analysis. Our analysis shows that, in both cases, method-induced variation using agile and waterfall methods accounts for about 40% of all activities, while the remaining 60% can be explained by a designer’s personal habits, the project’s fitness conditions, and environmental noise. Generally, the effect of method on software design activities is smaller than assumed and the impact of designer and project conditions on software processes and outcomes should thus not be understated

Semantics and efficient evaluation of partial tree-pattern queries on XML

Current applications export and exchange XML data on the web. Usually, XML data are queried using keyword queries or using the standard structured query language XQuery the core of which consists of the navigational query language XPath. In this context, one major challenge is the querying of the data when the structure of the data sources is complex or not fully known to the user. Another challenge is the integration of multiple data sources that export data with structural differences and irregularities. In this dissertation, a query language for XML called Partial Tree-Pattern Query (PTPQ) language is considered. PTPQs generalize and strictly contain Tree-Pattern Queries (TPQs) and can express a broad structural fragment of XPath. Because of their expressive power and flexibility, they are useful for querying XML documents the structure of which is complex or not fully known to the user, and for integrating XML data sources with different structures. The dissertation focuses on three issues. The first one is the design of efficient non-main-memory evaluation methods for PTPQs. The second one is the assignment of semantics to PTPQs so that they return meaningful answers. The third one is the development of techniques for answering TPQs using materialized views. Non-main-memory XML query evaluation can be done in two modes (which also define two evaluation models). In the first mode, data is preprocessed and indexes, called inverted lists, are built for it. In the second mode, data are unindexed and arrives continuously in the form of a stream. Existing algorithms cannot be used directly or indirectly to efficiently compute PTPQs in either mode. Initially, the problem of efficiently evaluating partial path queries in the inverted lists model has been addressed. Partial path queries form a subclass of PTPQs which is not contained in the class of TPQs. Three novel algorithms for evaluating partial path queries including a holistic one have been designed. The analytical and experimental results show that the holistic algorithm outperforms the other two. These results have been extended into holistic and non-holistic approaches for PTPQs in the inverted lists model. The experiments show again the superiority of the holistic approach. The dissertation has also addressed the problem of evaluating PTPQs in the streaming model, and two original efficient streaming algorithms for PTPQs have been designed. Compared to the only known streaming algorithm that supports an extension of TPQs, the experimental results show that the proposed algorithms perform better by orders of magnitude while consuming a much smaller fraction of memory space. An original approach for assigning semantics to PTPQs has also been devised. The novel semantics seamlessly applies to keyword queries and to queries with structural restrictions. In contrast to previous approaches that operate locally on data, the proposed approach operates globally on structural summaries of data to extract tree patterns. Compared to previous approaches, an experimental evaluation shows that our approach has a perfect recall both for XML documents with complete and with incomplete data. It also shows better precision compared to approaches with similar recall. Finally, the dissertation has addressed the problem of answering XML queries using exclusively materialized views. An original approach for materializing views in the context of the inverted lists model has been suggested. Necessary and sufficient conditions have been provided for tree-pattern query answerability in terms of view-to-query homomorphisms. A time and space efficient algorithm was designed for deciding query answerability and a technique for computing queries over view materializations using stack- based holistic algorithms was developed. Further, optimizations were developed which (a) minimize the storage space and avoid redundancy by materializing views as bitmaps, and (b) optimize the evaluation of the queries over the views by applying bitwise operations on view materializations. The experimental results show that the proposed approach obtains largely higher hit rates than previous approaches, speeds up significantly the evaluation of queries without using views, and scales very smoothly in terms of storage space and computational overhead

Using WG-Log schemata to represent semistructured data

In this paper we discuss the possibility to represent synthetically semistructured information via a loose notion of schema: we say that data are semistructured when, although some structure is present, it is not as strict, regular, or complete as the one required by the traditional database management systems. Our proposal is based on WG-Log, a graph based language for the representation of WWW site information. We show how information encoded in a typical semistructured information model, as OEM, can be represented and queried by means of the WG-Log language, and how the TSIMMIS and WG-Log Web Query System can be integrated to allow site content exploration and exploitation by means of WG-Log

Ontology-based infrastructure for intelligent applications

Ontologies currently are a hot topic in the areas of knowledge management and enterprise application integration. In this thesis, we investigate how ontologies can also be used as an infrastructure for developing applications that intelligently support a user with various tasks. Based on recent developments in the area of the Semantic Web, we provide three major contributions. We introduce inference engines, which allow the execution of business logic that is specified in a declarative way, while putting strong emphasis on scalability and ease of use. Secondly, we suggest various solutions for interfacing applications that are developed under this new paradigm with existing IT infrastructure. This includes the first running solution, to our knowledge, for combining the emerging areas of the Semantic Web Services. Finally, we introduce a set of intelligent applications, which is built on top of onologies and Semantic Web standards, providing a proof of concept that the engineering effort can largely be based on standard components.Ontologien sind derzeit ein viel diskutiertes Thema in Bereichen wie Wissensmanagement oder Enterprise Application Integration. Diese Arbeit stellt dar, wie Ontologien als Infrastruktur zur Entwicklung neuartiger Applikationen verwendet werden können, die den User bei verschiedenen Arbeiten unterstützen. Aufbauend auf den im Rahmen des Semantischen Webs entstandenen Spezifikationen, werden drei wesentliche Beiträge geleistet. Zum einen stellen wir Inferenzmaschinen vor, die das Ausführen von deklarativ spezifizierter Applikationslogik erlauben, wobei besonderes Augenmerk auf die Skalierbarkeit gelegt wird. Zum anderen schlagen wir mehrere Lösungen zum Anschluss solcher Systeme an bestehende IT Infrastruktur vor. Dies beinhaltet den, unseres Wissens nach, ersten lauffähigen Prototyp der die beiden aufstrebenden Felder des Semantischen Webs und Web Services verbindet. Schließlich stellen wir einige intelligente Applikationen vor, die auf Ontologien basieren und somit großteils von Werkzeugen automatisch generiert werden können

Keyword-Based Querying for the Social Semantic Web

Enabling non-experts to publish data on the web is an important achievement of the social web and one of the primary goals of the social semantic web. Making the data easily accessible in turn has received only little attention, which is problematic from the point of view of incentives: users are likely to be less motivated to participate in the creation of content if the use of this content is mostly reserved to experts. Querying in semantic wikis, for example, is typically realized in terms of full text search over the textual content and a web query language such as SPARQL for the annotations. This approach has two shortcomings that limit the extent to which data can be leveraged by users: combined queries over content and annotations are not possible, and users either are restricted to expressing their query intent using simple but vague keyword queries or have to learn a complex web query language. The work presented in this dissertation investigates a more suitable form of querying for semantic wikis that consolidates two seemingly conflicting characteristics of query languages, ease of use and expressiveness. This work was carried out in the context of the semantic wiki KiWi, but the underlying ideas apply more generally to the social semantic and social web. We begin by defining a simple modular conceptual model for the KiWi wiki that enables rich and expressive knowledge representation. A component of this model are structured tags, an annotation formalism that is simple yet flexible and expressive, and aims at bridging the gap between atomic tags and RDF. The viability of the approach is confirmed by a user study, which finds that structured tags are suitable for quickly annotating evolving knowledge and are perceived well by the users. The main contribution of this dissertation is the design and implementation of KWQL, a query language for semantic wikis. KWQL combines keyword search and web querying to enable querying that scales with user experience and information need: basic queries are easy to express; as the search criteria become more complex, more expertise is needed to formulate the corresponding query. A novel aspect of KWQL is that it combines both paradigms in a bottom-up fashion. It treats neither of the two as an extension to the other, but instead integrates both in one framework. The language allows for rich combined queries of full text, metadata, document structure, and informal to formal semantic annotations. KWilt, the KWQL query engine, provides the full expressive power of first-order queries, but at the same time can evaluate basic queries at almost the speed of the underlying search engine. KWQL is accompanied by the visual query language visKWQL, and an editor that displays both the textual and visual form of the current query and reflects changes to either representation in the other. A user study shows that participants quickly learn to construct KWQL and visKWQL queries, even when given only a short introduction. KWQL allows users to sift the wealth of structure and annotations in an information system for relevant data. If relevant data constitutes a substantial fraction of all data, ranking becomes important. To this end, we propose PEST, a novel ranking method that propagates relevance among structurally related or similarly annotated data. Extensive experiments, including a user study on a real life wiki, show that pest improves the quality of the ranking over a range of existing ranking approaches