Schema Versions Research Articles

Ontology Versioning Driven by Instance Evolution in the τOWL Framework

Like other components of Semantic Web-based applications, ontologies are evolving over time to reflect changes in the real world. Several of these applications require keeping a full-fledged history of ontology changes so that both ontology instance versions and their corresponding ontology schema versions are maintained. Updates to an ontology instance could be non-conservative that is leading to a new ontology instance version no longer conforming to the current ontology schema version. If, for some reasons, a non-conservative update has to be executed, in spite of its consequence, it requires the production of a new ontology schema version to which the new ontology instance version is conformant so that the new ontology version produced by the update is globally consistent. In this paper, we first propose an approach that supports ontology schema changes which are triggered by non-conservative updates to ontology instances and, thus, gives rise to an ontology schema versioning driven by instance updates. Note that in an engineering perspective, such an approach can be used as an incremental ontology construction method driven by the modification of instance data, whose exact structure may not be completely known at the initial design time. After that, we apply our proposal to the already established [Formula: see text]OWL (Temporal OWL 2) framework, which allows defining and evolving temporal OWL 2 ontologies in an environment that supports temporal versioning of both ontology instances and ontology schemas, by extending it to also support the management of non-conservative updates to ontology instance versions. Last, we show the feasibility of our approach by dealing with its implementation within a new release of the [Formula: see text] OWL-Manager tool.

Schema Evolution in Multiversion Data Warehouses

Data warehouses (DWs) evolve in both their content and schema due to changes of user requirements, business processes, or external sources to name a few. Although multiple approaches using temporal and/or multiversion DWs have been proposed to handle these changes, an efficient solution for this problem is still lacking. The authors' approach is to separate concerns and use temporal DWs to deal with content changes, and multiversion DWs to deal with schema changes. To address the former, previously, they have proposed a temporal multidimensional (MD) model. In this paper, they propose a multiversion MD model for schema evolution to tackle the latter problem. The two models complement each other and allow managing both content and schema evolution. In this paper, the semantics of schema modification operators (SMOs) to derive various schema versions are given. It is also shown how online analytical processing (OLAP) operations like roll-up work on the model. Finally, the mapping from the multiversion MD model to a relational schema is given along with OLAP operations in standard SQL.

TempoX: A disciplined approach for data management in multi-temporal and multi-schema-version XML databases

Although multi-temporal XML databases supporting schema versioning are used in several domains, like e-commerce, e-health, and e-government, existing database management systems and XML tools do not provide any support for managing (inserting, updating, and deleting) temporal XML data or temporal XML schema versioning. Besides, whereas much research work has focused in the last decade on schema versioning in temporal XML databases, any attention has been devoted to manipulating data in such databases. To fill this theoretical and practical gap, we propose in this paper a generic approach, named TempoX (Temporal XML), for data manipulation in multi-temporal and multi-schema-version XML databases. Indeed, we (i) define a new multi-temporal XML data model supporting temporal schema versioning, named TempoXDM (Temporal XML Data Model), (ii) introduce the principles on which our approach is based, and (iii) provide the specifications of the basic data manipulation operations: “insert”, “replace”, “evolve”, and “delete”. Moreover, to show the feasibility of TempoX, we use it to propose a temporal XML update language, named TempoXUF (Temporal XQuery Update Facility), as an extension of the W3C XQuery Update Facility language to temporal and versioning aspects. Furthermore, to validate our language proposal, we develop a system prototype, named TempoXUF-Manager, that supports TempoXUF.

FAIR data in meta-omics research: Using the MOD-CO schema to describe structural and operational elements of workflows from field to publication

Nucleic acid and protein sequencing-based analyses are increasingly applied to determine origin, identity and traits of environmental (biological) objects and organisms. In this context, the need for corresponding data structures has become evident. As existing schemas and community standards in the domains of biodiversity and molecular biological research are comparatively limited with regard to the number of generic and specific elements, previous schemas for describing the physical and digital objects need to be replaced or expanded by new elements for covering the requirements from meta-omics techniques and operational details. On the one hand, schemas and standards are hitherto mostly focussed on elements, descriptors, or concepts that are relevant for data exchange and publication, on the other hand, detailed operational aspects regarding origin context and laboratory processing, as well as data management details, like the documentation of physical and digital object identifiers, are rather neglected. The conceptual schema for Meta-omics Data and Collection Objects (MOD-CO; https://www.mod-co.net/) has been set up recently Rambold et al. 2019. It includes design elements (descriptors or concepts), describing structural and operational details along the work- and dataflow from gathering environmental samples to the various transformation, transaction, and measurement steps in the laboratory up to sample and data publication and archiving. The concepts are named according to a multipartite naming structure, describing internal hierarchies and are arranged in concept (sub-)collections. By supporting various kinds of data record relationships, the schema allows for the concatenation of individual records of the operational segments along a workflow (Fig. 1). Thus, it may serve as a logical and structural backbone for laboratory information management systems. The concept structure in version 1.0 comprises 653 descriptors (concepts) and 1,810 predefined descriptor states, organised in 37 concept (sub-)collections. The published version 1.0 is available as various schema representations of identical content (https://www.mod-co.net/wiki/Schema_Representations). A normative XSD (= XML Schema Definition) for the schema version 1.0 is available under http://schema.mod-o.net/MOD-CO_1.0.xsd. The MOD-CO concepts might be integrated as descriptor/element structures in the relational database DiversityDescriptions (DWB-DD) an open-source and freely available software of the Diversity Workbench (DWB; https://diversityworkbench.net/Portal/DiversityDescriptions; https://diversityworkbench.net). Currently, DWB-DD is installed at the Data Center of the Bavarian Natural History Collections (SNSB) to build an instance of its own for storing and maintaining MOD-CO-structured meta-omics research data packages and enrich them with ‘metadata’ elements from the community standards Ecological Markup Language (EML), Minimum Information about any (x) Sequence (MIxS), Darwin Core (DwC) and Access to Biological Collection Data (ABCD). These activities are achieved in the context of ongoing FAIR ('Findable, Accessible, Interoperable and Reuseable') biodiversity research data publishing via the German Federation for Biological Data (GFBio) network (https://www.gfbio.org/). Version 1.1 of the schema with extended collections of structural and operational design concepts is scheduled for 2020.

Multi-schema-version data management: data independence in the twenty-first century

Agile software development allows us to continuously evolve and run a software system. However, this is not possible in databases, as established methods are very expensive, error-prone, and far from agile. We present InVerDa, a multi-schema-version database management system (MSVDB) for agile database development. MSVDBs realize co-existing schema versions within one database, where each schema version behaves like a regular single-schema database and write operations are propagated between schema versions. Developers use a relationally complete and bidirectional database evolution language (BiDEL) to easily evolve existing schema versions to new ones. BiDEL scripts are more robust, orders of magnitude shorter, and cause only a small performance overhead compared to handwritten SQL scripts. We formally guarantee data independence: no matter how the data of the co-existing schema versions is physically materialized, each schema version is guaranteed to behave like a regular database. Since, the chosen physical materialization significantly determines the overall performance, we equip database administrators with an advisor that proposes an optimized materialization for the current workload, which can improve the performance by orders of magnitude compared to naive solutions. To our best knowledge, we are the first to facilitate agile evolution of production databases with full support of co-existing schema versions and formally guaranteed data independence.

An integration-oriented ontology to govern evolution in Big Data ecosystems

Big Data architectures allow to flexibly store and process heterogeneous data, from multiple sources, in their original format. The structure of those data, commonly supplied by means of REST APIs, is continuously evolving. Thus data analysts need to adapt their analytical processes after each API release. This gets more challenging when performing an integrated or historical analysis. To cope with such complexity, in this paper, we present the Big Data Integration ontology, the core construct to govern the data integration process under schema evolution by systematically annotating it with information regarding the schema of the sources. We present a query rewriting algorithm that, using the annotated ontology, converts queries posed over the ontology to queries over the sources. To cope with syntactic evolution in the sources, we present an algorithm that semi-automatically adapts the ontology upon new releases. This guarantees ontology-mediated queries to correctly retrieve data from the most recent schema version as well as correctness in historical queries. A functional and performance evaluation on real-world APIs is performed to validate our approach.

3D MODELLING AND VISUALIZATION BASED ON THE UNITY GAME ENGINE – ADVANTAGES AND CHALLENGES

Abstract. 3D City modelling is increasingly popular and becoming valuable tools in managing big cities. Urban and energy planning, landscape, noise-sewage modelling, underground mapping and navigation are among the applications/fields which really depend on 3D modelling for their effectiveness operations. Several research areas and implementation projects had been carried out to provide the most reliable 3D data format for sharing and functionalities as well as visualization platform and analysis. For instance, BIMTAS company has recently completed a project to estimate potential solar energy on 3D buildings for the whole Istanbul and now focussing on 3D utility underground mapping for a pilot case study. The research and implementation standard on 3D City Model domain (3D data sharing and visualization schema) is based on CityGML schema version 2.0. However, there are some limitations and issues in implementation phase for large dataset. Most of the limitations were due to the visualization, database integration and analysis platform (Unity3D game engine) as highlighted in this paper.

Temporal schema versioning in τOWL: a systematic approach for the management of time-varying knowledge

In this work, we consider the adoption of an OWL 2 ontology for the representation and management of time-varying knowledge. The W3C OWL 2 recommendation lacks explicit support for time-varying OWL ontologies. In previous work, we introduced τOWL which is an infrastructure and suite of tools to support the creation and validation of OWL ontologies with time-varying instances. In this paper, we extend τOWL to also support temporal versioning of the ontology schema. Schema versioning in the τOWL framework means that all the three components of a τOWL schema (i.e. conventional schema, logical and physical annotations) are versioned. In particular, we propose two complete sets of primitives, one for updating the conventional ontology schema and the other for managing the temporal ontology schema, and define their operational semantics. We also illustrate their use, through an example.

A Systematic Approach for Changing XML Namespaces in XML Schemas and Managing their Effects on Associated XML Documents under Schema Versioning

A Systematic Approach for Changing XML Namespaces in XML Schemas and Managing their Effects on Associated XML Documents under Schema Versioning

Using serum urate as a validated surrogate end point for flares in patients with gout: protocol for a systematic review and meta-regression analysis

IntroductionGout is the most common inflammatory arthritis in men over 40 years of age. Long-term urate-lowering therapy is considered a key strategy for effective gout management. The primary outcome measure for efficacy in clinical trials of urate-lowering therapy is serum urate levels, effectively acting as a surrogate for patient-centred outcomes such as frequency of gout attacks or pain. Yet it is not clearly demonstrated that the strength of the relationship between serum urate and clinically relevant outcomes is sufficiently strong for serum urate to be considered an adequate surrogate. Our objective is to investigate the strength of the relationship between changes in serum urate in randomised controlled trials and changes in clinically relevant outcomes according to the ‘Biomarker-Surrogacy Evaluation Schema version 3’ (BSES3), documenting the validity of selected instruments by applying the ‘OMERACT Filter 2.0’.Methods and analysisA systematic review described in terms of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines will identify all relevant studies. Standardised data elements will be extracted from each study by 2 independent reviewers and disagreements are resolved by discussion. The data will be analysed by meta-regression of the between-arm differences in the change in serum urate level (independent variable) from baseline to 3 months (or 6 and 12 months if 3-month values are not available) against flare rate, tophus size and number and pain at the final study visit (dependent variables).Ethics and disseminationThis study will not require specific ethics approval since it is based on analysis of published (aggregated) data. The intended audience will include healthcare researchers, policymakers and clinicians. Results of the study will be disseminated by peer-reviewed publications.Trial registration numberCRD42016026991.

$$\uptau $$ τ OWL: A Systematic Approach to Temporal Versioning of Semantic Web Ontologies

The W3C OWL 2 recommendation is an ontology language for the Semantic Web. It allows defining both schema (i.e., entities, axioms, and expressions) and instances (i.e., individuals) of ontologies. However, OWL 2 lacks explicit support for time-varying schema or for time-varying instances. Hence, knowledge engineers or maintainers of semantics-based Web resources have to use ad hoc techniques to specify OWL 2 time-varying ontologies. In this paper, for a disciplined and systematic approach to the temporal management of Semantic Web ontologies, we propose the adoption of a framework called temporal OWL 2 (\(\uptau \)OWL), which is inspired by the \(\uptau \)XSchema framework defined for XML data. In a way similar to what happens in \(\uptau \)XSchema, \(\uptau \)OWL allows creating a temporal OWL 2 ontology from a conventional (i.e., non-temporal) OWL 2 ontology and a set of logical and physical annotations. Logical annotations identify which elements of the ontology can vary over time; physical annotations specify how the time-varying aspects are represented in the OWL 2 document. Using annotations to integrate temporal aspects in the traditional Semantic Web, our framework (1) guarantees logical and physical data independence for temporal schemas and (2) provides a low-impact solution, since it requires neither modifications of existing Semantic Web ontologies, nor extensions to the OWL 2 recommendation and Semantic Web standards. Moreover, since the conventional schema and annotation documents could evolve over time to respond to new applications’ requirements, \(\uptau \)OWL supports temporal schema versioning by allowing changing these components and by keeping track of their evolution through the conventional schema versions and annotation document versions, respectively. Two complete sets of operations are proposed for changing the conventional schema and annotation documents; to complete the figure, a set of operations is also introduced for updating temporal schema which must be changed consequently each time one of the mentioned components evolves over time. To show the feasibility of our approach, a prototype tool, named \(\uptau \)OWL-Manager, is presented.

Synchronization of Queries and Views Upon Schema Evolutions

One of the problems arising upon the evolution of a database schema is that some queries and views defined on the previous schema version might no longer work properly. Thus, evolving a database schema entails the redefinition of queries and views to adapt them to the new schema. Although this problem has been mainly raised in the context of traditional information systems, solutions to it are also advocated in other database-related areas, such as Data Integration, Web Data Integration, and Data Warehouses. The problem is a critical one, since industrial organizations often need to adapt their databases and data warehouses to frequent changes in the real world. In this article, we provide a survey of existing approaches and tools to the problem of adapting queries and views upon a database schema evolution; we also propose a classification framework to enable a uniform comparison method among many heterogeneous approaches and tools.

Bi-temporal schema versioning in bi-temporal data warehouse

The data warehouse (DW) data as well as its schema is known to evolve continually with time to incorporate new requirements. In order to preserve complete history, the DW systems need to manage the evolution of schema with time through schema versioning and also have to provide support for evolution of data defined in different schema versions. However, the existing multidimensional DW are able to manage revisions in transaction data (measures/facts) but do not (or partially) manage evolutions in dimension data. In this paper, we propose an approach which allows not only to manage revisions of schema and dimension data but also track retroactive and proactive updates in DW using both valid-time and transaction-time. The main objective of this work is to propose an evolution model for bi-temporal DW using bi-temporal schema versioning.

New Research Directions in Knowledge Discovery and Allied Spheres

The realm of knowledge discovery extends across several allied spheres today. It encompasses database management areas such as data warehousing and schema versioning; information retrieval areas such as Web semantics and topic detection; and core data mining areas, e.g., knowledge based systems, uncertainty management, and time-series mining. This becomes particularly evident in the topics that Ph.D. students choose for their dissertation. As the grass roots of research, Ph.D. dissertations point out new avenues of research, and provide fresh viewpoints on combinations of known fields. In this article we overview some recently proposed developments in the domain of knowledge discovery and its related spheres. Our article is based on the topics presented at the doctoral workshop of the ACM Conference on Information and Knowledge Management, CIKM 2011.

Maintaining schema versions compatibility in cloud applications collaborative framework

The eXtensible Markup Language (XML) is a meta language that is widely used to provide a non-proprietary universal format for sharing hierarchical data among different software systems and applicat...

XS-Diff: XML schema change detection algorithm

Detecting changes in XML data has emerged as an important research issue in the last decade, but the majority of change detection algorithms focus on XML documents rather than on their schemas because documents that contain data are deemed more significant than the schema itself. However, the XML schema change detection tool is essential, especially in situations where we need to maintain related XML documents with evolving schema, sustain relational schema generated by schema-conscious approach for storing XML data and provide support for XML versioning. This paper focuses on XML Schema (XSD) changes and provides a more meaningful description of the detected changes. Our proposed algorithm XS-Diff uses the technique of storing XML Schema versions in a relational database where the detection and storage of delta changes are employed on relational tables. We demonstrate the correctness of the proposed algorithm through both synthetic and real data sets without deteriorating the execution time.

Schema Change Operations for Full Support of Schema Versioning in the τXSchema Framework

tXSchema (Currim et al., 2004) is a framework (a language and a suite of tools) for the creation and validation of time-varying XML documents. A tXSchema schema is composed of a conventional XML Schema annotated with physical and logical annotations. All components of a tXSchema schema can evolve over time to reflect changes in the real-world. Since many applications need to keep track of both data and schema evolution, schema versioning has been long advocated to be the best solution to do this. In this paper, we complete the tXSchema framework, which is predisposed from the origin to support schema versioning, with the definition of the operations which are necessary to exploit such feature and make schema versioning functionalities available to final users. Moreover, we propose a new technique for schema versioning in tXSchema, allowing a complete and safe management of schema changes. It supports both versioning of conventional schema and versioning of annotations, in an integrated manner. For each component of a tXSchema schema, our approach provides a complete and sound set of change primitives and a set of high-level change operations, for the maintenance of such a component and defines their operational semantics.

DATA WAREHOUSE AND MASTER DATA MANAGEMENT EVOLUTION A META-DATA-VAULT APPROACH

The paper presents a: a) brief overview and analysis of existing approaches to the data warehouse (DW) evolution problem, and b) detailed description of the research idea for the DW evolution problem (primarily intended for structured data sources and realizations with relational database engines). We observe the DW evolution problem as a double issue - from the DW perspective, and from the master data management (MDM) perspective. The proposed general solution will include a Data Vault (DV) model based metadata repository that will integrate the DW data and metadata with the MDM data and metadata. This historicized metadata repository will manage schema versions and support schema changes. We believe this integration will: a) increase the quality of data in the Enterprise Data Warehouse (EDW), b) increase the quality of the metadata in the EDW, and c) increase the simplicity and efficiency of the DW and the MDM schema evolution.

Online, asynchronous schema change in F1

We introduce a protocol for schema evolution in a globally distributed database management system with shared data, stateless servers, and no global membership. Our protocol is asynchronous--it allows different servers in the database system to transition to a new schema at different times--and online--all servers can access and update all data during a schema change. We provide a formal model for determining the correctness of schema changes under these conditions, and we demonstrate that many common schema changes can cause anomalies and database corruption. We avoid these problems by replacing corruption-causing schema changes with a sequence of schema changes that is guaranteed to avoid corrupting the database so long as all servers are no more than one schema version behind at any time. Finally, we discuss a practical implementation of our protocol in F1, the database management system that stores data for Google AdWords.

An Optimized Approach of Modified BAT Algorithm to Record Deduplication

task of recognizing, in a data warehouse, records that pass on to the identical real world entity despite misspelling words, kinds, special writing styles or even unusual schema versions or data types is called as the record deduplication. In existing research they offered a genetic programming (GP) approach to record deduplication. Their approach combines several different parts of substantiation extracted from the data content to generate a deduplication purpose that is capable to recognize whether two or more entries in a depository are duplications or not. Because record deduplication is a time intense task even for undersized repositories, their aspire is to promote a method that discovers a proper arrangement of the best pieces of confirmation, consequently compliant a deduplication function that maximizes performance using a small representative portion of the corresponding data for preparation purposes also the optimization of process is less. Our research deals these issues with a novel technique called modified bat algorithm for record duplication. The incentive behind is to generate a flexible and effective method that employs Data Mining algorithms. The structure distributes many similarities with evolutionary computation techniques such as Genetic programming approach. This scheme is initialized with an inhabitant of random solutions and explores for optima by updating bat inventions. Nevertheless, disparate GP, modified bat has no development operators such as crossover and mutation. We also compare the proposed algorithm with other existing algorithms, including GP from the experimental results.