Benchmarking bitemporal database systems: ready for the future or stuck in the past?

Abstract. Introduction: Many strategic investments are often justified with the argument that they will create synergy. For holding mining establishment the goal was more on how to increase business capacity and funding, management of natural resources of mineral and coal, increase value added through downstream and increase local content, as well as cost efficiency through synergy. This paper aims to find the value of synergy in Inalum, PTBA, ANTM and TINS before establishment holding company of mining and the sensitivity the value to different assumptions and how to improve value of synergy in creating a holding company of mining. The major aims of mining holding company to create value and synergy in mining State-Owned Enterprises, with the expectation, it will increase revenue contribution to the country. These goals could be analyzed and measured by understanding of synergy based on two sources of synergies: operating synergy and financial synergy. This paper will assess operating synergy. Methods: In this valuation, Discounted Cash Flow (DCF) Framework will be used to recognize the potential source of synergy from operation. Results: This study found that gain from operation synergy of increasing growth and cost reduction will maximize the business value amounted USD 3,659,295.63, compared to gain from cost reduction USD -14,181,427.91  and gain from increasing growth USD 644,448.44. Conclusion: Given the results from study, it is important to derive the right strategy from investment decision to reflect the optimal source of synergy in order to maximize the business value in Inalum. Keywords:  DCF, investing decision, maximize business value, value of synerg

Bitemporal Sliding Windows

The bitemporal data model associates two time intervals with each record - system time and application time - denoting the validity of the record from the perspective of the database and of the real world, respectively. One issue that has not yet been addressed is how to efficiently answer sliding window queries in this model. In this work, we propose and experimentally evaluate a main-memory index called BiSW that supports sliding windows on system time, application time, and both time attributes simultaneously. Our experimental results show that BiSW outperforms existing approaches in terms of space footprint, maintenance overhead and query performance

Efficient Self-Join Algorithm in Interval-based Temporal Data Models

Interval-based temporal data model is a popular data model in temporal databases. It uses time intervals for representing the period of validity of a tuple, leading to unavoidable self-joins when combining tuples for objects. It requires k+1-way self-join for k conjunctive conditions. Join operations are one of the most expensive operations in databases and they are even more serious in temporal databases because of growing data. There are many join algorithms for temporal databases. However, they focus on joining different inputs rather than an identical input, leading to multiple scans for the identical input. Advanced 2-way join algorithms avoid a quadratic disk I/O complexity, but they are affected by the number of self-joins and partition sizes. In this paper, we address the problem of self-joins in the interval-based temporal data model and introduce a stream-based self-join algorithm. The proposed algorithm shows that it achieves a single relation scan for k-way self-join and its performance is not affected by partition sizes

Transforming XML to RDF(S) with Temporal Information

The Resource Description Framework (RDF) is a model for representing resources on the Web. With the widespread acceptance of RDF in various applications (e.g., knowledge graph), a huge amount of RDF data is being proliferated. Therefore, transforming legacy data resources into RDF data is of increasing importance. In addition, time information widely exists in various real-world applications and temporal Web data has been represented and managed in the context of temporal XML. In this paper, we concentrate on transformation of temporal XML (eXtensible Markup Language) to temporal RDF data. We propose the mapping rules and mapping algorithms which can transform the temporal XML Schema and document into temporal RDF Schema and temporal RDF triples, respectively. We illustrate our mapping approach with an example and implement a prototype system. It is demonstrated that our mapping approach is valid

Modeling temporal dimensions of semistructured data

In this paper we propose an approach to manage in a correct way valid time semantics for semistructured temporal clinical information. In particular, we use a graph-based data model to represent radiological clinical data, focusing on the patient model of the well known DICOM standard, and define the set of (graphical) constraints needed to guarantee that the history of the given application domain is consistent

Interval-based temporal functional dependencies: specification and verification

In the temporal database literature, every fact stored in a database may beequipped with two temporal dimensions: the valid time, which describes the time whenthe fact is true in the modeled reality, and the transaction time, which describes the timewhen the fact is current in the database and can be retrieved. Temporal functional dependencies(TFDs) add valid time to classical functional dependencies (FDs) in order to expressdatabase integrity constraints over the flow of time. Currently, proposals dealing with TFDsadopt a point-based approach, where tuples hold at specific time points, to express integrityconstraints such as \u201cfor each month, the salary of an employee depends only on his role\u201d. Tothe best of our knowledge, there are no proposals dealing with interval-based temporal functionaldependencies (ITFDs), where the associated valid time is represented by an intervaland there is the need of representing both point-based and interval-based data dependencies.In this paper, we propose ITFDs based on Allen\u2019s interval relations and discuss theirexpressive power with respect to other TFDs proposed in the literature: ITFDs allow us toexpress interval-based data dependencies, which cannot be expressed through the existingpoint-based TFDs. ITFDs allow one to express constraints such as \u201cemployees starting towork the same day with the same role get the same salary\u201d or \u201cemployees with a given roleworking on a project cannot start to work with the same role on another project that willend before the first one\u201d. Furthermore, we propose new algorithms based on B-trees to efficientlyverify the satisfaction of ITFDs in a temporal database. These algorithms guaranteethat, starting from a relation satisfying a set of ITFDs, the updated relation still satisfies thegiven ITFDs

A User-driven Annotation Framework for Scientific Data

Annotations play an increasingly crucial role in scientific exploration and discovery, as the amount of data and the level of collaboration among scientists increases. There are many systems today focusing on annotation management, querying, and propagation. Although all such systems are implemented to take user input (i.e., the annotations themselves), very few systems are user-driven, taking into account user preferences on how annotations should be propagated and applied over data. In this thesis, we propose to treat annotations as first-class citizens for scientific data by introducing a user-driven, view-based annotation framework. Under this framework, we try to resolve two critical questions: Firstly, how do we support annotations that are scalable both from a system point of view and also from a user point of view? Secondly, how do we support annotation queries both from an annotator point of view and a user point of view, in an efficient and accurate way? To address these challenges, we propose the VIew-base annotation Propagation (ViP) framework to empower users to express their preferences over the time semantics of annotations and over the network semantics of annotations, and define three query types for annotations. To efficiently support such novel functionality, ViP utilizes database views and introduces new annotation caching techniques. The use of views also brings a more compact representation of annotations, making our system easier to scale. Through an extensive experimental study on a real system (with both synthetic and real data), we show that the ViP framework can seamlessly introduce user-driven annotation propagation semantics while at the same time significantly improving the performance (in terms of query execution time) over the current state of the art

An XML-based implementation of the parametric model for ad-hoc query of temporal and spatiotemporal data

The parametric model is one of the data models for dimensional data. Values in the parametric model are defined as functions. Such modeling concept helps one achieve a one-to-one correspondence between objects in the real world and records in a database. One of the important requirements is that domains of values should be closed under the set theoretic operations such as union, intersection, and complementation. Because of this, ParaSQL, a query language of the parametric model, is able to mimic natural languages more closely. In this dissertation we validate and implement the parametric model for temporal and spatiotemporal data. We also develop a preliminary prototype for the users of NC-94, an interesting dataset in agriculture;Viewing values as functions leads variable-length tuples. Potentially, such values vary in size ranging from a few bytes to gigabytes and beyond. This makes implementation of the parametric model a challenging problem. To meet the challenge, we develop an XML-based storage and deploy it in our implementation. Incidentally, XML is also used for interfacing various modules and artifacts like parse tree, expression tree, and iterators to fetch data from a disk;The NC-94 dataset, mentioned above, contains the most complete record of spatiotemporal variables that characterize the dynamics of agriculture covering the north central region in the United States. To support ad-hoc query of data in its geospatial context, a novel hybrid structure is designed and implemented. We use GML to describe geospatial information. Use of GML is a good match, because it is XML-based. More importantly, it meets the set theoretic closure requirements proposed by the parametric model;Validation and implementation methodologies introduced in this dissertation will contribute to database and GIS communities. The validation demonstrates the ease of use and efficiency of the parametric model for temporal and spatiotemporal data. This should help settle a debate in temporal database community which has continued since the mid 1980s. The findings also extend to spatial and spatiotemporal data. It is an important baby-step toward full-fledged implementation of the parametric model. We hope that this work will also help bring database and GIS communities together