106 research outputs found
IMPLEMENTING A MODERN TEMPORAL DATA MANAGEMENT SYSTEM
Temporal data management is a concept that has been around for many years. A temporal data management system (TDMS) manages data that is tracked over time. In this paper, the authors present an Oracle-based implementation of a TDMS that provides access to temporal data. The design and implementation presented in this paper are presented at a high level, with the significant features such as reference intervals and temporal relationships. The most notable TDMS benefits are a semi-portable solution and an implementation that maximizes on native database features. The paper finally presents an evaluation of the TDMS implementation with a feature comparison and benchmarking.Temporal data management
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Generic unified modelling process for developing semantically rich, dynamic and temporal models
Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models
Dynamic Provenance for SPARQL Update
While the Semantic Web currently can exhibit provenance information by using
the W3C PROV standards, there is a "missing link" in connecting PROV to storing
and querying for dynamic changes to RDF graphs using SPARQL. Solving this
problem would be required for such clear use-cases as the creation of version
control systems for RDF. While some provenance models and annotation techniques
for storing and querying provenance data originally developed with databases or
workflows in mind transfer readily to RDF and SPARQL, these techniques do not
readily adapt to describing changes in dynamic RDF datasets over time. In this
paper we explore how to adapt the dynamic copy-paste provenance model of
Buneman et al. [2] to RDF datasets that change over time in response to SPARQL
updates, how to represent the resulting provenance records themselves as RDF in
a manner compatible with W3C PROV, and how the provenance information can be
defined by reinterpreting SPARQL updates. The primary contribution of this
paper is a semantic framework that enables the semantics of SPARQL Update to be
used as the basis for a 'cut-and-paste' provenance model in a principled
manner.Comment: Pre-publication version of ISWC 2014 pape
Efficient Management of Short-Lived Data
Motivated by the increasing prominence of loosely-coupled systems, such as
mobile and sensor networks, which are characterised by intermittent
connectivity and volatile data, we study the tagging of data with so-called
expiration times. More specifically, when data are inserted into a database,
they may be tagged with time values indicating when they expire, i.e., when
they are regarded as stale or invalid and thus are no longer considered part of
the database. In a number of applications, expiration times are known and can
be assigned at insertion time. We present data structures and algorithms for
online management of data tagged with expiration times. The algorithms are
based on fully functional, persistent treaps, which are a combination of binary
search trees with respect to a primary attribute and heaps with respect to a
secondary attribute. The primary attribute implements primary keys, and the
secondary attribute stores expiration times in a minimum heap, thus keeping a
priority queue of tuples to expire. A detailed and comprehensive experimental
study demonstrates the well-behavedness and scalability of the approach as well
as its efficiency with respect to a number of competitors.Comment: switched to TimeCenter latex styl
SODA: Generating SQL for Business Users
The purpose of data warehouses is to enable business analysts to make better
decisions. Over the years the technology has matured and data warehouses have
become extremely successful. As a consequence, more and more data has been
added to the data warehouses and their schemas have become increasingly
complex. These systems still work great in order to generate pre-canned
reports. However, with their current complexity, they tend to be a poor match
for non tech-savvy business analysts who need answers to ad-hoc queries that
were not anticipated. This paper describes the design, implementation, and
experience of the SODA system (Search over DAta Warehouse). SODA bridges the
gap between the business needs of analysts and the technical complexity of
current data warehouses. SODA enables a Google-like search experience for data
warehouses by taking keyword queries of business users and automatically
generating executable SQL. The key idea is to use a graph pattern matching
algorithm that uses the metadata model of the data warehouse. Our results with
real data from a global player in the financial services industry show that
SODA produces queries with high precision and recall, and makes it much easier
for business users to interactively explore highly-complex data warehouses.Comment: VLDB201
Replicability, real-time data, and the science of economic research: FRED, ALFRED, and VDC
This article discusses the linkages between two recent themes in economic research: "real time" data and replication. These two themes share many of the same ideas, specifically, that scientific research itself has a time dimension. In research using real-time data, this time dimension is the date on which particular observations, or pieces of data, became available. In work with replication, it is the date on which a study (and its results) became available to other researchers and/or was published. Recognition of both dimensions of scientific research is important. A project at the Federal Reserve Bank of St. Louis to place large amounts of historical data on the Internet holds promise to unify these two themes.Research ; Federal Reserve Bank of St. Louis
TEMPOS: A Platform for Developing Temporal Applications on Top of Object DBMS
This paper presents TEMPOS: a set of models and languages supporting the manipulation of temporal data on top of object DBMS. The proposed models exploit object-oriented technology to meet some important, yet traditionally neglected design criteria related to legacy code migration and representation independence. Two complementary ways for accessing temporal data are offered: a query language and a visual browser. The query language, namely TempOQL, is an extension of OQL supporting the manipulation of histories regardless of their representations, through fully composable functional operators. The visual browser offers operators that facilitate several time-related interactive navigation tasks, such as studying a snapshot of a collection of objects at a given instant, or detecting and examining changes within temporal attributes and relationships. TEMPOS models and languages have been formalized both at the syntactical and the semantical level and have been implemented on top of an object DBMS. The suitability of the proposals with regard to applications' requirements has been validated through concrete case studies
Toward a Unified Timestamp with explicit precision
Demographic and health surveillance (DS) systems monitor and document individual- and group-level processes in well-defined populations over long periods of time. The resulting data are complex and inherently temporal. Established methods of storing and manipulating temporal data are unable to adequately address the challenges posed by these data. Building on existing standards, a temporal framework and notation are presented that are able to faithfully record all of the time-related information (or partial lack thereof) produced by surveillance systems. The Unified Timestamp isolates all of the inherent complexity of temporal data into a single data type and provides the foundation on which a Unified Timestamp class can be built. The Unified Timestamp accommodates both point- and interval-based time measures with arbitrary precision, including temporal sets. Arbitrary granularities and calendars are supported, and the Unified Timestamp is hierarchically organized, allowing it to represent an unlimited array of temporal entities.demographic surveillance, standardization, temporal databases, temporal integrity, timestamp, valid time
Snapshot Semantics for Temporal Multiset Relations (Extended Version)
Snapshot semantics is widely used for evaluating queries over temporal data:
temporal relations are seen as sequences of snapshot relations, and queries are
evaluated at each snapshot. In this work, we demonstrate that current
approaches for snapshot semantics over interval-timestamped multiset relations
are subject to two bugs regarding snapshot aggregation and bag difference. We
introduce a novel temporal data model based on K-relations that overcomes these
bugs and prove it to correctly encode snapshot semantics. Furthermore, we
present an efficient implementation of our model as a database middleware and
demonstrate experimentally that our approach is competitive with native
implementations and significantly outperforms such implementations on queries
that involve aggregation.Comment: extended version of PVLDB pape
Curating Covid-19 Data in Links
Curated scientific databases play an important role in the scientific
endeavour and support is needed for the significant effort that goes into their
creation and maintenance. This demonstration and case study illustrate how
curation support has been developed in the Links cross-tier programming
language, a functional, strongly typed language with language-integrated query
and support for temporal databases. The chosen case study uses weekly released
Covid-19 fatality figures from the Scottish government which exhibit updates to
previously released data. This data allows the capture and query of update
provenance in our prototype. This demonstration will highlight the potential
for language-integrated support for curation to simplify and streamline
prototyping of web-applications in support of scientific database
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