scholarly journals The Matrix: Connecting Time and Space in archaeological stratigraphic records and archives

2020 ◽  
Author(s):  
Keith May
Keyword(s):  
Paper Copy ◽  
Temporal Reasoning ◽  
Digital Archive ◽  
Valuable Data ◽  
Archaeological Data ◽  
Temporal Relationships ◽  
The Matrix ◽  
Spatio Temporal ◽  
Matrix Diagrams ◽  
Working Out

The records of archaeological stratigraphic data and the relationships between stratigraphic units are fundamental to understanding the overall cohesiveness of the archaeological archive of an excavation. The information about individual units of excavation identified on sites with complex stratigraphy is most often held in the site database records and stratigraphic matrix diagrams, usually documenting relationships based on the laws of stratigraphic superposition and the Harris matrix conventions (Harris 1979). However, once the matrix diagram has been used to record the information during excavation, there is far less consistency in how those stratigraphic records, and any associated phasing information, are finally deposited in the archives. For that valuable data to be successfully identified and re-used (particularly if the rest of the data is in a database), the stratigraphic and phasing data needs to be in a format that can be interrogated as part of the database. In practice, often only a (paper) copy of the matrix diagrams make the archive. This means that the critical temporal and spatio-temporal relationships upon which the phasing of sites is built, cannot usually be interrogated or (re)used without lengthy and wasteful re-keying of that data into another version of the database. The stratigraphic, sequencing and temporal information held in a matrix is fundamental in further studies of the site records and in working out how the site may relate to other excavated sites of similar or related dates and phases. This article will suggest ways in which the stratigraphic data from excavations and the reasoning processes carried out in subsequent analysis could be better managed, to make matrices (re)useable as part of a more integrated digital archive. This article examines how conceptual reference modelling, particularly using temporal relationships, can be used to explore these issues and how associated technologies could enable semantically-enriched deductions about the spatio-temporal and purely temporal relationships that fundamentally link archaeological data together. It will also consider where further work is needed both to deal with analysis of spatial or temporal records and to enhance Bayesian chronological modelling and associated temporal reasoning, and how this may form the basis for new linkages between archaeological information across space-time.

scholarly journals Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets

2021 ◽  
Author(s):  
Maria Lucia Parrella ◽  
Giuseppina Albano ◽  
Cira Perna ◽  
Michele La Rocca
Keyword(s):  
Missing Data ◽  
Missing Values ◽  
Sample Selection ◽  
Sample Path ◽  
Temporal Relationships ◽  
Empirical Performance ◽  
Spatio Temporal ◽  
Joint Prediction ◽  
Point Forecast ◽  
Prediction Regions

AbstractMissing data reconstruction is a critical step in the analysis and mining of spatio-temporal data. However, few studies comprehensively consider missing data patterns, sample selection and spatio-temporal relationships. To take into account the uncertainty in the point forecast, some prediction intervals may be of interest. In particular, for (possibly long) missing sequences of consecutive time points, joint prediction regions are desirable. In this paper we propose a bootstrap resampling scheme to construct joint prediction regions that approximately contain missing paths of a time components in a spatio-temporal framework, with global probability $$1-\alpha $$ 1 - α . In many applications, considering the coverage of the whole missing sample-path might appear too restrictive. To perceive more informative inference, we also derive smaller joint prediction regions that only contain all elements of missing paths up to a small number k of them with probability $$1-\alpha $$ 1 - α . A simulation experiment is performed to validate the empirical performance of the proposed joint bootstrap prediction and to compare it with some alternative procedures based on a simple nominal coverage correction, loosely inspired by the Bonferroni approach, which are expected to work well standard scenarios.

Patterns of Cognitive Test Performance As Functions of the Lateral Localization of Cerebral Abnormalities in the Temporal Lobe

1957 ◽  
Vol 103 (433) ◽  
pp. 758-772 ◽  
Author(s):  
Victor Meyer ◽  
H. Gwynne Jones
Keyword(s):  
Test Performance ◽  
Right Hemisphere ◽  
Cognitive Test ◽  
Temporal Relationships ◽  
Verbal Tasks ◽  
Specific Locus ◽  
Left And Right ◽  
Spatio Temporal ◽  
Cognitive Test Performance ◽  
Lateral Localization

Various investigations into the effects of brain injury on psychological test performance (Weisenburg and McBride, 1935; Patterson and Zangwill, 1944; Anderson, 1951; McFie and Piercy, 1952; Bauer and Becka, 1954; Milner, 1954) suggest the overall conclusion that patients with left hemisphere lesions are relatively poor at verbal tasks, while those with right-sided lesions do worst at practical tasks, particularly the manipulation of spatial or spatio-temporal relationships. Heilbfun's (1956) study confirmed that verbal deficits result from left-sided lesions but his left and right hemisphere groups produced almost identical scores on spatial tests. In so far as these workers paid attention to the specific sites of the lesions, their findings indicate that the pattern of test performance is a function of the hemisphere in which the lesion occurs rather than of its specific locus.

Multimedia Databases and Data Management

2012 ◽  
pp. 1-11
Author(s):  
Shu-Ching Chen
Keyword(s):  
Data Management ◽  
Relevant Information ◽  
Multimedia Databases ◽  
Multimedia Data ◽  
Formal Structure ◽  
Multimedia Database ◽  
Storage Devices ◽  
Temporal Relationships ◽  
Spatio Temporal ◽  
Application Requirements

The exponential growth of the technological advancements has resulted in high-resolution devices, such as digital cameras, scanners, monitors, and printers, which enable the capturing and displaying of multimedia data in high-density storage devices. Furthermore, more and more applications need to live with multimedia data. However, the gap between the characteristics of various media types and the application requirements has created the need to develop advanced techniques for multimedia data management and the extraction of relevant information from multimedia databases. Though many research efforts have been devoted to the areas of multimedia databases and data management, it is still far from maturity. The purpose of this article is to discuss how the existing techniques, methodologies, and tools addressed relevant issues and challenges to enable a better understanding in multimedia databases and data management. The focuses include: (1) how to develop a formal structure that can be used to capture the distinguishing content of the media data in a multimedia database (MMDB) and to form an abstract space for the data to be queried; (2) how to develop advanced content analysis and retrieval techniques that can be used to bridge the gaps between the semantic meaning and low-level media characteristics to improve multimedia information retrieval; and (3) how to develop query mechanisms that can handle complex spatial, temporal, and/or spatio-temporal relationships of multimedia data to answer the imprecise and incomplete queries issued to an MMDB.

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