Data Reuse

With the advent of the Web, increased emphasis on "research data management," and innovations in reproducible research practices, scholars have more incentives and opportunities to document and disseminate their primary data. This article seeks to guide archaeologists in data sharing by highlighting recurring challenges in reusing archived data gleaned from observations on workflows and reanalysis efforts involving datasets published over the past 15 years by Open Context. Based on our findings, we propose specific guidelines to improve data management, documentation, and publishing practices so that primary data can be more efficiently discovered, understood, aggregated, and synthesized by wider research communities. Con el advenimiento de la Web, el mayor énfasis en el "manejo de datos de investigación" y las innovaciones en las prácticas de investigación reproducibles, los investigadores tienen más incentivos y oportunidades para documentar y divulgar sus datos primarios. Este trabajo busca ofrecer a los arqueólogos una guía sobre cómo compartir información, señalando los desafíos más recurrentes en la reutilización de datos archivados que recopilamos a partir de observaciones sobre flujos de trabajo y del reanálisis de bases de datos publicadas a lo largo de los últimos 15 años en Open Context. Sobre la base de nuestros resultados, proponemos algunos lineamientos específicos para mejorar el manejo de datos, la documentación y las prácticas de publicación, de modo que los datos primarios puedan ser descubiertos, comprendidos, agrupados y sintetizados de manera más eficiente y por comunidades de investigadores más amplias. Palabras clave: arqueozoología, investigación reproducibles, manejo de datos, documentación de datos, lineamientos, reutilización de datos Archaeologists, particularly those specializing in zooarchaeology and other domains that emphasize quantitative methods, have long recognized that scientific rigor requires access to full and well-documented data (Driver 1992; Grigson 1978; Meadow and Zeder 1978). Only recently, however, have technologies caught up to the vision of full data description and dissemination. In addition to the decreasing cost of data storage, the Web offers new opportunities to efficiently and comprehensively document and disseminate our work. Data dissemination is becoming an expected part of scholarly communication, such that open access to publicly funded research results is now encouraged and even mandated by many governments and institutions (Kimbrough and Gasaway 2015; ScienceEurope 2019; White House 2013). Even so, while policies calling for data dissemination have gained traction, actual data sharing practices remain largely piecemeal and inconsistent. For data sharing to facilitate reproducibility and to open new research opportunities that involve reusing shared data, we must overcome significant challenges in archiving, curating, disseminating, and integrating diverse datasets. The challenges and opportunities afforded by computers and the Web require us to reexamine normative data management practices and consider both new approaches and refinements of extant practices. In this article, informed by years of data management experience and integrative data analyses, we describe some of the problems inherent in current, normative practices of data collection and documentation in archaeology. These problems can inhibit future data reuse by imposing costs in terms of the time and effort needed to clean, translate, and understand other researchers' datasets. We advocate integrating conventional publishing with new forms of data publication and version control to provide open access to primary datasets. We then offer a set of guidelines for data collection and dissemination in the "digital age." These are practical steps that practitioners can take to

Tiling is a crucial loop transformation for generating high performance code on modern architectures. Efficient generation of multilevel tiled code is essential for maximizing data reuse in systems with deep memory hierarchies. Tiled loops with parametric tile sizes (not compile-time constants) facilitate runtime feedback and dynamic optimizations used in iterative compilation and automatic tuning. Previous parametric multi-level tiling approaches have been restricted to perfectly nested loops, where all assignment statements are contained inside the innermost loop of a loop nest. Previous solutions to tiling for imperfect loop nests have only handled fixed tile sizes. In this paper, we present an approach to parametric multi-level tiling of imperfectly nested loops. The tiling technique generates loops that iterate over full rectangular tiles, making them amenable to compiler optimizations such as register tiling. Experimental results using a number of computational benchmarks demonstrate the effectiveness of the developed tiling approach.

This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self-citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation.

The paper describes the first BarCamp organized within 2013 ArcheoFOSS workshop. Usually a Barcamp is a collaborative non-conference without a predetermined theme. Nevertheless, in this case we recognized and proposed a very high relevance topic in the field of Open Data, “The reuse of data in Archaeology”. Within this frame, attendees were free to discuss specific sub-topics. The term reuse is very common in archaeology, such as the reuse of a site, the reuse of an architectural element or an epigraphic monument. The research itself is based on data that we reuse: historical and historiographical sources, geographic excavation data, photos, metric drawings, etc. Often, however, access to data is not easy, are partially furnished. This has negative effects in terms of efficiency in the dissemination of ongoing researches results and of information completeness and sharing. Paradoxically the increasing number of digital data and formats emphasizes the “access” issues.

Based on content analyses of 653 articles published between 2004 and 2008 in five key journals in the IS field, we demonstrate that the IS discipline exhibits data poverty characteristics as evident by the prevailing data sharing and reuse practices. As a result, the scope and scale of IS research is inhibited and the likelihood of generating far-reaching salient results is low. Finally, we discuss the implications to the IS discipline and draw recommendations for shifting the related practices from a vicious circle of data poverty to a virtuous circle of data richness.