WISeREP - An Interactive Supernova Data Repository

We have entered an era of massive data sets in astronomy. In particular, the number of supernova (SN) discoveries and classifications has substantially increased over the years from few tens to thousands per year. It is no longer the case that observations of a few prototypical events encapsulate most spectroscopic information about SNe, motivating the development of modern tools to collect, archive, organize and distribute spectra in general, and SN spectra in particular. For this reason we have developed the Weizmann Interactive Supernova data REPository - WISeREP - an SQL-based database (DB) with an interactive web-based graphical interface. The system serves as an archive of high quality SN spectra, including both historical (legacy) data as well as data that is accumulated by ongoing modern programs. The archive provides information about objects, their spectra, and related meta-data. Utilizing interactive plots, we provide a graphical interface to visualize data, perform line identification of the major relevant species, determine object redshifts, classify SNe and measure expansion velocities. Guest users may view and download spectra or other data that have been placed in the public domain. Registered users may also view and download data that are proprietary to specific programs with which they are associated. The DB currently holds >8000 spectra, of which >5000 are public; the latter include published spectra from the Palomar Transient Factory, all of the SUSPECT archive, the Caltech-Core-Collapse Program, the CfA SN spectra archive and published spectra from the UC Berkeley SNDB repository. It offers an efficient and convenient way to archive data and share it with colleagues, and we expect that data stored in this way will be easy to access, increasing its visibility, usefulness and scientific impact.Comment: To be published in PASP. WISeREP: http://www.weizmann.ac.il/astrophysics/wiserep

Using Provenance to support Good Laboratory Practice in Grid Environments

Conducting experiments and documenting results is daily business of scientists. Good and traceable documentation enables other scientists to confirm procedures and results for increased credibility. Documentation and scientific conduct are regulated and termed as "good laboratory practice." Laboratory notebooks are used to record each step in conducting an experiment and processing data. Originally, these notebooks were paper based. Due to computerised research systems, acquired data became more elaborate, thus increasing the need for electronic notebooks with data storage, computational features and reliable electronic documentation. As a new approach to this, a scientific data management system (DataFinder) is enhanced with features for traceable documentation. Provenance recording is used to meet requirements of traceability, and this information can later be queried for further analysis. DataFinder has further important features for scientific documentation: It employs a heterogeneous and distributed data storage concept. This enables access to different types of data storage systems (e. g. Grid data infrastructure, file servers). In this chapter we describe a number of building blocks that are available or close to finished development. These components are intended for assembling an electronic laboratory notebook for use in Grid environments, while retaining maximal flexibility on usage scenarios as well as maximal compatibility overlap towards each other. Through the usage of such a system, provenance can successfully be used to trace the scientific workflow of preparation, execution, evaluation, interpretation and archiving of research data. The reliability of research results increases and the research process remains transparent to remote research partners.Comment: Book Chapter for "Data Provenance and Data Management for eScience," of Studies in Computational Intelligence series, Springer. 25 pages, 8 figure

The XENON1T Data Distribution and Processing Scheme

The XENON experiment is looking for non-baryonic particle dark matter in the universe. The setup is a dual phase time projection chamber (TPC) filled with 3200 kg of ultra-pure liquid xenon. The setup is operated at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. We present a full overview of the computing scheme for data distribution and job management in XENON1T. The software package Rucio, which is developed by the ATLAS collaboration, facilitates data handling on Open Science Grid (OSG) and European Grid Infrastructure (EGI) storage systems. A tape copy at the Center for High Performance Computing (PDC) is managed by the Tivoli Storage Manager (TSM). Data reduction and Monte Carlo production are handled by CI Connect which is integrated into the OSG network. The job submission system connects resources at the EGI, OSG, SDSC's Comet, and the campus HPC resources for distributed computing. The previous success in the XENON1T computing scheme is also the starting point for its successor experiment XENONnT, which starts to take data in autumn 2019.Comment: 8 pages, 2 figures, CHEP 2018 proceeding

Identification of Design Principles

This report identifies those design principles for a (possibly new) query and transformation language for the Web supporting inference that are considered essential. Based upon these design principles an initial strawman is selected. Scenarios for querying the Semantic Web illustrate the design principles and their reflection in the initial strawman, i.e., a first draft of the query language to be designed and implemented by the REWERSE working group I4

RACOFI: A Rule-Applying Collaborative Filtering System

In this paper we give an overview of the RACOFI (Rule-Applying Collaborative Filtering) multidimensional rating system and its related technologies. This will be exemplified with RACOFI Music, an implemented collaboration agent that assists on-line users in the rating and recommendation of audio (Learning) Objects. It lets users rate contemporary Canadian music in the five dimensions of impression, lyrics, music, originality, and production. The collaborative filtering algorithms STI Pearson, STIN2, and the Per Item Average algorithms are then employed together with RuleML-based rules to recommend music objects that best match user queries. RACOFI has been on-line since August 2003 at http://racofi.elg.ca.

MDA-based ATL transformation to generate MVC 2 web models

Development and maintenance of Web application is still a complex and error-prone process. We need integrated techniques and tool support for automated generation of Web systems and a ready prescription for easy maintenance. The MDA approach proposes an architecture taking into account the development and maintenance of large and complex software. In this paper, we apply MDA approach for generating PSM from UML design to MVC 2Web implementation. That is why we have developed two meta-models handling UML class diagrams and MVC 2 Web applications, then we have to set up transformation rules. These last are expressed in ATL language. To specify the transformation rules (especially CRUD methods) we used a UML profiles. To clearly illustrate the result generated by this transformation, we converted the XMI file generated in an EMF (Eclipse Modeling Framework) model.Comment: International Journal of Computer Science & Information Technology-201