A paper presented by Manjula Patel (UKOLN) at the 4th International Digital Curation Conference, Edinburgh, 1-3rd December 2008, http://www.dcc.ac.uk/events/dcc-2008/programme/
The Role of OAIS Representation Information in the Digital Curation of Crysta...ManjulaPatel
A presentation given by Manjula Patel (UKOLN, University of Bath) and Simon Coles (EPSRC NCS, University of Southampton) at the 5th IEEE International Conference on e-Science
9-11th December 2009, Oxford, UK
Integrated research data management in the Structural SciencesManjulaPatel
A presentation given by Manjula Patel (UKOLN, University of Bath) at the I2S2 workshop "Scaling Up to Integrated Research Data Management", IDCC 2010, 6th December 2010, Chicago.
http://www.ukoln.ac.uk/projects/I2S2/events/IDCC-2010-ScalingUp-Wksp/
Curation and Preservation of Crystallography DataManjulaPatel
A presentation given by Manjula Patel (UKOLN) at "Chemistry in the Digital Age: A Workshop connecting research and education", June 11-12th 2009, Penn State University,
http://www.chem.psu.edu/cyberworkshop09
A presentation given by Manjula Patel (UKOLN) at the Repository Curation Environments (RECURSE) Workshop held at the 4th International Digital Curation Conference, Edinburgh, 1st December 2008,
http://www.dcc.ac.uk/events/dcc-2008/programme/
This document discusses considerations for data preservation according to information lifecycle management. It covers topics like creation, acquisition, cataloging, storage, preservation, and access of digital information. For each topic, it provides details on standards, strategies, technologies and issues to effectively manage long-term preservation of digital archives.
Reinventing Laboratory Data To Be Bigger, Smarter & FasterOSTHUS
• Big Data technologies, especially Data Lakes are spreading across many industries at the moment with the hopes that they will provide unprecedented capabilities for data integration and data analytics
• In spite of the popularity and promise of these technology approaches, many early adopters are not seeking immediate solutions to their complex problems. Answers are not simply appearing – this talk will explore this issue more thoroughly
• Of the 4 V’s of Big Data, Data Variety and Data Veracity (uncertainty) are of increasing importance. These can cause barriers to successful integration strategies , which, in turn, can lead to poorly performing analytics.
• The problems of Variety and Veracity can be tackled using a new form of Data Science which combines formal ontologies with statistical heuristics. This talk will explore some key features of these approaches and how they can be developed together in symbiosis – leading to complex models that allow for improved analytics – or as we call it Big Analysis.
• The end result is improved capture of data types/sources, from laboratory instrument data, to clinical data, to regulatory rules & submissions, all the way to business drivers for the enterprise. In the end providing advanced analytics capabilities that can be built as modules and expand across an enterprise.
The Role of OAIS Representation Information in the Digital Curation of Crysta...ManjulaPatel
A presentation given by Manjula Patel (UKOLN, University of Bath) and Simon Coles (EPSRC NCS, University of Southampton) at the 5th IEEE International Conference on e-Science
9-11th December 2009, Oxford, UK
Integrated research data management in the Structural SciencesManjulaPatel
A presentation given by Manjula Patel (UKOLN, University of Bath) at the I2S2 workshop "Scaling Up to Integrated Research Data Management", IDCC 2010, 6th December 2010, Chicago.
http://www.ukoln.ac.uk/projects/I2S2/events/IDCC-2010-ScalingUp-Wksp/
Curation and Preservation of Crystallography DataManjulaPatel
A presentation given by Manjula Patel (UKOLN) at "Chemistry in the Digital Age: A Workshop connecting research and education", June 11-12th 2009, Penn State University,
http://www.chem.psu.edu/cyberworkshop09
A presentation given by Manjula Patel (UKOLN) at the Repository Curation Environments (RECURSE) Workshop held at the 4th International Digital Curation Conference, Edinburgh, 1st December 2008,
http://www.dcc.ac.uk/events/dcc-2008/programme/
This document discusses considerations for data preservation according to information lifecycle management. It covers topics like creation, acquisition, cataloging, storage, preservation, and access of digital information. For each topic, it provides details on standards, strategies, technologies and issues to effectively manage long-term preservation of digital archives.
Reinventing Laboratory Data To Be Bigger, Smarter & FasterOSTHUS
• Big Data technologies, especially Data Lakes are spreading across many industries at the moment with the hopes that they will provide unprecedented capabilities for data integration and data analytics
• In spite of the popularity and promise of these technology approaches, many early adopters are not seeking immediate solutions to their complex problems. Answers are not simply appearing – this talk will explore this issue more thoroughly
• Of the 4 V’s of Big Data, Data Variety and Data Veracity (uncertainty) are of increasing importance. These can cause barriers to successful integration strategies , which, in turn, can lead to poorly performing analytics.
• The problems of Variety and Veracity can be tackled using a new form of Data Science which combines formal ontologies with statistical heuristics. This talk will explore some key features of these approaches and how they can be developed together in symbiosis – leading to complex models that allow for improved analytics – or as we call it Big Analysis.
• The end result is improved capture of data types/sources, from laboratory instrument data, to clinical data, to regulatory rules & submissions, all the way to business drivers for the enterprise. In the end providing advanced analytics capabilities that can be built as modules and expand across an enterprise.
This document discusses standards and metadata. It defines a standard as a document that provides requirements to ensure materials are fit for their purpose. Metadata is defined as "data about data" that describes other data. The document outlines several important metadata standards like Dublin Core, MARC, EAD, MODS and RDF. It provides details on the purpose and specifications of these standards, noting they are used to enhance accessibility, discovery and preservation of information.
Data repositories -- Xiamen University 2012 06-08Jian Qin
The document discusses data repositories and services. It begins by defining what a data repository is, noting that it is a logical and sometimes physical partitioning of data where multiple databases reside. It then outlines some key aspects of data repositories, including technical features like standards, software, and staffing requirements. The document also discusses functions of repositories like content management, archiving, dissemination and system maintenance. It provides examples of institutional repositories and data repositories, highlighting characteristics of each. Finally, it provides a case study on Dryad, an international repository for data and publications in biosciences.
How Portable Are the Metadata Standards for Scientific Data?Jian Qin
The one-covers-all approach in current metadata standards for scientific data has serious limitations in keeping up with the ever-growing data. This paper reports the findings from a survey to metadata standards in the scientific data domain and argues for the need for a metadata infrastructure. The survey collected 4400+ unique elements from 16 standards and categorized these elements into 9 categories. Findings from the data included that the highest counts of element occurred in the descriptive category and many of them overlapped with DC elements. This pattern also repeated in the elements co-occurred in different standards. A small number of semantically general elements appeared across the largest numbers of standards while the rest of the element co-occurrences formed a long tail with a wide range of specific semantics. The paper discussed implications of the findings in the context of metadata portability and infrastructure and pointed out that large, complex standards and widely varied naming practices are the major hurdles for building a metadata infrastructure.
This document discusses two approaches to incorporating data quality statements into spatial databases. It describes the Vector Product Format (VPF) used by the Digital Chart of the World project, which contains data quality information at different levels to allow users to evaluate data utility. VPF includes seven types of data quality information such as source, positional accuracy, and logical consistency. The document also discusses guidelines from the International Cartographic Association to provide a consistent approach to assessing data quality.
This document discusses a potential new HDF profile called HDF-GEO that would incorporate lessons learned from Earth science data formats. It proposes hosting a discussion at the HDF workshop to discuss the need, scope, and direction for HDF-GEO. The discussion would involve getting input from Earth science practitioners on their data needs and the successful features of existing formats. Key questions are posed around what a profile is, how it relates to standards, and what level of standardization would be useful versus overkill. The goal would be to establish best practices to support geo-referenced and time-series Earth science data.
Metadata for digital long-term preservationMichael Day
Presentation given at the Max Planck Gesellschaft eScience Seminar 2008: Aspects of long-term archiving, hosted by the Gesellschaft für Wissenschaftliche Datenverarbeitung mbh Göttingen (GWDG), Göttingen, Germany, 19-20 June 2008
The document describes the eTRIKS Data Harmonization Service Platform, which aims to provide a common infrastructure and services to support cross-institutional translational research. It discusses challenges around data integration and harmonization. The platform utilizes standards and controlled vocabularies to syntactically and semantically harmonize data from various sources. It employs a metadata framework and modular workflow to structure, standardize, and integrate observational data into a harmonized repository for exploration and analysis. A demo of the platform's capabilities for project setup, data staging, exploration, export, and integration with tranSMART is also provided.
Revolutionizing Laboratory Instrument Data for the Pharmaceutical Industry:...OSTHUS
The Allotrope Foundation is a consortium of major pharmaceutical companies and a partner network whose goal is to address challenges in the pharmaceutical industry by providing a set of public, non-proprietary standards for using and integrating analytical laboratory data. Current challenges in data management within the pharmaceutical industry often center around inconsistent or incomplete data and metadata and proprietary data formats. Because of a lack of standardization, several operations (e.g. integration of instruments/applications, transfer of methods or results, archiving for regulatory purposes) require unnecessary efforts. Further, higher level aggregation of data, e.g. regulatory filings, that are derived from multiple sources of laboratory data are costly to create. These unnecessary costs impact operations within a company’s laboratories, between partnering companies, and between a company and contract research organizations (CROs). Finally, the accelerating transition of laboratories from hybrid (paper + electronic) to purely electronic data streams, coupled with an ever-increasing regulatory scrutiny of electronic data management practices, further require a comprehensive solution. This talk will discuss how The Allotrope Foundation is providing a new framework for data standards through collaboration between numerous stakeholders.
Started in 2004 (under ASTM Committee E13.15) the Analytical Information Markup Language (AnIML) is an XML based standard for capturing, sharing, viewing, and archiving analytical instrument data from any analytical technique.
This paper discusses the AnIML standard in terms of philosophy, structure, usage, and the resources available to work with the standard. Examples will be given for different techniques as well as strategies for migration of legacy data. Finally, the current status of the standard and time frame for promulgation through ASTM will be reported.
Reference Model for an Open Archival Information Systems (OAIS): Overview and...faflrt
ALA/FAFLRT Workshop on Open Archival Information Service (OAIS). Presented by Alan Wood/A.E.Wood & Erickson/Lockheed Martin, Don Sawyer/NASA/GSFC, and Lou Reich/CSC. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 16, 2001 at the ALA Annual Conference.
This document provides an overview of metadata standards, including their purpose and types. It describes the MARC 21 and Dublin Core metadata standards in detail. MARC 21 is the predominant bibliographic standard, with formats for bibliographic data, holdings, and authority data. It exists in both MARC 21 and MARCXML syntaxes. Dublin Core is a simpler standard for resource discovery with 15 basic elements. It includes both simple and qualified versions with controlled vocabularies. The document lists several metadata standards and development organizations.
This presentation discusses the following topics:
Introduction
Objectives
What is Data Mining?
Data Mining Applications
Data Warehousing
Advantages and disadvantages
Trends and Current Issues
Future Research Possibilities
This document discusses knowledge engineering for health and big data. It notes that the rate of data generation is changing but complexity, requirement to use data, and mass of useless data are stable. Knowledge engineering was first defined in 1983 as integrating knowledge into computer systems to solve complex problems. The document discusses building a knowledge engineering community and notes a need for standards around semantics, syntax, technology, and quality. It advocates for a knowledge extraction approach rather than data warehouses and discusses architectural concepts, policy and strategy considerations, and acknowledges GEN2PHEN partners and funding sources.
Dataset description: DCAT and other vocabulariesValeria Pesce
This document discusses metadata needed to describe datasets for applications to find and understand them when stored in data catalogs or repositories. It examines existing dataset description vocabularies like DCAT and their limitations in fully capturing necessary metadata.
Key points made:
- Machine-readable metadata is important for datasets to be discoverable and usable by applications when stored across repositories.
- Metadata should describe the dataset, distributions, dimensions, semantics, protocols/APIs, subsets etc.
- Vocabularies like DCAT provide some metadata but don't fully cover dimensions, semantics, protocols/APIs or subsets.
- No single vocabulary or data catalog solution currently provides all necessary metadata for full semantic interoperability.
HDF5 has already demonstrated its ability to adapt to diverse applications, and to integrate with other standards, e.g., netCDF. The National Imagery Transfer Format (NITF) is another format which might benefit from HDF5 as it evolves.
NITF is the mandated standard for formatting digital imagery and imagery-related products, and exchanging them among the DoD and a number of US government agencies.
Although NITF has been improved over the years, and although designed to be extensible, there are technical and conceptual limits to its original paradigm: mono- and polychromatic images, symbols, text and associated data. NITF has been a mandated standard for many years, and enterprise architectures have been built around it. There are important reasons why it should be retained.
New sensors and algorithms are at the verge of stressing the standard with multispectral, hyperspectral, extended response, variable scale, time series, radar, video, and multisensor fusion products. Metadata are becoming more complex as the need for annotation and supporting data grows. Some imagery-like products are already originated in HDF, and others would benefit from a flexible format such as HDF.
Portions of the NITF user community are exploring ways to move beyond its limits, to incorporate enhanced metadata, and to set procedures for suitable product profiles. This presentation develops a mapping between HDF5 and NITF structures and features. It concludes with some ideas on how NITF could be extended by harmonization with HDF5, while affording minimal disruption to operational uses.
Where is the opportunity for libraries in the collaborative data infrastructure?LIBER Europe
Presentation by Susan Reilly at Bibsys2013 on the opportunties for libraries and their role in the collaborative data infrastructure. Looks at data sharing, authentication, preservation and advocacy.
Over the past decade, as the scholarly community’s reliance on e-content has increased, so too has the development of preservation-related digital repositories. The need for descriptive, administrative, and structural metadata for each digital object in a preservation repository was clearly recognized by digital archivists and curators. However, in the early 2000’s, most of the published specifications for preservation-related metadata were either implementation specific or broadly theoretical. In 2003, the Online Computer Library Center (OCLC) and Research Libraries Group (RLG) established an international working group called PREMIS (Preservation Metadata: Implementation Strategies) to develop a common core set of metadata elements for digital preservation. The first version of the PREMIS Data Dictionary for Preservation Metadata and its supporting XML schema was issued in 2005. Experience using its specifications in preservation repositories has led to several revisions, with the completion of a version 2.0 in 2008. The Data Dictionary is now in version 2.2 (July 2012), and it is widely implemented in preservation repositories throughout the world in multiple domains.
Applying Digital Library Metadata StandardsJenn Riley
Riley, Jenn. "Applying Digital Library Metadata Standards." Presentation sponsored by the Private Academic Library Network of Indiana (PALNI), May 9, 2006.
This document discusses preservation metadata, which supports the long-term preservation of digital objects. It outlines common types of preservation metadata like fixity, viability, renderability, and authenticity data. Standards for preservation metadata are also examined, including PREMIS and METS, which define the core metadata needed to document digital preservation processes. Issues around implementing preservation metadata schemas and ensuring interoperability are also considered.
Graphic standards and exchange formatskishor kumar
The document discusses graphics standards and the need for data exchange standards when transferring CAD files between different software and hardware platforms. It covers early issues with hardware dependence and the development of device-independent standards like GKS. It also summarizes several important neutral CAD data exchange standards, including DXF, IGES, STEP, and discusses some of their limitations in fully transferring design intent and parametric models. It proposes a macro-parametric approach using standardized modeling commands to improve the exchange of CAD files while maintaining parametric design histories.
Computers are used extensively in two main categories of industrial manufacturing applications: 1) direct computer monitoring and control of manufacturing processes, and 2) various manufacturing support functions through tools like CAD, CAM, CAPP and more. CAD software allows designing digital models of products while CAM software generates CNC programs for machining. Other support functions include planning, quality control and testing. Computers have transformed manufacturing by automating processes and supporting all stages from design to production.
This document discusses standards and metadata. It defines a standard as a document that provides requirements to ensure materials are fit for their purpose. Metadata is defined as "data about data" that describes other data. The document outlines several important metadata standards like Dublin Core, MARC, EAD, MODS and RDF. It provides details on the purpose and specifications of these standards, noting they are used to enhance accessibility, discovery and preservation of information.
Data repositories -- Xiamen University 2012 06-08Jian Qin
The document discusses data repositories and services. It begins by defining what a data repository is, noting that it is a logical and sometimes physical partitioning of data where multiple databases reside. It then outlines some key aspects of data repositories, including technical features like standards, software, and staffing requirements. The document also discusses functions of repositories like content management, archiving, dissemination and system maintenance. It provides examples of institutional repositories and data repositories, highlighting characteristics of each. Finally, it provides a case study on Dryad, an international repository for data and publications in biosciences.
How Portable Are the Metadata Standards for Scientific Data?Jian Qin
The one-covers-all approach in current metadata standards for scientific data has serious limitations in keeping up with the ever-growing data. This paper reports the findings from a survey to metadata standards in the scientific data domain and argues for the need for a metadata infrastructure. The survey collected 4400+ unique elements from 16 standards and categorized these elements into 9 categories. Findings from the data included that the highest counts of element occurred in the descriptive category and many of them overlapped with DC elements. This pattern also repeated in the elements co-occurred in different standards. A small number of semantically general elements appeared across the largest numbers of standards while the rest of the element co-occurrences formed a long tail with a wide range of specific semantics. The paper discussed implications of the findings in the context of metadata portability and infrastructure and pointed out that large, complex standards and widely varied naming practices are the major hurdles for building a metadata infrastructure.
This document discusses two approaches to incorporating data quality statements into spatial databases. It describes the Vector Product Format (VPF) used by the Digital Chart of the World project, which contains data quality information at different levels to allow users to evaluate data utility. VPF includes seven types of data quality information such as source, positional accuracy, and logical consistency. The document also discusses guidelines from the International Cartographic Association to provide a consistent approach to assessing data quality.
This document discusses a potential new HDF profile called HDF-GEO that would incorporate lessons learned from Earth science data formats. It proposes hosting a discussion at the HDF workshop to discuss the need, scope, and direction for HDF-GEO. The discussion would involve getting input from Earth science practitioners on their data needs and the successful features of existing formats. Key questions are posed around what a profile is, how it relates to standards, and what level of standardization would be useful versus overkill. The goal would be to establish best practices to support geo-referenced and time-series Earth science data.
Metadata for digital long-term preservationMichael Day
Presentation given at the Max Planck Gesellschaft eScience Seminar 2008: Aspects of long-term archiving, hosted by the Gesellschaft für Wissenschaftliche Datenverarbeitung mbh Göttingen (GWDG), Göttingen, Germany, 19-20 June 2008
The document describes the eTRIKS Data Harmonization Service Platform, which aims to provide a common infrastructure and services to support cross-institutional translational research. It discusses challenges around data integration and harmonization. The platform utilizes standards and controlled vocabularies to syntactically and semantically harmonize data from various sources. It employs a metadata framework and modular workflow to structure, standardize, and integrate observational data into a harmonized repository for exploration and analysis. A demo of the platform's capabilities for project setup, data staging, exploration, export, and integration with tranSMART is also provided.
Revolutionizing Laboratory Instrument Data for the Pharmaceutical Industry:...OSTHUS
The Allotrope Foundation is a consortium of major pharmaceutical companies and a partner network whose goal is to address challenges in the pharmaceutical industry by providing a set of public, non-proprietary standards for using and integrating analytical laboratory data. Current challenges in data management within the pharmaceutical industry often center around inconsistent or incomplete data and metadata and proprietary data formats. Because of a lack of standardization, several operations (e.g. integration of instruments/applications, transfer of methods or results, archiving for regulatory purposes) require unnecessary efforts. Further, higher level aggregation of data, e.g. regulatory filings, that are derived from multiple sources of laboratory data are costly to create. These unnecessary costs impact operations within a company’s laboratories, between partnering companies, and between a company and contract research organizations (CROs). Finally, the accelerating transition of laboratories from hybrid (paper + electronic) to purely electronic data streams, coupled with an ever-increasing regulatory scrutiny of electronic data management practices, further require a comprehensive solution. This talk will discuss how The Allotrope Foundation is providing a new framework for data standards through collaboration between numerous stakeholders.
Started in 2004 (under ASTM Committee E13.15) the Analytical Information Markup Language (AnIML) is an XML based standard for capturing, sharing, viewing, and archiving analytical instrument data from any analytical technique.
This paper discusses the AnIML standard in terms of philosophy, structure, usage, and the resources available to work with the standard. Examples will be given for different techniques as well as strategies for migration of legacy data. Finally, the current status of the standard and time frame for promulgation through ASTM will be reported.
Reference Model for an Open Archival Information Systems (OAIS): Overview and...faflrt
ALA/FAFLRT Workshop on Open Archival Information Service (OAIS). Presented by Alan Wood/A.E.Wood & Erickson/Lockheed Martin, Don Sawyer/NASA/GSFC, and Lou Reich/CSC. Sponsored by ALA Federal and Armed Forces Libraries Roundtable (FAFLRT). Presented on June 16, 2001 at the ALA Annual Conference.
This document provides an overview of metadata standards, including their purpose and types. It describes the MARC 21 and Dublin Core metadata standards in detail. MARC 21 is the predominant bibliographic standard, with formats for bibliographic data, holdings, and authority data. It exists in both MARC 21 and MARCXML syntaxes. Dublin Core is a simpler standard for resource discovery with 15 basic elements. It includes both simple and qualified versions with controlled vocabularies. The document lists several metadata standards and development organizations.
This presentation discusses the following topics:
Introduction
Objectives
What is Data Mining?
Data Mining Applications
Data Warehousing
Advantages and disadvantages
Trends and Current Issues
Future Research Possibilities
This document discusses knowledge engineering for health and big data. It notes that the rate of data generation is changing but complexity, requirement to use data, and mass of useless data are stable. Knowledge engineering was first defined in 1983 as integrating knowledge into computer systems to solve complex problems. The document discusses building a knowledge engineering community and notes a need for standards around semantics, syntax, technology, and quality. It advocates for a knowledge extraction approach rather than data warehouses and discusses architectural concepts, policy and strategy considerations, and acknowledges GEN2PHEN partners and funding sources.
Dataset description: DCAT and other vocabulariesValeria Pesce
This document discusses metadata needed to describe datasets for applications to find and understand them when stored in data catalogs or repositories. It examines existing dataset description vocabularies like DCAT and their limitations in fully capturing necessary metadata.
Key points made:
- Machine-readable metadata is important for datasets to be discoverable and usable by applications when stored across repositories.
- Metadata should describe the dataset, distributions, dimensions, semantics, protocols/APIs, subsets etc.
- Vocabularies like DCAT provide some metadata but don't fully cover dimensions, semantics, protocols/APIs or subsets.
- No single vocabulary or data catalog solution currently provides all necessary metadata for full semantic interoperability.
HDF5 has already demonstrated its ability to adapt to diverse applications, and to integrate with other standards, e.g., netCDF. The National Imagery Transfer Format (NITF) is another format which might benefit from HDF5 as it evolves.
NITF is the mandated standard for formatting digital imagery and imagery-related products, and exchanging them among the DoD and a number of US government agencies.
Although NITF has been improved over the years, and although designed to be extensible, there are technical and conceptual limits to its original paradigm: mono- and polychromatic images, symbols, text and associated data. NITF has been a mandated standard for many years, and enterprise architectures have been built around it. There are important reasons why it should be retained.
New sensors and algorithms are at the verge of stressing the standard with multispectral, hyperspectral, extended response, variable scale, time series, radar, video, and multisensor fusion products. Metadata are becoming more complex as the need for annotation and supporting data grows. Some imagery-like products are already originated in HDF, and others would benefit from a flexible format such as HDF.
Portions of the NITF user community are exploring ways to move beyond its limits, to incorporate enhanced metadata, and to set procedures for suitable product profiles. This presentation develops a mapping between HDF5 and NITF structures and features. It concludes with some ideas on how NITF could be extended by harmonization with HDF5, while affording minimal disruption to operational uses.
Where is the opportunity for libraries in the collaborative data infrastructure?LIBER Europe
Presentation by Susan Reilly at Bibsys2013 on the opportunties for libraries and their role in the collaborative data infrastructure. Looks at data sharing, authentication, preservation and advocacy.
Over the past decade, as the scholarly community’s reliance on e-content has increased, so too has the development of preservation-related digital repositories. The need for descriptive, administrative, and structural metadata for each digital object in a preservation repository was clearly recognized by digital archivists and curators. However, in the early 2000’s, most of the published specifications for preservation-related metadata were either implementation specific or broadly theoretical. In 2003, the Online Computer Library Center (OCLC) and Research Libraries Group (RLG) established an international working group called PREMIS (Preservation Metadata: Implementation Strategies) to develop a common core set of metadata elements for digital preservation. The first version of the PREMIS Data Dictionary for Preservation Metadata and its supporting XML schema was issued in 2005. Experience using its specifications in preservation repositories has led to several revisions, with the completion of a version 2.0 in 2008. The Data Dictionary is now in version 2.2 (July 2012), and it is widely implemented in preservation repositories throughout the world in multiple domains.
Applying Digital Library Metadata StandardsJenn Riley
Riley, Jenn. "Applying Digital Library Metadata Standards." Presentation sponsored by the Private Academic Library Network of Indiana (PALNI), May 9, 2006.
This document discusses preservation metadata, which supports the long-term preservation of digital objects. It outlines common types of preservation metadata like fixity, viability, renderability, and authenticity data. Standards for preservation metadata are also examined, including PREMIS and METS, which define the core metadata needed to document digital preservation processes. Issues around implementing preservation metadata schemas and ensuring interoperability are also considered.
Graphic standards and exchange formatskishor kumar
The document discusses graphics standards and the need for data exchange standards when transferring CAD files between different software and hardware platforms. It covers early issues with hardware dependence and the development of device-independent standards like GKS. It also summarizes several important neutral CAD data exchange standards, including DXF, IGES, STEP, and discusses some of their limitations in fully transferring design intent and parametric models. It proposes a macro-parametric approach using standardized modeling commands to improve the exchange of CAD files while maintaining parametric design histories.
Computers are used extensively in two main categories of industrial manufacturing applications: 1) direct computer monitoring and control of manufacturing processes, and 2) various manufacturing support functions through tools like CAD, CAM, CAPP and more. CAD software allows designing digital models of products while CAM software generates CNC programs for machining. Other support functions include planning, quality control and testing. Computers have transformed manufacturing by automating processes and supporting all stages from design to production.
The document summarizes CATIA product lifecycle management solutions, including:
1) Supporting all stages of product development from concept to manufacturing with integrated CAD, PDM, CAM, and analysis tools.
2) Providing a single, associative 3D model environment to reduce costs and iterations throughout the process.
3) Enabling collaboration, knowledge sharing, and process automation across the product lifecycle.
The document discusses the integration of CAD-CAM systems and shared databases. It describes how CIM (Computer Integrated Manufacturing) helps integrate product design data into manufacturing processes using a common database. This allows different parts of an enterprise to exchange product information and data seamlessly. The key benefits are reduced time and costs, improved quality, and increased flexibility and productivity. Standards like STEP allow different CAD systems to exchange geometric data through neutral file formats. Future areas of work include flexible manufacturing systems and nano-scale metrology and manufacturing.
This document discusses standards for CAD/CAM data exchange and integration. It describes early graphics exchange standards like IGES and DXF that helped with CAD-to-CAD translation but were limited in scope. More comprehensive standards like STEP were later developed to support product lifecycle data exchange. The document also discusses topics like adaptive control systems that optimize machining parameters and computer-integrated manufacturing (CIM) that aims to integrate the entire manufacturing process through information systems.
CADWINFM is software that enables integration of IT and facilities management for data centers. It allows users to create common processes supported by data to provide oversight of operations, environmental management, and critical issues. The software integrates graphic, numeric, and document data for equipment and infrastructure in 2D, 3D and other formats. This centralized information platform allows for optimization of capacity, analysis of best practices, and integration of monitoring tools. CADWINFM creates a dashboard to help manage frequent challenges in data centers like utilization and compliance.
PLM is a tool that helps manage product data and development processes across an organization. It integrates information about products from design through manufacturing and allows for collaboration between teams. Key benefits of PLM include reduced costs, improved quality, and faster time-to-market through features like centralized product information storage, workflow management of development processes, and control of product structures and configurations. PLM systems connect to other enterprise systems like ERP and SCM to share engineering and commercial data.
CDG provides comprehensive engineering design and data conversion services to help engineering organizations overcome budget constraints, deliver high quality products on time and budget, address the shrinking engineering talent pool, and meet requirements for life cycle management. Some of CDG's specialty services include 3D modeling and simulation, weight optimization, discrete design optimization, materials engineering, and safety analysis to help improve functionality, performance and reduce costs while maintaining quality and compliance.
Computer Aided Process Planning Using Neutral File Step for Rotational PartsRSIS International
Present investigation is on process planning using neutral file with format STEP for rotational parts with use of computer. CAE systems involved in every stage of product life cycle mainly uses the product data produced by the CAD systems and integrated manufacturing data produced by CAPP and CAM systems. As the degree of automation and CAD/CAM integration increases, the inclusion of high level information with the product data and its seamless flow in CAD-CAM-CNC chain becomes a necessity. The objective of this work is to develop a Computer Aided Process Planning system for rotational parts using ISO 10303 standard STEP AP224 data exchange file, enabling the inclusion of high level information about the product besides geometry. The developed system aims to incorporate the small and medium sized manufacturing enterprises into the e-manufacturing chain by adopting the NC-code based CNC machine tools without any modification of the controllers.
The document discusses the design of user interfaces for CAD (computer-aided design) systems. It outlines requirements for CAD interfaces to be comprehensive, flexible, responsive, focused, and accessible. The document then explains the design thinking process and how it was used to develop the interface for a CAD system using the Microsoft Fluent UI framework. Examples are provided of how the interface was customized for different users like emergency call takers, fire brigades, and coast guards.
Human Factors in Product Data Management outlines a process for evaluating the usability of Product Data Management (PDM) systems using human factors methods. The process involves:
1. Identifying user profiles and scenarios based on common tasks.
2. Performing a Collaboration Usability Analysis of the tasks and subtasks to evaluate ease of use and learnability.
3. Heuristically evaluating the user interface against standards for suitability, learnability, controllability and error prevention.
4. Scoring and analyzing the results to identify low usability tasks and provide recommendations for improving the system design and user interactions.
This document discusses various standards used in computer-aided design (CAD) and computer-aided manufacturing (CAM). It outlines the need for graphics standards to enable portability and device independence. It then describes several key CAD standards, including those for graphics (GKS, PHIGS), data exchange (IGES, STEP, DXF), and communication (LAN, WAN). It provides more detail on specific standards like IGES, STEP, DXF, and VRML. The document emphasizes that standards are crucial to integrating design and manufacturing processes for maximum efficiency.
The document introduces MOND TM software, which provides a common data model and semantic mapping capabilities to enable quick and easy integration and maintenance of transformations between different platforms and data sources. It discusses challenges with traditional integration approaches and how MOND TM addresses these challenges through features such as template maps and rules, a semantics engine, support for various data formats and protocols, and packaged integration of common standards. The document also outlines the value propositions of MOND TM such as reduced costs, increased flexibility, automation and compliance. It concludes with answering some frequently asked questions about the software.
Collaborative Product Development with 100% Partner ConnectionSEEBURGER
The document discusses collaborative product development through digital connectivity across engineering partners and the entire value chain.
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Strategies for the curation of CAD Engineering Models
1. Strategies for the Curation of CAD Engineering Models 4th International Digital Curation Conference "Radical Sharing: Transforming Science?“ 1 st -3 rd December 2008 Edinburgh, UK Manjula Patel, Alexander Ball, Lian Ding UKOLN, DCC, IdMRC University of Bath, UK
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5. PLM Information Flows Conceptualisation; Design Organisation; Design; Evaluation; Manufacture & Delivery; Sales & Distribution; Service & Support; Decommission & Disposal Pre-existing information & experience Design team Design team In service In service Upgrade Production In service In service Upgrade Production Design Product 1 Product 2 Partners Regulators Customers
17. LiMMA LiMMA (Lightweight Models with Multilayered Annotations) 1. Designers create several annotation documents, at the same time as the CAD model.
18. LiMMA LiMMA (Lightweight Models with Multilayered Annotations) 2. CAD model can be derived to different LWFs for different users requiring different viewpoints: e.g. PRC for manufacturing engineers; JT for assembly engineers
19. LiMMA LiMMA (Lightweight Models with Multilayered Annotations) 3. All users throughout the product lifecycle are able to feedback their knowledge and experiences through annotations rather than modifying the CAD model itself. e.g. service staff can provide information regarding wear and tear.