Technical data management system

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A technical data management system (TDMS) is a document management system (DMS) pertaining to the management of technical and engineering drawings and documents. Often the data are contained in 'records' of various forms, such as on paper, microfilms or digital media. Hence technical data management is also concerned with record management involving technical data. Technical document management systems are used within large organisations with large scale projects involving engineering. For example, a TDMS can be used for integrated steel plants (ISP), automobile factories, aero-space facilities, infrastructure companies, city corporations, research organisations, etc. In such organisations, technical archives or technical documentation centres are created as central facilities for effective management of technical data and records.

Contents

A simplified example of information flow within a technical data management system Information processing system (english).svg
A simplified example of information flow within a technical data management system

TDMS functions are similar to that of conventional archive functions in concepts, except that the archived materials in this case are essentially engineering drawings, survey maps, technical specifications, plant and equipment data sheets, feasibility reports, project reports, operation and maintenance manuals, standards, etc.

Document registration, indexing, repository management, reprography, etc. are parts of TDMS. Various kinds of sophisticated technologies such as document scanners, microfilming and digitization camera units, wide format printers, digital plotters, software, etc. are available, making TDMS functions an easier process than previous times.

Constituents of a technical data management system

Technical data refers to both scientific and technical information recorded and presented in any form or manner (excluding financial and management information). [1] A Technical Data Management System is created within an organisation for archiving and sharing information such as technical specifications, datasheets and drawings. Similar to other types of data management system, a Technical Data Management System consists of the 4 crucial constituents mentioned below.

Data planning

Data plans (long-term or short-term) are constructed as the first essential step of a proper and complete TDMS. It is created to ultimately help with the 3 other constituents, data acquisition, data management and data sharing. A proper data plan should not exceed 2 pages and should address the following basics: [2]

Data acquisition

Raw data is collected from primary sites of the organisations through the use of modern technologies. [4] Please reference the table below for examples. [4]

OrganisationsRaw DataPrimary SitesTechnologies
Integrated steel plants, automobile factoriesFeasibility reports, equipment datasheets, etc.Test rigs and controlsTransiting software to digitize data and input software for recording report results and details on datasheets
Aero-space facilitiesEngineering drawings, operation manuals, maintenance logs, etc.Engineering labsScanners for engineering drawings, Input software for maintenance logs
City corporationsSurvey maps, population reports, etc.City to be mapped and city that involves the researchDigital cameras for survey maps, Input software for statistics of population

The data collected is then transferred to technical data centres for data management.

Data management

After data acquisition, data is sorted out, whilst useful data is archived, unwanted data is disposed. When managing and archiving data, the features below of the data are considered. [5]

Data sharing

Archived and managed data are accessible to rightful entities. A proper and complete TDMS should share data to a suitable extent, under suitable security, in order to achieve optimal usage of data within the organisation. It aims for easy access when reused by other researchers and hence it enhances other research processes. Data is often referred in other tests and technical specifications, where new analysis is generated, managed and archived again. As a result, data is flowing within the organisation under effective management through the use of TDMS. [6]

Advantages and disadvantages of usage of technical data management systems

There are strengths and weakness when using technical data management systems (TDMS) to archive data. Some of the advantages and disadvantages are listed below. [7] [8] [9]

Advantages

1. Faster and easier data management

Since TDMS is integrated into the organisation's systems, whenever workers develop data files (SolidWorks, AutoCAD, Microsoft Word, etc.), they can also archive and manage data, linking what they need to their current work, at the same time they can also update the archives with useful data. This speeds up working processes and makes them more efficient.

2. Increased security

All data files are centralized, hence internal and external data leakages are less likely to happen, and the data flow is more closely monitored. As a result, data in the organisation is more secured.

3. Increased collaboration within the organisation

Since the data files are centralized and the data flow within the organisation increases, researchers and workers within the organisation are able to work on joint projects. More complex tasks can be performed for higher yields.

4. Compatible to various formats of data

TDMS is compatible to many formats of data, from basic data like Microsoft Words to complex data like voice data. This enhances the quality of the management of data archived.

Disadvantages

1. Higher financial costs

Implementing TDMS into the organisation's systems involves monetary costs. Maintenance costs certain amount of human resources and money as well. These resources involve opportunity costs as they can be utilized in other aspects.

2. Lower stability

Since TDMS manages and centralizes all the data the organisation processes, it links the working processes within the whole organisation together. It also increases the vulnerability of the organisation data network. If TDMS is not stable enough or when it is exposed to hacker and virus attacks, the organisation's data flow might shut down completely, affecting the work in an organisation-wide scale and leading to a lower stability as results.

Comparison between traditional data management approaches and technical data management systems

Test engineers and researchers are facing great challenges in turning complex test results and simulation data into usable information for higher yields of firms. These challenges are listed below. [10]

A company logo for Oracle Oracle logo.svg
A company logo for Oracle

Traditional data management approaches

Many organisations are still applying the conventional file management systems, due to the difficulty in building a proper and complete archives for data management.

The first approach is the simple file-folder system. This costs the problem of ineffectiveness as workers and researchers have to manually go through numerous layers of systems and files for the target data. Moreover, the target data may contain files with different formats and these files may not be stored in the same machine. These files are also easily lost if renamed or moved to another location.

The second approach is conventional databases such as Oracle. These databases are capable of enabling easy search and access of data. However, a great drawback is that huge effort for preparing and modeling the data is required. For large-scale projects, huge monetary costs are induced, and extra IT human resources must be employed for constant handling, expanding and maintaining the inflexible system, which is custom for specific tasks, instead of all tasks. In the long-term, it is not cost-effective.

Technical data management systems (TDMS)

TDMS is developed based on 3 principles, flexible and organized file storage, self-scaling hybrid data index, and an interactive post-processing environment. The system in practical, mainly consists of 3 components, data files with essential and relevant Metadata, data finders for organizing and managing data regardless of files formats, and, a software of searching, analyzing and reporting. With metadata attached to original data files, the data finder can identify different related data files during searches, even if they are in different file formats. TDMS hence allows researchers to search for data like browsing the Internet. Last but not least, it can adapt to changes and update itself according to the changes, unlike databases.

Comparison between strong information systems and weak information systems

Complex organizations may need large amounts of technical information, which can be distributed among several independent archives. Existing approaches span from "no integration" to "strong integration", that is based on a common database or product model. The so-called weak information systems (WIS) [11] lie somewhere in the middle. Their basic concept is to add to the pre-existing information a new layer of multiple partial models of products and processes, so that it is possible to reuse existing databases, to reduce the development from scratch, and to provide evolutionary paths relevant for the development of the WIS. Each partial model may include specific knowledge and it acts as a way to structure and access the information according to a specific user view. The comparison between strong and weak information systems may be summarized as follows:

Strong information systemsWeak information systems
Common data model Multiple specific integration models
Database oriented architecture Integration of multiple data sources by adding integration layers
One shot designGrowing process
Redesign of legacy systemsIntegration of legacy systems

The architecture of a weak information system is composed of:

The integration layer comprises the following sub-layers:

Technical data management systems in terms of regulations in different countries

In some countries, such as in the US, record and document management are considered very vital functions, and much stress is given in the management of Technical Archives. Records and documents coming under the public domain are governed by appropriate laws. [12] However, this has not been so in many underdeveloped and developing nations. For example, India enacted the ' Public Records Act' [13] in 1993. However, many in the country are not aware of the existence of such a law or its importance.

Applications and examples of technical data management systems

Technical Data Management Systems (TDMS) are widely applied across the globe, in different sectors. Some of the examples are listed below.

See also

Related Research Articles

Database Organized collection of data in computing

In computing, a database is an organized collection of data stored and accessed electronically. Small databases can be stored on a file system, while large databases are hosted on computer clusters or cloud storage. The design of databases spans formal techniques and practical considerations including data modeling, efficient data representation and storage, query languages, security and privacy of sensitive data, and distributed computing issues including supporting concurrent access and fault tolerance.

A document management system (DMS) is a system used to receive, track, manage and store documents and reduce paper. Most are capable of keeping a record of the various versions created and modified by different users. In the case of the management of digital documents such systems are based on computer programs. The term has some overlap with the concepts of content management systems. It is often viewed as a component of enterprise content management (ECM) systems and related to digital asset management, document imaging, workflow systems and records management systems.

Digital object identifier ISO standard unique string identifier for a digital object

A digital object identifier (DOI) is a persistent identifier or handle used to uniquely identify various objects, standardized by the International Organization for Standardization (ISO). DOIs are an implementation of the Handle System. They are widely used to identify academic, professional, and government information, such as journal articles, research reports, data sets, and official publications. DOIs have also been used to identify other types of information resources, such as commercial videos.

Product data management (PDM) should not be confused with product information management (PIM). PDM is the name of a business function within product lifecycle management (PLM) that is denotes the management and publication of product data. In software engineering, this is known as version control. The goals of product data management include ensuring all stakeholders share a common understanding, that confusion during the execution of the processes is minimized, and that the highest standards of quality controls are maintained.

A data dictionary, or metadata repository, as defined in the IBM Dictionary of Computing, is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format". Oracle defines it as a collection of tables with metadata. The term can have one of several closely related meanings pertaining to databases and database management systems (DBMS):

In library and archival science, digital preservation is a formal endeavor to ensure that digital information of continuing value remains accessible and usable. It involves planning, resource allocation, and application of preservation methods and technologies, and it combines policies, strategies and actions to ensure access to reformatted and "born-digital" content, regardless of the challenges of media failure and technological change. The goal of digital preservation is the accurate rendering of authenticated content over time. The Association for Library Collections and Technical Services Preservation and Reformatting Section of the American Library Association, defined digital preservation as combination of "policies, strategies and actions that ensure access to digital content over time." According to the Harrod's Librarian Glossary, digital preservation is the method of keeping digital material alive so that they remain usable as technological advances render original hardware and software specification obsolete.

A technology roadmap is a flexible planning technique to support strategic and long-range planning, by matching short-term and long-term goals with specific technology solutions. It is a plan that applies to a new product or process and may include using technology forecasting or technology scouting to identify suitable emerging technologies. It is a known technique to help manage the fuzzy front-end of innovation. It is also expected that roadmapping techniques may help companies to survive in turbulent environments and help them to plan in a more holistic way to include non-financial goals and drive towards a more sustainable development. Here roadmaps can be combined with other corporate foresight methods to facilitate systemic change.

Product information management (PIM) is the process of managing all the information required to market and sell products through distribution channels. This product data is created by an internal organization to support a multichannel marketing strategy. A central hub of product data can be used to distribute information to sales channels such as e-commerce websites, print catalogues, marketplaces such as Amazon and Google Shopping, social media platforms like Instagram and electronic data feeds to trading partners.

A data steward is an oversight or data governance role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the metadata for those data assets. A data steward may share some responsibilities with a data custodian, such as the awareness, accessibility, release, appropriate use, security and management of data. A data steward would also participate in the development and implementation of data assets. A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for.

Geospatial metadata is a type of metadata applicable to geographic data and information. Such objects may be stored in a geographic information system (GIS) or may simply be documents, data-sets, images or other objects, services, or related items that exist in some other native environment but whose features may be appropriate to describe in a (geographic) metadata catalog.

Knowledge Discovery Metamodel (KDM) is a publicly available specification from the Object Management Group (OMG). KDM is a common intermediate representation for existing software systems and their operating environments, that defines common metadata required for deep semantic integration of Application Lifecycle Management tools. KDM was designed as the OMG's foundation for software modernization, IT portfolio management and software assurance. KDM uses OMG's Meta-Object Facility to define an XMI interchange format between tools that work with existing software as well as an abstract interface (API) for the next-generation assurance and modernization tools. KDM standardizes existing approaches to knowledge discovery in software engineering artifacts, also known as software mining.

Preservation metadata is item level information that describes the context and structure of a digital object. It provides background details pertaining to a digital object's provenance, authenticity, and environment. Preservation metadata, is a specific type of metadata that works to maintain a digital object's viability while ensuring continued access by providing contextual information, usage details, and rights.

Metadata Data about data

Metadata is "data that provides information about other data", but not the content of the data, such as the text of a message or the image itself. There are many distinct types of metadata, including:

Data Units of information

Data are individual facts, statistics, or items of information, often numeric. In a more technical sense, data are a set of values of qualitative or quantitative variables about one or more persons or objects, while a datum is a single value of a single variable.

A contact manager is a software program that enables users to easily store and find contact information, such as names, addresses, and telephone numbers. They are contact-centric databases that provide a fully integrated approach to tracking all information and communication activities linked to contacts. Simple ones for personal use are included in most smartphones. The main reference standard for contact data and metadata, semantic and interchange, is the vCard.

Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, and can provide a single customer view of the overall data.

A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; this may lead to data being well-managed in the present, and prepared for preservation in the future.

A metadata repository is a database created to store metadata. Metadata is information about the structures that contain the actual data. Metadata is often said to be "data about data", but this is misleading. Data profiles are an example of actual "data about data". Metadata adds one layer of abstraction to this definition– it is data about the structures that contain data. Metadata may describe the structure of any data, of any subject, stored in any format.

The following is provided as an overview of and topical guide to databases:

A machine-readable document is a document whose content can be readily processed by computers. Such documents are distinguished from machine-readable data by virtue of having sufficient structure to provide the necessary context to support the business processes for which they are created.

References

  1. "What is technical data? Definition and meaning". BusinessDictionary.com. WebFinance, Inc. 2015-11-03. Retrieved 2015-11-03.
  2. "Data planning". Data Curation. Penn State University Libraries. 2015-11-03. Retrieved 2015-11-03.
  3. Rouse, Margaret (July 2014). "metadata". WhatIs.com. Search engine optimization (SEO). Retrieved 2015-11-03.
  4. 1 2 3 Finkl, Karl (2015-11-03). "By using powerful default components, TDM, NI DataFinder, and DIAdem, and without using a database, we considerably reduced our creation and maintenance costs". National Instruments. a-solution GmbH. Retrieved 2015-11-03.
  5. "Data Management". Data Curation. Penn State University Libraries. 2015-11-03. Retrieved 2015-11-03.
  6. "Data Sharing". Data Curation. Penn State University Libraries. 2015-11-03. Retrieved 2015-11-03.
  7. "Product Data Management and Product Lifecycle Management(PDM/PLM)". Razorleaf Solutions. Razorleaf Corporation. 2019-08-16. Retrieved 2019-08-16.
  8. Ahmed, Zeeshan; Gerhard, Detlef (2015-11-03). "Contributions of PDM Systems in Organiza- tional Technical Data Management". arXiv: 1008.1321 [cs.OH].
  9. "Calcium - technical data management". Flow Simulation. Flow Simulation Ltd. 2015-11-03. Retrieved 2015-11-03.
  10. "From Raw Data to Engineering Results: The NI Technical Data Management Solution". National Instruments. 2015-10-13. Retrieved 2015-11-03.
  11. Salvaneschi, Paolo; Lazzari, Marco (1997). Weak information systems for technical data management (PDF). Worldwide ECCE Symposium on computers in the practice of building and civil engineering. Lahti, Finland. pp. 310–314. Retrieved 2015-11-29.
  12. Best, Steven J.; Foster, Debbie (January 2009). "Document Management in the Digital Law Office". Law Practice Today. American Bar Association. Retrieved 2015-11-03.
  13. MOHANPURIA, K.L. (1993-12-22). "THE PUBLIC RECORDS ACT, 1993 (India)". Government of India. Archived from the original on 2015-09-10. Retrieved 2015-11-03.
  14. "Knowledge & Technical Data Management". Danburykline. 2015-11-03. Retrieved 2015-11-03.
  15. "Data availability". Test engineering Technical data management. Berghof. 2015-11-03. Retrieved 2015-11-03.

Further reading