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 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
Raw data is collected from primary sites of the organisations through the use of modern technologies.4 Please reference the table below for examples.5
The data collected is then transferred to technical data centres for 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.6
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.7
There are strengths and weakness when using technical data management systems (TDMS) to archive data. Some of the advantages and disadvantages are listed below.8910
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.
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.
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.
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.
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.
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.
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.11
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.
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.
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)12 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:
The architecture of a weak information system is composed of:
The integration layer comprises the following sub-layers:
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.13 However, this has not been so in many underdeveloped and developing nations. For example, India enacted the ' Public Records Act'14 in 1993. However, many in the country are not aware of the existence of such a law or its importance.
Technical Data Management Systems (TDMS) are widely applied across the globe, in different sectors. Some of the examples are listed below.
Data management solutions are tools and technologies that organizations use to manage their data. These solutions can include a wide range of different tools and technologies, such as databases and data warehouses, data integration and ETL (extract, transform, load) tools, data governance and quality tools, and data visualization and reporting tools. Data management solutions can help organizations store, organize, and manage their data in a more effective and efficient manner. They can also help to improve the accuracy and reliability of the data that is used to make important decisions and enable organizations to gain insights from their data more easily.
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