Technical data management system

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]

• Types of data (samples, experiment results, reports, drawings, etc.) and metadata (data that summarizes and describes other data. In this case, it refers to details such as sample sizes, experiment conditions and procedures, dates of reports, explanations of drawings, etc.)[3]
• Means of researches and collections of data (field works, experiments in production lines, etc.)
• Costs of researches
• Policies for access, sharing (re-use within the organisation and re-distribution to the public)
• Proposals for archiving data and maintaining access to it

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]

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.[5]

• Names, labels, values and descriptions for variables and records. (In the case of TDMS, one example is names of equipments on an equipment datasheet)
• Derived data from the original data, with code, algorithm or command file used to create them. (In the case of TDMS, one example is an expectation report derived from the analysis of an equipment datasheet)
• Metadata associates with the data being archived

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]

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.

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.