Aspects of Orthogonality in the Development of the National Digital Wealth ( NDW )

There are presented aspects of orthogonality in the development of the national digital wealth. There is presented the concept of NDW. Are identified quality characteristics. Are built orthogonality metrics for software development applications which are parts of NDW.


National Digital Wealth (NDW)
Digital national wealth is a concept that has emerged with the first electronic computing machines and with the first electronic products developed with them.Emergence of electronic computing machines has led to the development of software products machine code and to the creation of files.The development of hardware and software components led to increased default spectrum applicability of the concept of NDW.NDW concept involves finding solutions for creating software for the NDW development, NDW storage required, and involves the construction of means used to access NDW.NDW is comprised of software, databases, multimedia content, resulted from the digitization process as celluloid filmdigital, music disc -CD, e-learning platforms.NDW components are:  hardware: computers, routers, switches, fiber optic cables, data acquisition equipment -scanner, keyboard, digital camera, microphone, building design tools;  software, which refers to computer applications, software products, along with related files and databases.Unlike other components, NDW software component is the result of intellectual activity.NDW is classified based on several criteria, taking into account the homogenization of the components resulted when applying the classification criteria.
By the criterion of components used NDW:  products used directly to obtain information, services, transactions, results, training of the users;  components that assist software development processes, industries producing consumer goods, industry that produces inputs for the production of consumer goods..By the criterion of using mode, the NDW components NDW are:  produced on a computer, working independently, without interaction with other components and without the need to interconnect with other components;  networking products, network software that can be updated, the update should take into account components compatible versions;  products in which software is on the network server and the database is also in the network..After data entry criterion, the components NDW are:  products which are activated and have no dynamic in terms of taking on new data; are independent components that do not interact with the user;  products that take data, but do not store them, only use them when making selections; for example, the because the takeover by copying parts of existing components in NDW enable versioning, it is important that every developer should take into account the dynamics of its products, so to be in circulation the newest version, which should contain all the facilities required by the previous versions.NDW is a component formed by integrating the entire national wealth which exists in the online environment.Accessing them is done by custom module which allows viewing content rendered through a system connected online.So if the online environment requires adherence to necessary preparatory steps authentication and attribution of rights to view content stored, then NDW enforce procedures; if, however, is not required any authenticate and access is freely then NDW also allows free access to information.

NDW Quality Features
Digital national wealth is a concept with a broad spectrum of application, which requires knowledge of the quality characteristics in order to ensure the optimization of NDW components.NDW quality features are given by the:  reliability, hardware and software, is regarded as a measure of the ability of a NDW component to function properly in the conditions envisaged from the beginning. the totally free accessibility is the characteristic of those informatics applications, equipment, facilitating the access to resources of informatics applications and consist in elimination of any restrictions, so anyone who sits at a terminal that is connected to the Internet, without special identification measurements to be able to access NDW components; through this access level users is able to dispose of all is stored in NDW;  the partially restricted accessibility requires both functions that are freely accessible, without username and password, but also functions for which the user create an account, define a username and password and set those elements which allow him to perform processing; in the case of some applications where users are selected, they receive username, password and after that they access the application;  the restricted accessibility is the feature of informatics applications that address user groups oriented on types of processing involving resources allocation with making payments or additions, alterations, respectively, removal of information; these informatics applications require the rigorous identification of users since there are responsibilities related to the nature of transactions by generated effects; in e-learning systems the tests require strict assessment on student; in electronic payments systems there is identified the account of the payee as well as the account of beneficiary that receives the amounts;  the certified accessibility is a new type to obtain resources or to provide resources in the informational plan, the authentication being performed by electronic signature; the way how the electronic signature is defined gives the same value as a handwritten signature and even more.Indicators are indicative, dynamic and by their aggregation result an indicator that offers a true picture of NDW.

NDW Characteristics of Orthogonality
The concept of orthogonality comes from mathematics.Orthogonality is the indicator that studies the originality of an application based on the criteria of originality.The concept applies to software components, hardware and all data involved in the process of adding to the NDW.Orthogonality establish the measurement in which the NDW components are taken or are specially designed to meet a need established, the hardware components perform functions uniquely, without any two or more hardware components to perform the same or similar activities and how data, information, images, tends to be redundant.Orthogonality identifies those NDW components which must be revised to increase its efficiency, on the basis of orthogonality criteria.Orthogonality indicator is calculated for each criterion, and the results are aggregated using the aggregation formula, resulting HA indicator, given by: where: nthe number of criteria used to analyze the NDW orthogonality; H ithe value of i orthogonality indicator.Orthogonality criteria are dependent on the components evaluated and set standards for review of NDW.Thus, if after determining orthogonality indicator of the component to be included, it has a value below 0.93, its original level is one below the accepted limit and it is recommended not to be included.Orthogonality NDW studying the degree of similarity between two or more components.Through this quality characteristics is determined if NDW meets the criteria of DOI: 10.12948/issn14531305/18.1.2014.08 originality, both the components elements and at a unit level.The concept of orthogonality comes from mathematics, where is considering the following aspects:  two planes are orthogonal if their intersection angle cosine is equal to zero, a finite set of plane is orthogonal if planes are perpendicular in pairs;  two lines are orthogonal if they form congruent adjacent angles, a finite set of lines is orthogonal if the lines are perpendicular in pairs;  two vectors are orthogonal if their dot product is zero, a finite set of vectors is orthogonal if the dot product of any two different vectors is null.Orthogonality is studied on the basis of orthogonality criteria.With these criteria are highlighted features that have the same value for the studied components and are determined levels of similarity.Using the concept of orthogonality is determined degree of similarity in the components already included in the NDW and between the new components to be included, in relation to the items already stored.Based on the characteristics of the components there are defined their quality indicators.Based on these indicators is constructed an indicator that takes into account the values of component indicators.Comparison of two components of NDW is reduced to report a component to the other, namely to identify common parts and parts that differ.There are then compared the corresponding features of the two components.
To study the orthogonality is defined a standardized indicator orthogonality in the range [0, 1], which takes the value 1 if the elements are orthogonal, that have nothing in common and the value 0 if the elements are identical, they have no different values for no feature.If the indicator tends to 1 means that the components of NDW tend to orthogonality , and if the indicator is close to 0 means that the sets of components have many identical elements.

Study of NDW components orthogonality implies orthogonality import definitions and constructing mathematical indicators to be applied on NDW components .
Adapting mathematical formulas imposes studying the similarities between concepts and building indicators that satisfy the demands of working with NDW components.We propose the following algorithm for determining the orthogonality of the two NDW components.In order to compare the new components to be taken in the NDW existing components, should be considered to define the classes of characteristics.Classes of characteristics the qualities of all components included in the NDW, and the quality of future components.Based on the classes of characteristics is provided a new filter for the newest elements, namely originality that new components bring to the NDW.In order to be tested the originality, should be considered an important step, which is to determine which class of characteristics it belongs to the new component.After determining the class of characteristics, there are compared all components already included in NDW with de new component, based on belonging to the same class 's characteristics; for each comparison are taken into account those characteristics for which the two compared terms have the same values.After testing all the components related to new component, the indicator is the aggregated, and if the value is above the threshold of 75 % , it is considered that the new component does not make any original contribution within NDW, otherwise the component is taken in the NDW .There are presented the algorithm P i steps: P 1 there are considered the quality characteristics K 1 , K 2 , ..., K m ; P 2 each characteristics class is composed by the characteristics: K 1 = { k 11 , k 12 , …, k 1n }, K 2 = { k 21 , k 22 , …, k 2n }, ..., K m = { k m1 , k m2 , …, k mn }; P 3 each component already included in NDW is given to a class of characteristics; P 4 it is considered the T digital component which is tested in order to be established if it will be included in NDW; P 5 it is identified the characteristics class to which the T component belongs to; P 6 for all the components already included in NDW and which belongs to the same class of characteristics with the new component, it is calculated the aggregated indicator: , where: T jthe i already included in NDW Tthe component to be included in NDW; mthe number of the characteristics classes; K jithe characteristic for component i for the j class of characteristics; E()the number of characteristics of the class for which the new component and the component already included have similar values.For component to be included it is identified a class of characteristics K T which is the same as the characteristics class for the component already included and in order to establish the degree of originality, compared to NDW components, are aggregates H k indicators.The components' orthogonality is determined as internal and external.Internal orthogonality sets the extent to which the component elements are used repeatedly.External orthogonality shows the differences and similarities that exist between components.
Building orthogonality indicator provides a touch of originality to the items included in the NDW.Storage elements that bring new utility helps to increase NDW, users becoming more interested in share the NDW components.Independent developers develop simultaneously NDW components with the same functionality, aspect which involves the development of the indicators to ensure the inclusion of the original components in the NDW.
In order to establish the components' degree of originality was developed the on-line ORTOES application.This allows the calculation of the orthogonality level for a C++ class of components, composed of 130 components.The ORTOES application presents the characteristics needed to be extended in order to use them to determine the originality of components NDW.

NDW Orthogonality Metrics
Software metric is a mathematical model that contains one or more equations or inequalities, and has one or more objective functions; its role is being to describe the associated system status.Metrics are models implemented to test the quality of NDW components, taking into account factors influencing the measured characteristic.The need to use metrics is given by the following considerations:  Allow setting targets for improvement NDW components;  Provides a real way to achieve these goals;  Allow the identification of the causes that negatively affect the characteristics of NDW quality components;  Identify requirements to be followed for the development of component models qualitatively superior.The metric is a definition, an algorithm or a mathematical function used for quantitative evaluation of the product tested.A metric is designed to achieve the following objectives:  Quantification of characteristics;  Determine the influence of indirect factors;  Aggregation of values;  Hierarchy of components;  Comparative analysis.There are presented the metric's functions: Measurement function, with which is emphasized the quality characteristics measurement level, by expressing the metric units into the measurement units.Comparison function, define the purpose of using the quality metrics, namely to analyze DOI: 10.12948/issn14531305/18.1.2014.08 from the point of view of a quality features parts of NDW and to make comparisons with herself, fitting into a defined category of components, or with other components placing them at a certain stage in the hierarchy.Comparison is limited to the achievement gap between the two terms expressed in the same unit of measure comparing the result to 0, or calculating the ratio , with verifying the result to 1. NUT-the number of users which repeatedly accessed NDW and which after many attempts identified what they were looking for; TNUtotal number of users.RLS is taking value between 0 and 1, the 0 limit showing a small degree of satisfaction.
NDW is an open system, which is based on the concept of inclusion, through is taken new components which are the subject of national wealth in digital form.Acquisition of new components is realized by analyzing their content, as follows:  Identifying the content already stored in NDW;  Strict control of redundancy to provide original content and a high utility to the user;  Analyzing and retrieving components containing complex content;  Implementing processes linking content already stored with new content of the taken components.Determining metrics must meet the theoretical, conceptual described in mathematics and statistics.Primary indicators are those that are obtained by numerical quantification based on considered quality characteristics.Metrics are the way by which numerical form elements that define the quality of the components included in the NDW are translated into results.Implementation of the metrics involves identifying quality characteristics, influencing factors, establishing links between factors of influence, building primary indicators and interpretation of results.

Conclusions
NDW is a complex process that involves analyzing, processing and storage of components which are accessed through an electronic calculating system.The NDW components range from software, hardware and continue with all areas in which they are applicable and useful.Homogenization the NDW content is one aspect that should be considered in identifying, analyzing and incorporating new components.The spread of NDW is an accurate indicator of the level of automation of the company, the degree of socialization of the community members and especially it is an accurate measure of the level of culture and development of the society.NDW evolution involves the acquisition of data so as to enable increasing the utility for the users.In order to include original data, the orthogonality indicators which are testing the components quality should be improved, their range of applicability must be extended so as to improve the quality of NDW components.Building digital wealth leads to a new digital component, namely the knowledge society.

References
Define strategies for future development.NDW study must be approached with the idea of establishing the way forward for increasing the equipment modernization and for increasing skill levels.Implementation and a continuous analysis of NDW increase culture degree, access to information, automation of daily activities and a thorough knowledge of the qualitative aspects of life.NDW data components have the first criterion storage the high levels of accuracy and a redundancy as low as possible.The DNW indicator is estimated starting from the formula:If it is taking into consideration the level of satisfaction for users who accessed NDW, it is determined by applying the formula: where:HW ithe value of i hardware component; SW jthe value of j software component; p1 i , p2 jthe weight of distinct hardware and software components; nhwthe number of hardware the completion of basic cycles, to consider extending the general public;  Development structure for NDW must be built taking into account the maximization of user satisfaction DOI: 10.12948/issn14531305/18.1.2014.08 [1] I. Ivan, C. Ciurea, Gh.Nosca, Economy Informatics, vol.13, no.1-4, 2013, pp.51 -63