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|[ Article ]|
|International Journal of Knowledge Content Development & Technology - Vol. 6, No. 1, pp. 41-68|
|ISSN: 2234-0068 (Print) 2287-187X (Online)|
|Print publication date Jun 2016|
|Received 01 Aug 2015 Revised 06 Oct 2015 Accepted 01 Nov 2015|
|Role of Database Management Systems in Selected Engineering Institutions of Andhra Pradesh: An Analytical Survey|
|*Assistant Professor, Library and Information Science, College of Veterinary Science, Sri Venkateswara Veterinary University, India (email@example.com)|
This paper aims to analyze the function of database management systems from the perspective of librarians working in engineering institutions in Andhra Pradesh. Ninety-eight librarians from one hundred thirty engineering institutions participated in the study. The paper reveals that training by computer suppliers and software packages are the significant mode of acquiring DBMS skills by librarians; three-fourths of the librarians are postgraduate degree holders. Most colleges use database applications for automation purposes and content value. Electrical problems and untrained staff seem to be major constraints faced by respondents for managing library databases.
|Keywords: Databases, Hardware, Software, Backup, Skills
Libraries use Information Technology (IT) to automate an extensive range of administrative and technical processes, to build databases, OPACs, as well as networks, and to offer better services to their users. This widespread application of IT in libraries has created a need to reflect on all aspects of the present library environment. Computers are being used for routine housekeeping activities of the library, which saves the time of the end users as well as library professionals, avoids repetition of work and makes the library services smooth and effective (Sinha, 2000). Figure 1 represents the implications of DBMS in engineering college libraries.
Previous studies using seventy-six librarian subjects (Partridge et al., 2010), which explored the skills, knowledge and attributes required by the contemporary library and information professional in a world of ever changing technology, reported that personality traits, not just qualifications, would be critical to being a successful librarian or information worker in the future. Baro et al. (2013) investigated the achievements of librarians who attended a workshop on e-library services. They reported that the librarians who participated in the workshop were exposed to skills in areas such as database searching, using different search engines, using social media, knowledge of relevant websites, and knowledge of planning for e-libraries. According to the authors, acquiring such skills would enable the librarians to effectively use e-resources and train users on different search strategies.
Enormous studies done all over India on the impact of Information and Communication Technology in engineering institutions (Balu & Reddy, 2011; R. Kumar, 2012; Satpathy & Maharana, 2011; Ramasesh, Chowdappa, & Devi, 2012). The role of DBMS became inevitable in every academic institution, which ultimately transformed the job of a librarian into being an information-specialist. Very few studies made on DBMS in the point of view of librarian. Hence, the present study was carried out in selected institutions of Andhra Pradesh through the perspective of librarians. Librarians were questioned on various modes of acquiring DBMS skills and their application in the libraries. Their responses are analyzed and presented in this paper.
Jean (2011) described the innovative blend of personalization and persuasive technology in the academic library database environment. The paper provided features and options within popular library databases.
Shiva (2005) studied the development of indigenous databases and their benefits for library users in libraries and information centers in the research and development institutions of the Council of Scientific & Industrial Research of North India, and discussed the role of indigenous databases, their development and impact. The paper gave an overview of factors responsible for developing indigenous databases; perceptions of librarians towards them; database forms and formats; database development from a national perspective; database maintenance, services and marketing.
Venkata and Chandrasekhar (2003) discusses planning approaches adopted for IT implementation in Central University Libraries in India, It covers computers and software packages used, computerized library operations, development of databases, bibliographic standards used, computerized information services, and the level of participation in networks and computerized facilities offered to users, etc.
M. Kumar and Kumar (2010) presents a study on issues and strategies in digital library management. The author mentions the managerial issues and strategies needed to understand the function of digital libraries including hardware and software management, and preservation of materials. The author also points out the role of library information science (LIS) professionals in the information and communication technology (ICT) environment such as a collector of data and evaluator of information.
The study aimed to look at the professional and educational implications of librarians who are strongly connected to support environments for academic libraries, particularly with regard to data management and information retrieval. Several academic librarians perceive that the institutions are increasing data management services in the library but they are constrained by gaps in staff skills, knowledge, confidence, and resourcing issues in dealing with these functions. The following are the objectives framed to seek out the areas of concern for the librarians, and the current state of data management in the libraries in order to recommend additional support that is necessary.
Data was collected using a structured questionnaire. One hundred thirty questionnaires were distributed to engineering colleges within the four zones of Andhra Pradesh. Each zone was comprised of three districts except Zone IV, which included four districts. Ten questionnaires were distributed randomly to engineering college libraries (that had digital library and automation services) in each district. Out of 130 questionnaires distributed, 98 were completely filled out and were qualified as valid, which constituted a 75.38% response rate. In this study, the response received for mode of acquiring DBMS skills was vigilantly analyzed using SPSS (Statistical Package for the Social Sciences) software version 19 for statistical analysis of the data. Table 1 illustrates the zone wise distribution of districts (Saidul, 2013) and Figure 2, the sample size.
|S.No||Zone||District||Questionnaires Distributed||Questionnaires Received|
|1||Zone-I||Srikakulam||10 (7.69)||4 (4.08)|
|2||Visakhapatnam||10 (7.69)||9 (9.18)|
|3||Vizianagaram||10 (7.69)||6 (6.12)|
|4||Zone-II||East Godavari||10 (7.69)||8 (8.16)|
|5||West Godavari||10 (7.69)||8 (8.16)|
|6||Krishna||10 (7.69)||9 (9.18)|
|7||Zone-III||Guntur||10 (7.69)||9 (9.18)|
|8||Prakasam||10 (7.69)||6 (6.12)|
|9||Nellore||10 (7.69)||7 (7.14)|
|10||Zone-IV||Anantapur||10 (7.69)||7 (7.14)|
|11||Chittoor||10 (7.69)||9 (9.18)|
|12||Kadapa||10 (7.69)||8 (8.16)|
|13||Kurnool||10 (7.69)||8 (8.16)|
|Total||130 (100)||98 (100)|
Analysis of data was divided into four sections. Part- A provides general information about the respondents. The criterion includes gender, age, educational qualification, and mode of acquiring database management skills. Part-B gives data on information and communication technology facilities available in the engineering college libraries included in the survey. Part- C reveals information about the application of database management in the college libraries using data collected under the following parameters: purpose of database, staff in-charge of database, storage file formats, and device used for data storage, preservation and backup techniques with which they were acquainted. Part - D indicates constraints faced by respondents in performing database management.
Librarianship (Yilmaz, 2012) is a professional career in which there are quantitatively more female workers than males however; library professionals, specifically female librarians (Irvine, 1985), have a negative image in popular culture. Even though studies show that males make up approximately 20% of library staff (Schott & Connor, 2010) Table 2 provides gender wise distribution of respondents, which show that among the total respondents of the survey, 81.33% were male while 18.37% were female.
It should be noted from Table 3 that 39.80% of the respondents fall between the ages of 31-35, 21.43% are between 36-40 years of age and only 8.16% are below 30 years of age.
|1||Below 30||8 (8.16)|
|5||46 Above||14 (14.29)|
Studies have been conducted throughout the world on academic qualification of librarians (de Souza, 2006), in which being a LIS professional was considered as a significant criterion for social identity and professional visibility. Focusing on educational qualification, 64.29% are postgraduate degree holders, 28.57% have completed M. Phil, and 7.14% have attained a doctorate degree. The data is illustrated in Table 4. It is worth noting that the majority of librarians are postgraduate degree holders in the state of Andhra Pradesh, since the basic qualification for a librarian demands this.
|2||Post Graduate||63 (64.29)|
|3||M. Phil||28 (28.57)|
A number of studies were done with the goal of developing an education system for librarianship (Ritchie et al., 2010), their objectives were to determine the future skills, and knowledge necessary. Some of the drivers for changing the profession of librarianship rely on their ability to extract data from organizational databases, respond to academic questions (Casterella & Vijayasarathy, 2013) and support decision-making. Table 5 depicts various means of acquiring database management skills that the respondents have used.
|S.No||Mode of acquiring DBMS Skills||Yes||No|
|1||Through Academic Education||23 (23.47)||75 (76.53)|
|2||Training by Suppliers of Computer and Software Packages||39 (39.80)||59 (60.20)|
|3||Attending Workshops, Seminar, etc.||19 (19.39)||79 (80.61)|
|4||Private Training Program||9 (9.18)||89 (90.82)|
|5||Online Course||8 (8.16)||90 (91.84)|
The majority of the librarians (39.80%) have acquired DBMS skills through training by suppliers of computers and software packages and through academic education (23.47%). Nowadays, courses on DBMS start in school as a vocational training course (Chia-Wen, Pei-Di, & Meng-Chuan, 2011). The vocational schools in Taiwan regard professional certifications as a badge of skills achievement. The teaching in this context usually focuses on how to help students enhance their professional skills and pass the certificate examinations, particularly as this relates to computer courses. The above table denotes that only 8.16% are aware of online courses. A cluster analysis was made for this parameter and a dendogram generated, which is shown in Figure 3.
The major purpose of Cluster Analysis is to group together a collection of objects (e.g. feedback from respondents) into “clusters” so that the objects in the clusters are “similar”. In terms of building prediction and classification models, cluster analysis (Thomas, 2010) can help the analyst identify groups of input variables that in turn can lead to different models for each group. Clustering became a popular software tool to enhance the significance of ranking by grouping items in a typically large list of results. Cluster analysis was based on variables with different scales of measurement across various disciplines worldwide (Chan, 2006; Moon et al., 2005; Hirakue, 2010; Ágústa, 2009; Karunanayake & Haruki, 2014; Bricker, 1991; Dutta, Majumder, & Sen, 2011; Perryman, 2009; Anuradha & Gopalan, 2007; Egea, González, & Menéndez, 2011; Nagata & Klopfer, 2011; Liao & Wen, 2007; Altingovde et al., 2008; Korenius et al., 2006; Kim, Song, & Koo, 2008; Shaw, 1993; Cassisi et al., 2013). The variables and variable codes considered for the cluster analysis representing the mode of acquiring database management skills are shown in Table 6.
|S.No||Variable Code||Mode of Acquiring DBMS Skills|
|1||TAE||Through Academic Education|
|2||TSCSP||Training by Suppliers of Computer and Software Packages|
|3||AWS||Attending Workshops and Seminar, etc.|
|4||PTP||Private Training Programme|
The resulting Dendrogram shown as figure 3
Table 7 provides the results of cluster 1 that includes data on the least frequently attained mode of database management skills; in cluster 1, four variables are grouped as shown in the table. The ratio of agree and disagree is 0.17:1, which can be interpreted as self-study is the least frequent mode of acquiring DBMS skills.
|S.No||Variable Code||Variable Name||Agree||Disagree|
|1||TAE||Through Academic Education||23 (23.47)||75 (76.53)|
|2||AWS||Attending Workshops, Seminar, etc.||19 (19.39)||79 (80.61)|
|3||PTP||Private Training Program||9 (9.18)||89 (90.82)|
|4||SS||Self Study||8 (8.16)||90 (91.84)|
Table 8 gives information on the mode used most frequently to attain database management skills by librarians in the study. In cluster 2 which recorded only a single variable, the agree and disagree ratio was found to be 0.65:1, which can be interpreted that the training by suppliers of computer and software packages seems to be most commonly preferred method for obtaining DBMS skills.
|S.No||Variable Code||Variable Name||Agree||Disagree|
|1||TSCSP||Training by Suppliers of Computer and Software Packages||39 (39.80)||59 (60.20)|
Fortunately, for libraries and librarians, electronic journal terminology and software are heading (Stankus, 1999) for at least a momentary plateau, in which certain terms and technologies will be accepted as standard. Clark (1989) describes some of the available software and hardware tools being used to develop a decision support system, which will be implemented on computers, and discusses activities supported by software including data entry, data coding, finding and combining data, and data compatibility. Hardware considerations include speed, storage capacity, and networking.
Table 9 provides information about hardware availability in the engineering colleges in the study and the ranks given them accordingly. It is obvious from the table that CD/DVD computers seem to be available in all of the libraries (100%). 88.78% libraries are provided with pen drives, and in 74.49% of the college libraries servers are available. Pen drives and servers attained second and third rankings respectively.
|1||Servers||73 (74.49)||25 (25.51)||3|
|2||Computers||98 (100.00)||0 (0.00)||1|
|3||Laptop||8 (8.16)||90 (91.84)||5|
|4||External Hard Disc||41 (41.84)||57 (58.16)||4|
|5||Think Client||18 (18.37)||80 (81.63)||5|
|6||Pen Drive||87 (88.78)||11 (11.22)||2|
|7||CD/DVD Drive||98 (100.00)||0 (0.00)||1|
|8||Others||4 (4.08)||94 (95.92)||6|
Udoh-Ilomechine (2011) investigated the criteria used in the selection of computer hardware and software in six university libraries in Nigeria. The study revealed that the respondents took into account factors such as memory, speed, capacity, durability, costs, reliability and standardization, brand and manufacturer, warranty, and scalability of the system before procuring computer hardware. The respondents also considered the reliability and record of accomplishment of the vendor, service and technical support, previews or sample sections, compatibility with other programs used, product cost, and data migration before procuring computer software. Table 10 reveals significant factors considered by respondents before procuring hardware amenities. The data gives you an idea that price (63.27%) is the most important criteria, followed by manufacturer’s warranty (54.08%). memory is taken into account by 52.04% of librarians.
|1||Memory||51 (52.04)||47 (47.96)|
|2||Speed||43 (43.88)||55 (56.12)|
|3||Capacity||38 (38.78)||60 (61.22)|
|4||Durability||44 (44.90)||54 (55.10)|
|5||Price||62 (63.27)||36 (36.73)|
|6||Reliability||29 (29.59)||69 (70.41)|
|7||Standardization||43 (43.88)||55 (56.12)|
|8||Brand||24 (24.49)||74 (75.51)|
|9||Manufacturer Warranty||53 (54.08)||45 (45.92)|
|10||Scalability||39 (39.80)||50 (51.02)|
Data on software availability is given in Table 11 and ranks provided for the same. Studies report that the MySQL database management system (Dunlap, 2005) offers the combination ideal for developing reliable and scalable Web applications that can store, (Allison, 2012) access, and present information. By using existing SQL/database technology, not only are costs minimal for implementation of the new SQL extension, but users can seamlessly retrieve information (White, 2005) from the database. SQL is the language used by most databases (Wood & Ow, 2005) and advocated as a means to access specific Web data. Structured Query Language (SQL) is said to be relationally complete and used to express any query supported by predicate calculus. The above table shows that MySQL is used in the majority of the engineering college libraries (45.92%); hence MySQL received the ranking of first. Oracle (38.78%) and PostgreSQL (13.27%) secured the second and third rank respectively.
|1||Oracle||38 (38.78)||60 (61.22)||2|
|2||MySQL||45 (45.92)||53 (54.08)||1|
|3||PostgreSQL||13 (13.27)||85 (86.73)||3|
|4||RDM Server||2 (2.04)||96 (97.96)||4|
|5||Dbase||1 (1.02)||97 (98.98)||5|
|6||IBM DB2||1 (1.02)||97 (98.98)||6|
|7||Others||2 (2.04)||96 (97.96)||6|
Table 12 denotes essential factors for decisions regarding software acquisition. 65.31% respondents look at product cost, 63.27% of librarians rely on service and technical support, while 53.06% of the respondents consider compatibility with other programs.
|1||Track Record of the Vendor||49 (50.00)||49 (50.00)|
|2||Service and Technical Support||62 (63.27)||36 (36.73)|
|3||Previews or Sample Sections||38 (38.78)||60 (61.22)|
|4||Compatibility with Other Programs Being Used||52 (53.06)||46 (46.94)|
|5||Product Cost||64 (65.31)||34 (34.69)|
|6||Data Migration||41 (41.84)||57 (58.16)|
Automation in academic libraries (Stuart, 1990) is essential for the development of library databases, access to subjects in relation to external developments, and to improved user service. A question put to users to determine the purpose of using a database, found, as listed in table 13, that 92.86% of librarians use a database for automation while 16.33% rely on a digital library. Various aspects of library automation like circulation, retro-conversion, serial control, information retrieval and dissemination, current awareness of services, selective dissemination of information, bibliographical services, and on-line search of databases seem to be the major criteria for librarians to procure a database; hence, automation is ranked first.
|1||Automation||91 (92.86)||7 (7.14)||1|
|2||Digital Library||16 (16.33)||82 (83.67)||2|
|3||Others||2 (2.04)||96 (97.96)||3|
It can be noted from Table 14 that 29.59% of librarians adopted a database protocol through oral statements, 19.39% submitted a proposal, while only 16.33% provided a written protocol on DBMS.
|1||Written||16 (16.33)||82 (83.67)|
|2||Orally||29 (29.59)||69 (70.41)|
|3||Proposed||19 (19.39)||79 (80.61)|
It is very clear from Table 15 that 75.51% of librarians are in-charge of databases, while 16.33% of system administrators/IT managers take responsibility over management of databases.
|S.No||In- charge of DBMS||Yes||No|
|1||Librarian||74 (75.51)||24 (24.49)|
|2||Library Staff||8 (8.16)||90 (91.84)|
|3||System administrator/IT Manager||16 (16.33)||82 (83.67)|
Respondents responses concerning the criteria of preference for a database for library administration are provided in Table 16. 90.82% of the librarians preferred a database for content value, while 65.31% used databases for archival purposes.
|S.No||In- charge of DBMS||Yes||No|
|1||Archival Value||64 (65.31)||34 (34.69)|
|2||Content Value||89 (90.82)||9 (9.18)|
|3||Rare Data||19 (19.39)||79 (80.61)|
|4||Frequency of Change||23 (23.47)||75 (76.53)|
|5||Other||8 (8.16)||90 (91.84)|
Chester (2006) discusses the ways to archive electronic files for long-term access. The study offers some solutions to the problem of preserving important electronic information. The authors present some formats in which files are converted. They include text format (Scholtes, 2007) particularly for alphanumeric information, XML format, still image formats such as TIFF, and mixed text and picture formats such as HTML, PDF, and JPEG2000. Table 17 gives information about various data storing file formats employed in libraries. Almost all the respondents (100%) are acquainted with the MS-Word file format, 77.55% of the data is stored using the MS-Excel format while 70.41% of the data is stored using the PDF format.
|S.No||In- charge of DBMS||Yes||No|
|1||Word||98 (100.00)||0 (0.00)|
|2||Excel||76 (77.55)||22 (22.45)|
|3||ASCII||32 (32.65)||66 (67.35)|
|4||69 (70.41)||29 (29.59)|
|5||MPEG-4||9 (9.18)||89 (90.82)|
|6||TIFF||1 (1.02)||97 (98.98)|
|7||JPEG||38 (38.78)||60 (61.22)|
|8||Others||3 (3.06)||95 (96.94)|
A radar graph, sometimes called a star or spider graph, is laid out in a circular fashion, rather than the more common (Nancy, 2005; Chambers et al., 1983; Jamali et al., 2014) linear arrangement. As represented in Figure 4, a radar graph consists of axis lines that start in the center of a circle and extend to its periphery. Each axis can represent an independent measure related to data storing file format. This spider chart represents the zone wise distribution versus various data storing file formats used by the engineering colleges in the study. Figure 4 explains that the MS-word, MS-Excel, ASCII, and PDF file formats are the most used by engineering college librarians of Zone IV and the JPEG format is employed in libraries of Zone III.
In the present scenario, the nature and evolution (Malinconico, 1980) of direct access mass storage devices (Kadyszewski, 1977) are matters of particular concern. Studies that have been done focusing on the data storage devices (Veaner, 1983; Templeton, 1976) like CD-ROM and floppy discs indicate that CDs (Ryan, 1993) and floppies have a significant (Anderson & Spike, 2007) impact on centralized depositories, especially as librarians attempt to adapt to the demands of CD-ROM technology. When librarians were queried about the level of contentment with data storage devices their responses, as indicated in table 18, indicated that librarians are more content with computers (62.24%) and pen- drive (39.80%), than the other methods.
|S.No||Data Storage Devices||Excellent||Good||Satisfactory||Poor||No Comments|
|1||Servers||23 (23.47)||51 (52.04)||17 (17.35)||5 (5.10)||2 (2.04)|
|2||Computers||31 (31.63)||61 (62.24)||5 (5.10)||1 (1.02)||0 (0.00)|
|3||Laptop||2 (2.04)||6 (6.12)||0 (0.00)||0 (0.00)||0 (0.00)|
|4||External Hardisc||19 (19.39)||22 (22.45)||0 (0.00)||0 (0.00)||0 (0.00)|
|5||Cloud Storage||8 (8.16)||10 (10.20)||0 (0.00)||0 (0.00)||0 (0.00)|
|6||Pen Drive||26 (26.53)||39 (39.80)||19 (19.39)||2 (2.04)||1 (1.02)|
|7||CD/DVD||9 (9.18)||31 (31.63)||39 (39.80)||10 (10.20)||9 (9.18)|
|8||Others||1 (1.02)||1 (1.02)||1 (1.02)||0 (0.00)||1 (1.02)|
The concept of data integrity in databases (Gross, 1998) is as old as data storage. Various methods have been adopted to check the corruption of data, but they all fall fundamentally into three categories: backup, validation, and security. The following section features the backup practices used in the engineering colleges of Andhra Pradesh in the study.
Studies done on data backup, suggest that institutions (Byers, 2007) must check their backups regularly and determine how often critical data changes to establish the frequency of the backup schedule. It is clear from Table 19 that 62.24% of librarians do backups everyday and 21.43% do them once a week.
|1||Immediately||0 (0.00)||98 (100.00)|
|2||Every Day||61 (62.24)||37 (37.76)|
|3||Once in a Week||21 (21.43)||77 (78.57)|
|4||Once in a Month||10 (10.20)||88 (89.90)|
|5||Once in a Year||6 (6.12)||92 (93.88)|
Different methods have been adopted for database backup. Lohman et al. (1976) described a differential database representation that was shown to be an efficient method for storing large and volatile databases. The technique confines database modifications to a relatively small area of physical storage, and as a result offers two significant operational advantages. First, because the reference point for the database is inherently static, it can be simple and efficiently stored. Moreover, since all modifications to the database are physically localized, the processes of backup and recovery (Breeding, 2010) are relatively fast and inexpensive. With the focus on this type of backup, Table 20 reveals that 68.37% practice manual backup and 19.39% adopt automatic backup.
|1||Full Backup||8 (8.16)||90 (91.84)|
|2||Incremental Backup||4 (4.08)||94 (95.92)|
|3||Automatic Backup||19 (19.39)||79 (80.61)|
|4||Manual Backup||67 (68.37)||31 (31.63)|
Table 21 gives information regarding post backup practice processes. It was determined that 58.16% practice preservation of data while 17.35% adopt restoration processes.
|1||Tagging||7 (7.14)||91 (92.96)|
|2||Classification||6 (6.12)||92 (93.88)|
|3||Verification||3 (3.06)||95 (96.94)|
|4||Authentication||8 (8.16)||87 (88.78)|
|5||Restoration||17 (17.35)||78 (79.59)|
|6||Preservation||57 (58.16)||41 (41.84)|
Even though digitization is not a preservation technique, digitized materials (Palmer, 2008) still need to be protected from adversity caused by a technical or organizational collapse. The study emphasizes the demand for abundant storage and redundant backup routines in digital environments. Steps taken by respondents for preserving database backup are provided in Table 22. 43.88% have opted for cleaning the storage media, while 31.63% store databases in secure and clean environments. For proper backup and safety, it is necessary to take precautions during backup. Some safety measures suggested below might help in maintaining database backup:
|1||Store in Secure & Proper Environment||31 (31.63)||67 (68.37)|
|2||Auditing||13 (13.27)||85 (86.73)|
|3||Migration/Refreshment||9 (9.18)||89 (90.82)|
|4||Replication||2 (2.04)||96 (97.96)|
|5||Cleaning of Storage Media||43 (43.88)||55 (56.12)|
Studies indicate that a library with limited staff, funding, and systems development resources (Piorun & Palmer, 2007) can initiate and support a digital library. Facilitators to success include clear lines of authority, a strong champion, and the appropriate technology for the project. In the context of what is happening in India, libraries are still in the process (Rajesh, 2003) of the automation and digitization of their resources; however, the following table presents some of the hindrances faced by the respondents while managing database in their respective libraries.
Constraints faced by librarians during database management are illustrated in Table 23. Electricity problems (65.31%) were found to be the foremost issue. Additionally 50% of the respondents felt that poor ICT knowledge among staff was the key problem. Constraints are depicted through the radar plot (Figure 5).
The above figure explains that librarians of Zone-II face more constraints in database management with huge data and security issues in the library and electricity problems. Engineering college librarians of Zone-III encounter issues with networking and untrained library staff with the most frequency.
|1||Huge Data for Maintenance and Backup||31 (31.63)||67 (68.37)|
|2||Lack of ICT Resources||16 (16.33)||82 (83.67)|
|3||Lack of Networking||38 (38.78)||60 (61.22)|
|4||Poor ICT Knowledge and Skills among some Staff||49 (50.00)||49 (50.00)|
|5||Lack of Security in Library||19 (19.39)||79 (80.61)|
|6||Electricity Problem||64 (65.31)||34 (34.39)|
|7||Software Version Compatibility||41 (41.84)||57 (58.16)|
|8||Post Backup Issues||33 (33.67)||65 (66.33)|
Librarians are perfectly poised to combine sound pedagogy with their expert knowledge of available digital resources to promote adult achievement in technology education. The most preferred way to obtain needed materials when failing to find information that is required is to approach a librarian directly (Noh et al., 2011). Librarians instruct their communities in the areas of internet searching, electronic database use, and personal computing skills. Many of the information seekers are adults, including other library staff members, community members, and non-traditional students. It is clear from the article that some aspects and components of Database Management Systems are complex and difficult. The librarian has to both learn them thoroughly and familiarize other library staff with them. To overcome the problem we suggest:
The survey showed that none of the library staff had any formal education and training in online searching. Most have learned it on the job, and have learned by trial and error methods. The staff has little time to train themselves, nor do database providers. Database providers generally supply a slide show rather than hands-on training. With regard to staff education and training, the individuals require a broader understanding of the latest research in different disciplines, scholarly landscape, and technology.
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Dr. Kutty. Kumar, Ph.D is presently working as Assistant Professor, Library and Information Science in Sri Venkateswara Veterinary University, College of Veterinary Science, Proddatur. His research focuses on Digital Library Initiatives in Engineering Educational Institutions in Rayalaseema Region of Andhra Pradesh. He has 16 years experience in librarianship in both Engineering and Medical Educational Institutions. Around 51 articles were published in peer reviewed journals, 28 conference proceedings (both National and International) and had attended about 14 workshops and seminars. His subjects of interest include Digital Library, Web Technology, Cloud Computing, Data Mining and Computer Networks.
The following survey conducted to know
Please make it convenient to answer the following simple questions and Tick (✓) in the relevant box, which will hardly take 5 min to complete. I guarantee strict confidentiality to your identity and information provided.
|S.No||Mode of Acquiring DBMS Skills||Yes||No|
|1||Through Academic Education|
|2||Training by Suppliers of Computer and Software Packages|
|3||Attending Workshops, Seminar, etc.|
|4||Private Training Programme|
|1||Track Record of the Vendor|
|2||Service and Technical Support|
|3||Previews or Sample Sections|
|4||Compatibility with other Programs Being Used|
|S.No||Strategy / Protocol||Yes||No|
|S.No||In- charge of DBMS||Yes||No|
|3||System Administrator/IT Manager|
|4||Frequency of Change|
|S.No||Data Storage Devices||Excellent||Good||Satisfactory||Poor||No Comments|
|3||Once in a Week|
|4||Once in a Month|
|5||Once in a Year|
|1||Store in Secure & Proper Environment|
|5||Cleaning of Storage Media|
|1||Huge No of Data for Maintance and Backup|
|2||Lack of ICT Resources|
|3||Lack of Networking|
|4||Poor ICT Knowledge and Skills among Some Staff|
|5||Insecurity in Library|
|7||Software Version Compatibility|
|8||Post Backup Issues|
Thanks for your valuable response