Am trying to focus back in on my original assertion about what I was going to study. This was whether there are differences between subjects and their degree of separation from the www, and their primary ontologies. Although I was going to use economics and psychology or perhaps sociology and their attendant ontologies to create a spotlight with which to examine this question, this would still involve looking at the ontologies of a range of other subjects.

I was going to use economics as a focus, as I think it perhaps represents something that might be wrong with how we talk about knowledge in general and reasons for studying, working together, collaborating – ultimately: trust.

A lot of work that we do is tied into research programs that are underwritten by governments as being part of some economic promise. For example, the last Labour government’s education policy was predicated partly on the premise (stemming from research in the 1950s that re-emerged in the 1970s (need to find and cite)) that countries with a more highly educated population tend to do better economically. Thus following Tomlinson’s recommendations, the Diploma system was introduced, only partially, which in fact had the consequence of introducing a system that did the opposite of what he had intended.

This however, being loosely accepted: that the more highly educated a population is, the more wealthy their country, it would seem to follow that it makes sense to make use of emerging technologies to help to educate this population. There is a body of research on this – how technology can be ubiquitous; it can get to the places that teachers can’t, and can help to make learning something that is always ‘on’.

There are actually so many problems with these assertions that it would take a whole other blog post, or perhaps even, essay, or perhaps even, thesis to go into them – but I’m happy to accept that 1) learning is basically a Good Thing and that 2) technology can help to mediate it. I might perhaps then reluctantly accept that it’s possible that if you have a lot of learning, you might end up creating more wealth for your country, however some of the data for this is possibly correlative rather than strongly causal.

But to get back to my original question, it is whether there might be said to be an economics of ontologies? Could we find out whether there are some subjects that lend themselves, via their objects of knowledge to be shared and studied on the web? And that therefore are more accessible and therefore might end up generating more money?

It seems at first glance, that physics might be one of these subjects. Physics research can be large scale and tend to be carried out by large communities who share resources.  Is there something about the nature of physics that makes people more likely to collaborate? Are they perhaps true seekers after knowledge who are less motivated by economics / reward than say, chemists? (Apologies to all you pioneering, truth-seeking chemists out there.) Would this then mean that by the very nature of a subject, if it attracts more people who care more about discovery, or truth, then they may well as a result, collaborate more, and could easily use technology in order to do this, but they care less about creating wealth, so that all web-based subjects that can easily or practically use the web to be studied are never going to be worth funding by governments who only care about short-term goals?

This seems on the face of it, rather facile, but it does intersect with another debate about why there still seem to be less girls studying physics, and in general, science subjects. (This debate appears worldwide, but I shall for now confine myself to the UK.) There was recently some speculation about whether the Big Bang Theory was attracting more people to the subject, but this generated some scathing responses from researchers who had determined that take up of physics was in fact governed by early influences.

Museum Studies

The museums by themselves have different processes and meanings for the population and institutions.  Through these classifications of museums, we can provide a more accurate linkage in between the object of study (or exhibited) and the audience.

Cultural Theory

Through contemporary cultural theory we can incorporate all sort of art practices into the everyday life. This will create our culture. So culture is becoming something less separatist in which art or culture itself no longer belongs to the educated or rich classes. The cultural theory is now being implemented more and more within museums, specially in social history and contemporary collections (Macdondald, 2011). Contemporary cultural theory seeks to utilize culture from a pluralistic perspective.

We inhabit a culture in the sense that we share a certain amount of knowledge and understanding about our environment with others.

We have evolved into a society that shares what Stuart Hall (1997: 18) in Macdonald (2011:18) defines “cultural maps” which makes us question or make judgements the value, status and legitimacy of products or cultural practices.

Within museums we are trying to materialize values and trying to give meaning to objects. For this reason museums within cultural theory are public spaces in which their values and the culture creation is always under debate.

Main theoretical apporach

In order to give meaning to something, we depend on a social construction of a signifying system that creates a shared understanding. The semiotic research of Ferdinand de Saussure, indicates that signifiers and signifieds relate arbitrarily. This means that perhaps the meaning or classification (curation) system to an object could be completely different  from the perspective of a different culture.

When an artifact is being curated, this is attached or linked to an interpretation system that could be attached to a single cultural ‘string’.  Taking the post-structuralist approach, we can provide a structure of interpretation that adapts to the cultural needs of the artifact or the audience. The attempt to materialize culture and present how an object can change through time,  tends to fit to the vision of the post-structuralist thinking.

For this project this could be the way in which post-structuralism becomes the main way of presenting an object of study.  A multi curated object presented from different cultural backgrounds and within different cultural audiences. Although the object can be presented with several meanings, “poststructuralist theory does not automatically imply that the material world ceases to exist” (Macdonald, 2011:21), but it will be understood from different perspectives or meanings.

V&A Mark Lane Archway (Gallery 49)

The Object

Before photography, multimedia and all the new technologies, the object by itself was the way to present the culture or places which it came from. For this reason I think that the object presented should contain enough information to communicate or represent the specific qualities of a culture. When the object is unique it will be a challenge to transmit the embedded information to a replica that could be presented somewhere else.  The use of modern manufacture technology and prototype making can assist with this process.  But it will be the correct adaptation of the object and its environment what will be able to make the correct communication to the audience possible.

Bibliography

MACDONALD, S. 2011. A companion to museum studies, Malden, MA ; Oxford, Wiley-Blackwell.

PEARCE, S. 2001. Interpreting Objects and Collections, Andover, Routledge, 2001.

Information Systems

O’brien (2007) defines an Information system (IS) as any kind of organized combination of people, hardware, software, communications network, data resources, and policies and procedures that stores, retrieves, transforms, and disseminates information in an organization.

The Framework.

There are 5 main areas that build the framework for the information systems.  All these elements play an important role in the process of building the research project.

Foundation Concepts

To develop an information system, it is important to understand the behavioral, technical, business and managerial elements in order to develop the components for the Information System.

Information Technologies

In this area we will focus on the hardware, software, networks and data management that will affect the project in regard of its development, concept development and management.

Business Applications

Concepts like e-commerce can influence or provide ways of how the management can be implemented in an Information System like the one required for the Museum application.

Developments Processes

This will be focusing on the planning, development and implementation of the system(s) to meet the requirements of the problem or situation.

Management Challenges

Through this process, we will focus on delivering and managing effectively the information technologies at the end-user, business or int this case a multiuser/global institution.

Inside Management Systems

There are several types of Information Systems. They are usually classified into two different groups: Operations Support Systems and Management Support Systems.

Operation Support Systems:

• Specialized Processing Systems
• Transaction Processing Systems
• Process Control Systems
• Enterprise Collaboration Systems

Management Support Systems:

• Management Information Systems
• Decision Support Systems
• Executive Information Systems
• Specialized Processing Systems

There are five major resources focusing on the relationship with the IS and the products (O’brien, 2007)

• People Resources
  • Specialists – software developers or system operators
  • End Users – the person who uses the IS
• Hardware Resources
  • Machines – computers, monitors, drives, printers or scanners
  • Media – Storage, disks or paper forms
• Software Resources
  • Programs – operating systems, editors or payroll applications
  • Procedures – data entry procedures, error correction, paycheck distribution procedures
• Data Resources
  • Communication media, communication processors, network access, control software
• Information Products
  • Management reports, business visual display and paper forms

All these elements and areas can help us to visualize the complexity of the development of an Information System. We need to know what do we want from the organisation (system) to do? An organisation that includes people is more complex to manage than one that doesn’t (Wilson, 2001). For this, it is important to analyse the system implemented.  Users or a human response will vary which will vary the judgement of the system.

To avoid judging problems we have to follow a specific methodology.  We have to define a problem first of all. From here we can start gathering the appropriate techniques to solve this problem. The implementation or application of these techniques will allow us to go to the next step if effective or back to the previous one if unsuccessful. We also have to analyse the cost/effective solution.  After these steps we can finally implement the solution.

So we have to solve a problem. But, who is defining the problem. What seems to be problematic for one person can not appar to be so for another one. Wilson (2001) explains that instead of focusing on a person’s problem or a problem, we have to focus on defining a situation that is problematic. I believe this will help the project not to isolate on a single person’s perspective.

Bibliography

O’BRIEN, J. A. & MARAKAS, G. M. 2007. Introduction to information systems, Boston, Mass., McGraw-Hill.

WILSON, B. B. 2001. Soft systems methodology conceptual model building and its contribution, Chichester ;, Wiley,.

Hypothesis and Experimentation

The scientific method

The hypothetico-deductive aspect of the scientific method focuses on the observation.  This observation leads to a guess or logical guess called the hypothesis that tries to explain how a system works.  From there, some predictions are made from this hypothesis and the experimentation or tests begin to try to prove it.

After the experimentation, the results can only be either consistent or inconsistent with the hypothesis.

These sets of experimentation will allow the hypothesis to be more consistent with the implementation of the project.  But it is important to link the results properly with the hypothesis.  This is where the statistics come in.

Statistics

Statistics are use in many different industries. Statistics will allow us to make decisions about large numbers of subjects which we can be able to group into some sort of systems.  This way we can see patterns or data that is not visible through ‘static’ numbers.

It is extremely important to understand how statistics work.  This is due to the necessity to analyse the information inside them.  If we can not produce a proper statistical model, perhaps we won’t be able to make a good decision about our project. Also, if we can not understand statistics, there is no way we can see errors or disprove a theory or result.

Graphs

Once we have developed the statistical models we also have the option of visualizing this data. Or perhaps analyzing more in depth the information provided.

Mean, Error, Percent Error, and Percent Deviation

All these arithmetical/statistical tools can help us to understand our data.  For example the Percent Deviation will allow us to understand or to see the whole extent of the data, not only the mean number.

σ =

∑d2 n-1

Percent Deviation

All statistical models are methods of obtaining the probability of success of our experiments which will help making a decision about our hypothesis or group analysis

Reporting Experiments

Through the report is where the explanation about the study. Peter Harris (2008) points 5 elemental items for the report.

• What you did
• Why you did it
• How you did it
• What were your findings
• What do you think it shows

This can then be translated to a formal document presentation like this:

• Title
• Abstract
• Introduction
• Method
• Results
• Discussion
• References
• Appendices

So, through this report we are intended to provide the information and the appropriate material. For this we also have to consider our reader.  Who is intended to see our information. This is important because perhaps we will have to give an introduction to our area of study. If we are presenting the document to Computer Scientists, perhaps we need to give and induction to Heritage or Visual Communication.

Within museums

The statistics and the report provided is also an intrinsic part of the analysis. Before even starting to provide model experimentation, it is important to provide a hypothesis.  Something like:

• What are the main reasons why small museums don’t have access to big collections?
• How many visitors does each museum have per year/per day/per month?
• How many times does an expensive collection travel through different museums?

It is important to start analyzing this type of information in order to visualize the real requirements not only of the project but also of the museum. problem or situation.

Bibliography

Brookshear, J. G. (2010). Computer science an overview. (11th ed.). Addison-Wesley,.

Harris, P. (Peter R. ). (2008). Designing and reporting experiments in psychology (3rd ed., p. 284). Maidenhead :: Open University Press,

McKillup, S. (2006). Statistics explained an introductory guide for life sciences (p. 267). Cambridge :: Cambridge University Press

Collaborating with other disciplines

Starting from the essential bibliography for this research, there are some elemental concepts that the readings from Frederick Brooks (1995), Peter Harris  (2008) and Brian Wilson (2001).  The methodological process to undertake this project will be very important.  The interdisciplinary quality will bring big challenges in the managerial aspect of the project. At this early stage, I believe the project being an intrinsic part of Web Science will invite collaborative work from Computer Science, Museology, Business Management and Visual Communication among others.

Developing Software?

I will argue that the project will contain a product similar to a computer software product.  This product I believe will be develop similar to software, by this I mean a “collection of programs and the algorithms they represent” (Brookshear, 2010).

The complexity within the development of any kind of software of application requires an understanding of the methodology and the environment in which these products are created. It is also important to learn how to communicate with the team and how to make the team communicate with each other as a managerial task (Brooks, 1995). In the development of software, Brooks (1995) defines some essential tasks:

• Planning
• Coding
• Component test and early system test
• System test, all components in hand

Its about time!

It is important to know how to calculate the time needed for the development of the project and the time needed for each one of the tasks, not only for the implementation of these digital tools, but also for all the research tasks of the project.  If there are some ‘hold backs’ within the project, Brooks (1995) explains that bringing more man work will not only be the solutions due to the tasks required for the development of software.  Therefore it is important to analyse and understand all the different solutions applied within the Computer Science discipline and all the other disciplines involved.

It is recommended to use as little people as possible for the construction of a ‘soft system’. This is due to the managerial problems that big teams create. But sometimes small teams won’t be able to cope with the workload. Based on this, I will argue that it is also important to plan correctly the size of the teams in order for the research project to flow smoothly and with minimum communicative problems.

Assembling the team

It is my perception that is important to understand how a big system team is built in order to continue or to blend the methodological process into that work structure.

Although there are other organizational proposals, the one that seems more traditional is where we find a chief programmer defining the original program and codes and even testing the software. Followed by a co-pilot working as a second hand. There are other team members like the administrator, the editor, secretaries, program clerk, toolsmith, language lawyer and the tester (Brooks, 1995).

Problem solving

The main objective of a program or software is to solve a problem (Brooks, 1995; Wilson, 2001; Harris, 2008).  For this it is essential to define the problem.  What is this set of tools or applications going to solve. Wilson (2001), defines two types of problems: hard problems and soft problems. “The design of a piece of software to meet a given specification is a hard problem (as long as the specification is ‘a given’) whereas the specification of information requirements to meet business needs is a soft problem…”.  The perception of what is a problems is also important.  Being a multidisciplinary project means that what seems to be a problem, it could not mean anything to the person working in the museum or the audience or even the cultural heritage manager.  To solve this, Wilson (2001) suggest that instead of trying to solve a problem, it would be more helpful to try to solve the situation that is creating the problem. For this he proposes the next methodology.

1. Define the situation that is problematic
2. Express the situation (top mapping, rich picture, etc.)
3. Select concepts that may be relevant
4. Assemble concepts into an intellectual structure
5. Use this structure to explore the situation
6. Define changes to the situation (i.e problems to be tackled)
7. Implement change processes

Its all about the good manners.

Both Wilson (2001) and Brooks (1995) express the importance of the way to communicate with other team members.  The ‘hierarchical’ level of communication. During the production of this research project (and any other), which I completely agree is to break the ‘tree’ system in which one person is the boss and the people below are reporting or working for this person.  The responsibilities have been already defined and in the communicative structure, everybody is allowed to participate and to provide solutions to the situation problem solving.

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Museum collaboration // Essential bibliography

In this post I will start to list some of the bibliography to be used to get familiarized with essential concepts and ideas that will allow the project to be carried in the most optimal manner.  The bibliography was chosen from the BSc Information Technology in Organizations fron University of Southampton and readings from Museum Studies and Museology.

Due to my visual communication background the Museum Studies readings I will be focusing on the more challenging theories instead on the basic methodology.  On the other hand, IT in Organizations I will be focusing on basic readings to be able to get familiarized with basic concepts.

Information Technologies in Organizations

Tools and Techniques for IT Modeling

• Peter Harris. Designing and Reporting Experiments in Psychology (2nd ed). OU Press
• Steve McKillup. Statics Explained. Cambridge

Collaborative Projects

• Brooks, FP, The Mythical Man-Month, Addison-Wesley, 1982.
• Checkland, P, and Scholes, J, Soft Systems Methodology, Wiley

Human Computer Interaction

• Dix A, Finlay J, Abowd G and Beale R, Human-Computer Interaction, 3rd Edition. Prentice Hall, 2003
• Norman DA, The Design of Everyday Things, Basic Books, 2002 new edition

Information Systems Strategy

• Bocij, P. et al. (2005) Business Information Systems Technology, Development and Management in E-business. Pearson Higher Education FT Prentice Hall.
• Turban, E., Rainer, R.K. and Potter, R.E. 3rd editon (2004) Introduction to Information Technology: John Wiley and Sons
• Brown, J.S. and Duguid, P. (2002) The Social Life of Information. Harvard Business School
• Simon, J.C. (2000) Introduction to Information Systems. New York: Wiley

Museology and Museum Studies

• Sharon Macdonald. A Companion to Museum Studies, Malden, MA ; Oxford : Blackwell Pub., 2006
• Pearce, Susan. Interpreting Objects and Collections. Andover:Routledge, 2001
• Hein, George E. Learning in the Museum (Museum Meanings) Boulder, Co. netLibrary c2001-c2003
• Poli, C. Mobility and Environment: Humanists versus Engineers in Urban Policy and Professional Education. Dordrecht; New York, Springer c2011

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