Towards using ICT to Enhance Flow of Information to aid Farmer Sustainability in Sri Lanka

Farmers need information at all stages of the farming life cycle to make optimal decisions. The required information includes not only prior knowledge but also real time (dynamic) information such as market prices and current production levels. Some valuable information needed by the farmers is produced by government organizations and is available in different locations in different formats. Although farmer is the most important stakeholder in agriculture, there has not been much effort to provide the essential information to farmers on a real time basis. This lack of information is creating many difficulties for farmers as they are not being able to make the correct decisions relating to their farming activities. Through field studies we have identified information required by farmers at various stages of the farming cycle and official sources where this information is available. Next we developed an information flow model that connects various information sources to farmers’ information needs. Based on these findings we are now developing a mobile phone based information system to deliver the required information to farmers in real time

Towards An Agriculture Information Ecosystem

Stakeholders of a domain in their day today activities generate information which is a valuable resource. To obtain full value of this information it should reach right people at the right time. To investigate how this can be achieved we developed an information flow model for agriculture domain by mapping information needed by stakeholders to information generated by others using set of aggregation and disaggregation operators. We found majority of information needs of stakeholders can be fulfilled by applying these operators to information produced by some other stakeholders thus creating a direct benefit to encourage sharing information. This information flow model had many similarities to biological ecosystems where nutrient cycles and energy flows are replaced by information flows. Based on this information ecosystem model we are developing a mobile based information system for farmers in Sri Lanka. Like biological ecosystems information ecosystems will also need time to grow and become sustainable

Towards using ICT to enhance flow of information to aid farmer sustainability in Sri Lanka

Farmers need information at all stages of the farming life cycle to make optimal decisions. The required information includes not only prior knowledge but also real time (dynamic) information such as market prices and current production levels. Some valuable information needed by the farmers is produced by government organizations and is available in different locations in different formats. Although farmer is the most important stakeholder in agriculture, there has not been much effort to provide the essential information to farmers on a real time basis. This lack of information is creating many difficulties for farmers as they are not being able to make the correct decisions relating to their farming activities. Through field studies we have identified information required by farmers at various stages of the farming cycle and official sources where this information is available. Next we developed an information flow model that connects various information sources to farmers&rsquo; information needs. Based on these findings we are now developing a mobile phone based information system to deliver the required information to farmers in real time.<br /

Towards an agriculture knowledge ecosystem :A social life network for farmers in Sri Lanka

We have developed and successfully trialled a Social Life Network (SLN); a Mobile Based Information System to support farming activities in Sri Lanka. It provides information required to support activities such as crop selection and cultivation planning in the context of farmer, farm location, season and task being performed. The system also provides a facility for farmers to sell farming related products and services to other farmers. The final system architecture evolved through a series of iterative relevance and design cycles based on Design Science Research methodology. In the first relevance cycle we identified farmer information needs, their current decision making patterns, and some possible ways to enhance their decision making process. In the first design cycles we developed the initial prototype to visualise a possible solution and in subsequent cycles a crop ontology to reorganise published crop information that would be queried in context and processes to empower farmers. Next we went through 2 cycles of creating functional prototypes, field testing with farmers and improving these to arrive at the final system. We noted that this system can enhance the flow of information in the agriculture domain by aggregating or disaggregating information produced by some stakeholders to be consumed by others. Based on this observation the overall architecture was reconceptualised as a Digital Knowledge Ecosystem

Quality of information for quality of life: Healthcare big data analytics

Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients

Path Index Based Keywords to SPARQL Query Transformation for Semantic Data Federations

Semantic web is a highly emerging research domain. Enhancing the ability of keyword query processing on Semantic Web data provides a huge support for familiarizing the usefulness of Semantic Web to the general public. Most of the existing approaches focus on just user keyword matching to RDF graphs and output the connecting elements as results. Semantic Web consists of SPARQL query language which can process queries more accurately and efficiently than general keyword matching. There are only about a couple of approaches available for transforming keyword queries to SPARQL. They basically rely on real time graph traversals? for identifying subgraphs which can connect user keywords. Those approaches are either limited to query processing on a single data store or a set of interlinked data sets. They have not focused on query processing on a federation of independent data sets which belongs to the same domain. This research proposes a Path Index based approach eliminating real time graph traversal for transforming keyword queries to SPARQL. We have introduced an ontology alignment based approach for keyword query transforming on a federation of RDF data stored using multiple heterogeneous vocabularies. Evaluation shows that the proposed approach have the ability to generate SPARQL queries which can provide highly relevant results for user keyword queries. The Path Index based query transformation approach has also achieved high efficiency compared to the existing approach

Adopting healthcare big data in Sri Lankan healthcare sector

The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life

One Year of One-to-one Computing in Sri Lanka - the Impact on Formal Learning in Primary School Education

One-to-one computing has lately become a frequently used buzzword in the discussions on e-learning in primary education. The main idea in one-to-one computing is to provide every student with a personal computer. This has often been combined with Internet access and the idea to share content but not to share the computers. Some examples of low-cost laptop brands produced for one-to-one computing are Intel Classmate, Asus Eee PC and the One Laptop Per Child (OLPC) XO computer. Different versions of one-to-one computing concept have recently been implemented in the developing world as well as in several developing countries. This study will focus on the Sri Lankan OLPC initiative and data has been gathered from three selected primary schools. In the Sri Lankan OLPC model there is no focus on Internet connectivity and the emphasis is on content development in local languages. Schools chosen in this first one year pilot project are to be classified as to be &#147;the poorest of the poor&#148; and located in rural areas. The research question in this paper is, if and why the introduction of one-to-one computing has had an impact on the formal learning outcomes. Our measurements of the impact on the formal education results are based on data from the selected schools&#146; grading registries, but the general analysis and conclusions are also based on observations and interviews with teachers and school principals. There have also been interviews and discussions with people in charge at the Sri Lankan Ministry of Education. All the visited schools have had technical as well as pedagogical problems during the first year, but findings show that there has been an impact on formal learning in subjects like Mathematics and English. We believe that the Sri Lankan emphasis on content development is part of the explanation but also that the strong commitment amongst teachers and parents has contributed. Our recommendation is that this pilot project should be extended but that the focus should be kept on poor schools in non urban areas. We also give some suggestions on how to improve the content development and how to extend the support to staff and parents at the Sri Lankan OLPC schools

Improving intensive care surveillance protocols

The Intensive Care Unit (ICU) plays a central and pivotal role in the processes of critical care decision-making. Patients in the ICU require immediate critical care regardless of ICU care processes and infrastructure facilities available. Existing clinical evidence and the research gaps suggest that the interchange between the two processes; clinical decision making and protocols are defectively managed. The reasons for this are unclear despite the existence of the critical clinical information integration for a considerable period of time. It is understood that in-effective of the information provided and disconnection between hierarchical structures of the clinical decision makers are a crucial factor for the ICU. The physicians as hierarchical decision makers are playing a vital role in ICU units congested with information from different sources, including clinical notes and reports, flow charts, bedside monitors and laboratory results. Integration between this flows of information is, therefore challenging and useful. Consequently, past research evidence suggests that clinicians with several decades of experience are unable to integrate the information consistently for unknown reasons. Hence, a literature review was undertaken to examine existing solutions. A conceptual model which consists of the components of input case, interface, case library, decision maker, classification, system tuner and knowledge miner was discussed. This is ongoing research which emerges with a conceptual framework of expert clinical decision making processes. Finally the requirements of the case in line with the accessibility, modification and addition modelled using the UPPAAL tool are presented